id	sid	tid	token	lemma	pos
app01-10633	1	1	acta	acta	PROPN
app01-10633	1	2	polytechnica	polytechnica	PROPN
app01-10633	1	3	ctu	ctu	NOUN
app01-10633	1	4	proceedings	proceeding	NOUN
app01-10633	1	5	https://doi.org/10.14311/app.2025.52.0116	https://doi.org/10.14311/app.2025.52.0116	PROPN
app01-10633	1	6	acta	acta	PROPN
app01-10633	1	7	polytechnica	polytechnica	PROPN
app01-10633	1	8	ctu	ctu	NOUN
app01-10633	1	9	proceedings	proceeding	NOUN
app01-10633	1	10	52:116–121	52:116–121	NUM
app01-10633	1	11	,	,	PUNCT
app01-10633	1	12	2025	2025	NUM
app01-10633	1	13	©	©	ADP
app01-10633	1	14	2025	2025	NUM
app01-10633	1	15	the	the	DET
app01-10633	1	16	author(s	author(s	NOUN
app01-10633	1	17	)	)	PUNCT
app01-10633	1	18	.	.	PUNCT
app01-10633	2	1	licensed	license	VERB
app01-10633	2	2	under	under	ADP
app01-10633	2	3	a	a	DET
app01-10633	2	4	cc	cc	NOUN
app01-10633	2	5	-	-	PUNCT
app01-10633	2	6	by	by	ADP
app01-10633	2	7	4.0	4.0	NUM
app01-10633	2	8	licence	licence	NOUN
app01-10633	2	9	published	publish	VERB
app01-10633	2	10	by	by	ADP
app01-10633	2	11	the	the	DET
app01-10633	2	12	czech	czech	PROPN
app01-10633	2	13	technical	technical	PROPN
app01-10633	2	14	university	university	PROPN
app01-10633	2	15	in	in	ADP
app01-10633	2	16	prague	prague	PROPN
app01-10633	2	17	the	the	DET
app01-10633	2	18	effect	effect	NOUN
app01-10633	2	19	of	of	ADP
app01-10633	2	20	roadside	roadside	NOUN
app01-10633	2	21	on	on	ADP
app01-10633	2	22	speed	speed	NOUN
app01-10633	2	23	perception	perception	NOUN
app01-10633	2	24	martin	martin	PROPN
app01-10633	2	25	rak∗	rak∗	PROPN
app01-10633	2	26	,	,	PUNCT
app01-10633	2	27	martin	martin	PROPN
app01-10633	2	28	bilík	bilík	PROPN
app01-10633	2	29	brno	brno	PROPN
app01-10633	2	30	university	university	PROPN
app01-10633	2	31	of	of	ADP
app01-10633	2	32	technology	technology	PROPN
app01-10633	2	33	,	,	PUNCT
app01-10633	2	34	institute	institute	NOUN
app01-10633	2	35	of	of	ADP
app01-10633	2	36	forensic	forensic	ADJ
app01-10633	2	37	engineering	engineering	NOUN
app01-10633	2	38	,	,	PUNCT
app01-10633	2	39	purkyňova	purkyňova	NOUN
app01-10633	3	1	464/118	464/118	PROPN
app01-10633	3	2	,	,	PUNCT
app01-10633	3	3	612	612	NUM
app01-10633	3	4	00	00	NUM
app01-10633	3	5	brno	brno	NOUN
app01-10633	3	6	,	,	PUNCT
app01-10633	3	7	czech	czech	PROPN
app01-10633	3	8	republic	republic	NOUN
app01-10633	3	9	∗	∗	NOUN
app01-10633	3	10	corresponding	correspond	VERB
app01-10633	3	11	author	author	NOUN
app01-10633	3	12	:	:	PUNCT
app01-10633	3	13	martin.rak@vut.cz	martin.rak@vut.cz	PROPN
app01-10633	3	14	abstract	abstract	NOUN
app01-10633	3	15	.	.	PUNCT
app01-10633	4	1	the	the	DET
app01-10633	4	2	study	study	NOUN
app01-10633	4	3	examines	examine	VERB
app01-10633	4	4	how	how	SCONJ
app01-10633	4	5	various	various	ADJ
app01-10633	4	6	roadside	roadside	NOUN
app01-10633	4	7	elements	element	NOUN
app01-10633	4	8	,	,	PUNCT
app01-10633	4	9	such	such	ADJ
app01-10633	4	10	as	as	ADP
app01-10633	4	11	flat	flat	ADJ
app01-10633	4	12	areas	area	NOUN
app01-10633	4	13	,	,	PUNCT
app01-10633	4	14	trees	tree	NOUN
app01-10633	4	15	,	,	PUNCT
app01-10633	4	16	slopes	slope	NOUN
app01-10633	4	17	,	,	PUNCT
app01-10633	4	18	and	and	CCONJ
app01-10633	4	19	buildings	building	NOUN
app01-10633	4	20	,	,	PUNCT
app01-10633	4	21	influence	influence	NOUN
app01-10633	4	22	speed	speed	NOUN
app01-10633	4	23	perception	perception	NOUN
app01-10633	4	24	.	.	PUNCT
app01-10633	5	1	data	datum	NOUN
app01-10633	5	2	from	from	ADP
app01-10633	5	3	multiple	multiple	ADJ
app01-10633	5	4	previous	previous	ADJ
app01-10633	5	5	studies	study	NOUN
app01-10633	5	6	were	be	AUX
app01-10633	5	7	combined	combine	VERB
app01-10633	5	8	and	and	CCONJ
app01-10633	5	9	reanalyzed	reanalyze	VERB
app01-10633	5	10	using	use	VERB
app01-10633	5	11	newly	newly	ADV
app01-10633	5	12	established	establish	VERB
app01-10633	5	13	criteria	criterion	NOUN
app01-10633	5	14	to	to	PART
app01-10633	5	15	assess	assess	VERB
app01-10633	5	16	the	the	DET
app01-10633	5	17	proximity	proximity	NOUN
app01-10633	5	18	and	and	CCONJ
app01-10633	5	19	nature	nature	NOUN
app01-10633	5	20	of	of	ADP
app01-10633	5	21	roadside	roadside	NOUN
app01-10633	5	22	features	feature	NOUN
app01-10633	5	23	.	.	PUNCT
app01-10633	6	1	the	the	DET
app01-10633	6	2	dataset	dataset	NOUN
app01-10633	6	3	includes	include	VERB
app01-10633	6	4	9	9	NUM
app01-10633	6	5	776	776	NUM
app01-10633	6	6	speed	speed	NOUN
app01-10633	6	7	estimates	estimate	NOUN
app01-10633	6	8	,	,	PUNCT
app01-10633	6	9	gathered	gather	VERB
app01-10633	6	10	from	from	ADP
app01-10633	6	11	a	a	DET
app01-10633	6	12	wide	wide	ADJ
app01-10633	6	13	range	range	NOUN
app01-10633	6	14	of	of	ADP
app01-10633	6	15	road	road	NOUN
app01-10633	6	16	types	type	NOUN
app01-10633	6	17	and	and	CCONJ
app01-10633	6	18	surroundings	surrounding	NOUN
app01-10633	6	19	,	,	PUNCT
app01-10633	6	20	allowing	allow	VERB
app01-10633	6	21	for	for	ADP
app01-10633	6	22	an	an	DET
app01-10633	6	23	analysis	analysis	NOUN
app01-10633	6	24	of	of	ADP
app01-10633	6	25	how	how	SCONJ
app01-10633	6	26	these	these	DET
app01-10633	6	27	elements	element	NOUN
app01-10633	6	28	affect	affect	VERB
app01-10633	6	29	speed	speed	NOUN
app01-10633	6	30	estimation	estimation	NOUN
app01-10633	6	31	accuracy	accuracy	NOUN
app01-10633	6	32	.	.	PUNCT
app01-10633	7	1	the	the	DET
app01-10633	7	2	findings	finding	NOUN
app01-10633	7	3	suggest	suggest	VERB
app01-10633	7	4	that	that	SCONJ
app01-10633	7	5	flat	flat	ADJ
app01-10633	7	6	areas	area	NOUN
app01-10633	7	7	consistently	consistently	ADV
app01-10633	7	8	lead	lead	VERB
app01-10633	7	9	to	to	ADP
app01-10633	7	10	overestimations	overestimation	NOUN
app01-10633	7	11	of	of	ADP
app01-10633	7	12	speed	speed	NOUN
app01-10633	7	13	,	,	PUNCT
app01-10633	7	14	likely	likely	ADJ
app01-10633	7	15	due	due	ADP
app01-10633	7	16	to	to	ADP
app01-10633	7	17	the	the	DET
app01-10633	7	18	lack	lack	NOUN
app01-10633	7	19	of	of	ADP
app01-10633	7	20	physical	physical	ADJ
app01-10633	7	21	cues	cue	NOUN
app01-10633	7	22	that	that	PRON
app01-10633	7	23	provide	provide	VERB
app01-10633	7	24	visual	visual	ADJ
app01-10633	7	25	references	reference	NOUN
app01-10633	7	26	.	.	PUNCT
app01-10633	8	1	in	in	ADP
app01-10633	8	2	contrast	contrast	NOUN
app01-10633	8	3	,	,	PUNCT
app01-10633	8	4	trees	tree	NOUN
app01-10633	8	5	and	and	CCONJ
app01-10633	8	6	forested	forest	VERB
app01-10633	8	7	environments	environment	NOUN
app01-10633	8	8	have	have	VERB
app01-10633	8	9	a	a	DET
app01-10633	8	10	stabilizing	stabilize	VERB
app01-10633	8	11	effect	effect	NOUN
app01-10633	8	12	,	,	PUNCT
app01-10633	8	13	helping	help	VERB
app01-10633	8	14	individuals	individual	NOUN
app01-10633	8	15	to	to	PART
app01-10633	8	16	estimate	estimate	VERB
app01-10633	8	17	speed	speed	NOUN
app01-10633	8	18	more	more	ADV
app01-10633	8	19	accurately	accurately	ADV
app01-10633	8	20	.	.	PUNCT
app01-10633	9	1	built	build	VERB
app01-10633	9	2	environments	environment	NOUN
app01-10633	9	3	,	,	PUNCT
app01-10633	9	4	such	such	ADJ
app01-10633	9	5	as	as	ADP
app01-10633	9	6	industrial	industrial	ADJ
app01-10633	9	7	zones	zone	NOUN
app01-10633	9	8	and	and	CCONJ
app01-10633	9	9	urban	urban	ADJ
app01-10633	9	10	areas	area	NOUN
app01-10633	9	11	,	,	PUNCT
app01-10633	9	12	tend	tend	VERB
app01-10633	9	13	to	to	PART
app01-10633	9	14	lead	lead	VERB
app01-10633	9	15	to	to	ADP
app01-10633	9	16	significant	significant	ADJ
app01-10633	9	17	overestimations	overestimation	NOUN
app01-10633	9	18	of	of	ADP
app01-10633	9	19	speed	speed	NOUN
app01-10633	9	20	.	.	PUNCT
app01-10633	10	1	these	these	DET
app01-10633	10	2	results	result	NOUN
app01-10633	10	3	highlight	highlight	VERB
app01-10633	10	4	the	the	DET
app01-10633	10	5	importance	importance	NOUN
app01-10633	10	6	of	of	ADP
app01-10633	10	7	roadside	roadside	ADJ
app01-10633	10	8	environments	environment	NOUN
app01-10633	10	9	in	in	ADP
app01-10633	10	10	influencing	influence	VERB
app01-10633	10	11	speed	speed	NOUN
app01-10633	10	12	perception	perception	NOUN
app01-10633	10	13	,	,	PUNCT
app01-10633	10	14	with	with	ADP
app01-10633	10	15	natural	natural	ADJ
app01-10633	10	16	settings	setting	NOUN
app01-10633	10	17	like	like	ADP
app01-10633	10	18	forests	forest	NOUN
app01-10633	10	19	providing	provide	VERB
app01-10633	10	20	clearer	clear	ADJ
app01-10633	10	21	visual	visual	ADJ
app01-10633	10	22	cues	cue	NOUN
app01-10633	10	23	that	that	PRON
app01-10633	10	24	help	help	VERB
app01-10633	10	25	drivers	driver	NOUN
app01-10633	10	26	and	and	CCONJ
app01-10633	10	27	observers	observer	NOUN
app01-10633	10	28	better	well	ADV
app01-10633	10	29	estimate	estimate	VERB
app01-10633	10	30	speed	speed	NOUN
app01-10633	10	31	.	.	PUNCT
app01-10633	11	1	keywords	keyword	NOUN
app01-10633	11	2	:	:	PUNCT
app01-10633	11	3	speed	speed	NOUN
app01-10633	11	4	perception	perception	NOUN
app01-10633	11	5	,	,	PUNCT
app01-10633	11	6	roadside	roadside	NOUN
app01-10633	11	7	,	,	PUNCT
app01-10633	11	8	perception	perception	NOUN
app01-10633	11	9	accuracy	accuracy	NOUN
app01-10633	11	10	,	,	PUNCT
app01-10633	11	11	speed	speed	NOUN
app01-10633	11	12	estimation	estimation	NOUN
app01-10633	11	13	.	.	PUNCT
app01-10633	12	1	1	1	X
app01-10633	12	2	.	.	X
app01-10633	12	3	introduction	introduction	NOUN
app01-10633	12	4	the	the	DET
app01-10633	12	5	perception	perception	NOUN
app01-10633	12	6	of	of	ADP
app01-10633	12	7	speed	speed	NOUN
app01-10633	12	8	is	be	AUX
app01-10633	12	9	influenced	influence	VERB
app01-10633	12	10	by	by	ADP
app01-10633	12	11	various	various	ADJ
app01-10633	12	12	roadside	roadside	ADJ
app01-10633	12	13	elements	element	NOUN
app01-10633	12	14	.	.	PUNCT
app01-10633	13	1	those	those	PRON
app01-10633	13	2	can	can	AUX
app01-10633	13	3	vary	vary	VERB
app01-10633	13	4	depending	depend	VERB
app01-10633	13	5	on	on	ADP
app01-10633	13	6	the	the	DET
app01-10633	13	7	surrounding	surround	VERB
app01-10633	13	8	area	area	NOUN
app01-10633	13	9	and	and	CCONJ
app01-10633	13	10	can	can	AUX
app01-10633	13	11	include	include	VERB
app01-10633	13	12	trees	tree	NOUN
app01-10633	13	13	,	,	PUNCT
app01-10633	13	14	barriers	barrier	NOUN
app01-10633	13	15	,	,	PUNCT
app01-10633	13	16	slopes	slope	NOUN
app01-10633	13	17	,	,	PUNCT
app01-10633	13	18	buildings	building	NOUN
app01-10633	13	19	,	,	PUNCT
app01-10633	13	20	etc	etc	X
app01-10633	13	21	.	.	X
app01-10633	14	1	these	these	DET
app01-10633	14	2	visual	visual	ADJ
app01-10633	14	3	stimuli	stimulus	NOUN
app01-10633	14	4	can	can	AUX
app01-10633	14	5	provide	provide	VERB
app01-10633	14	6	drivers	driver	NOUN
app01-10633	14	7	feedback	feedback	NOUN
app01-10633	14	8	that	that	PRON
app01-10633	14	9	affects	affect	VERB
app01-10633	14	10	their	their	PRON
app01-10633	14	11	perception	perception	NOUN
app01-10633	14	12	of	of	ADP
app01-10633	14	13	how	how	SCONJ
app01-10633	14	14	fast	fast	ADV
app01-10633	14	15	they	they	PRON
app01-10633	14	16	are	be	AUX
app01-10633	14	17	moving	move	VERB
app01-10633	14	18	and	and	CCONJ
app01-10633	14	19	understanding	understand	VERB
app01-10633	14	20	the	the	DET
app01-10633	14	21	role	role	NOUN
app01-10633	14	22	of	of	ADP
app01-10633	14	23	roadside	roadside	NOUN
app01-10633	14	24	features	feature	NOUN
app01-10633	14	25	in	in	ADP
app01-10633	14	26	speed	speed	NOUN
app01-10633	14	27	perception	perception	NOUN
app01-10633	14	28	.	.	PUNCT
app01-10633	15	1	dense	dense	ADJ
app01-10633	15	2	roadside	roadside	NOUN
app01-10633	15	3	environments	environment	NOUN
app01-10633	15	4	–	–	PUNCT
app01-10633	15	5	trees	tree	NOUN
app01-10633	15	6	,	,	PUNCT
app01-10633	15	7	guardrails	guardrail	NOUN
app01-10633	15	8	,	,	PUNCT
app01-10633	15	9	and	and	CCONJ
app01-10633	15	10	buildings	building	NOUN
app01-10633	15	11	–	–	PUNCT
app01-10633	15	12	create	create	VERB
app01-10633	15	13	a	a	DET
app01-10633	15	14	tunnel	tunnel	NOUN
app01-10633	15	15	effect	effect	NOUN
app01-10633	15	16	.	.	PUNCT
app01-10633	16	1	this	this	DET
app01-10633	16	2	effect	effect	NOUN
app01-10633	16	3	occurs	occur	VERB
app01-10633	16	4	when	when	SCONJ
app01-10633	16	5	visual	visual	ADJ
app01-10633	16	6	stimuli	stimulus	NOUN
app01-10633	16	7	are	be	AUX
app01-10633	16	8	placed	place	VERB
app01-10633	16	9	close	close	ADV
app01-10633	16	10	to	to	ADP
app01-10633	16	11	the	the	DET
app01-10633	16	12	road	road	NOUN
app01-10633	16	13	,	,	PUNCT
app01-10633	16	14	causing	cause	VERB
app01-10633	16	15	a	a	DET
app01-10633	16	16	sensation	sensation	NOUN
app01-10633	16	17	of	of	ADP
app01-10633	16	18	increased	increase	VERB
app01-10633	16	19	speed	speed	NOUN
app01-10633	16	20	as	as	SCONJ
app01-10633	16	21	drivers	driver	NOUN
app01-10633	16	22	pass	pass	VERB
app01-10633	16	23	them	they	PRON
app01-10633	16	24	quickly	quickly	ADV
app01-10633	16	25	.	.	PUNCT
app01-10633	17	1	drivers	driver	NOUN
app01-10633	17	2	often	often	ADV
app01-10633	17	3	respond	respond	VERB
app01-10633	17	4	by	by	ADP
app01-10633	17	5	reducing	reduce	VERB
app01-10633	17	6	speed	speed	NOUN
app01-10633	17	7	,	,	PUNCT
app01-10633	17	8	even	even	ADV
app01-10633	17	9	if	if	SCONJ
app01-10633	17	10	it	it	PRON
app01-10633	17	11	is	be	AUX
app01-10633	17	12	not	not	PART
app01-10633	17	13	excessive	excessive	ADJ
app01-10633	17	14	.	.	PUNCT
app01-10633	18	1	this	this	DET
app01-10633	18	2	reaction	reaction	NOUN
app01-10633	18	3	has	have	AUX
app01-10633	18	4	been	be	AUX
app01-10633	18	5	well	well	ADV
app01-10633	18	6	documented	document	VERB
app01-10633	18	7	in	in	ADP
app01-10633	18	8	urban	urban	ADJ
app01-10633	18	9	environments	environment	NOUN
app01-10633	18	10	,	,	PUNCT
app01-10633	18	11	where	where	SCONJ
app01-10633	18	12	buildings	building	NOUN
app01-10633	18	13	or	or	CCONJ
app01-10633	18	14	other	other	ADJ
app01-10633	18	15	vertical	vertical	ADJ
app01-10633	18	16	elements	element	NOUN
app01-10633	18	17	close	close	ADJ
app01-10633	18	18	to	to	ADP
app01-10633	18	19	the	the	DET
app01-10633	18	20	road	road	NOUN
app01-10633	18	21	create	create	VERB
app01-10633	18	22	a	a	DET
app01-10633	18	23	feeling	feeling	NOUN
app01-10633	18	24	of	of	ADP
app01-10633	18	25	restriction	restriction	NOUN
app01-10633	18	26	that	that	PRON
app01-10633	18	27	prompts	prompt	VERB
app01-10633	18	28	slower	slow	ADJ
app01-10633	18	29	driving	driving	NOUN
app01-10633	18	30	.	.	PUNCT
app01-10633	19	1	guardrails	guardrail	NOUN
app01-10633	19	2	,	,	PUNCT
app01-10633	19	3	similarly	similarly	ADV
app01-10633	19	4	,	,	PUNCT
app01-10633	19	5	add	add	VERB
app01-10633	19	6	to	to	ADP
app01-10633	19	7	this	this	DET
app01-10633	19	8	effect	effect	NOUN
app01-10633	19	9	by	by	ADP
app01-10633	19	10	reinforcing	reinforce	VERB
app01-10633	19	11	the	the	DET
app01-10633	19	12	sense	sense	NOUN
app01-10633	19	13	of	of	ADP
app01-10633	19	14	lane	lane	NOUN
app01-10633	19	15	narrowing	narrowing	NOUN
app01-10633	19	16	,	,	PUNCT
app01-10633	19	17	which	which	PRON
app01-10633	19	18	encourages	encourage	VERB
app01-10633	19	19	cautious	cautious	ADJ
app01-10633	19	20	driving	driving	NOUN
app01-10633	20	1	[	[	X
app01-10633	20	2	1	1	NUM
app01-10633	20	3	,	,	PUNCT
app01-10633	20	4	2	2	NUM
app01-10633	20	5	]	]	PUNCT
app01-10633	20	6	.	.	PUNCT
app01-10633	21	1	in	in	ADP
app01-10633	21	2	contrast	contrast	NOUN
app01-10633	21	3	,	,	PUNCT
app01-10633	21	4	open	open	ADJ
app01-10633	21	5	landscapes	landscape	NOUN
app01-10633	21	6	,	,	PUNCT
app01-10633	21	7	such	such	ADJ
app01-10633	21	8	as	as	ADP
app01-10633	21	9	fields	field	NOUN
app01-10633	21	10	,	,	PUNCT
app01-10633	21	11	sparsely	sparsely	ADV
app01-10633	21	12	vegetated	vegetate	VERB
app01-10633	21	13	areas	area	NOUN
app01-10633	21	14	,	,	PUNCT
app01-10633	21	15	and	and	CCONJ
app01-10633	21	16	wide	wide	ADJ
app01-10633	21	17	,	,	PUNCT
app01-10633	21	18	open	open	ADJ
app01-10633	21	19	spaces	space	NOUN
app01-10633	21	20	,	,	PUNCT
app01-10633	21	21	lead	lead	VERB
app01-10633	21	22	to	to	ADP
app01-10633	21	23	the	the	DET
app01-10633	21	24	opposite	opposite	ADJ
app01-10633	21	25	effect	effect	NOUN
app01-10633	21	26	.	.	PUNCT
app01-10633	22	1	these	these	DET
app01-10633	22	2	environments	environment	NOUN
app01-10633	22	3	tend	tend	VERB
app01-10633	22	4	to	to	PART
app01-10633	22	5	provide	provide	VERB
app01-10633	22	6	fewer	few	ADJ
app01-10633	22	7	visual	visual	ADJ
app01-10633	22	8	cues	cue	NOUN
app01-10633	22	9	,	,	PUNCT
app01-10633	22	10	which	which	PRON
app01-10633	22	11	can	can	AUX
app01-10633	22	12	cause	cause	VERB
app01-10633	22	13	drivers	driver	NOUN
app01-10633	22	14	to	to	PART
app01-10633	22	15	underestimate	underestimate	VERB
app01-10633	22	16	their	their	PRON
app01-10633	22	17	actual	actual	ADJ
app01-10633	22	18	speed	speed	NOUN
app01-10633	22	19	,	,	PUNCT
app01-10633	22	20	leading	lead	VERB
app01-10633	22	21	to	to	ADP
app01-10633	22	22	unintentional	unintentional	ADJ
app01-10633	22	23	speeding	speeding	NOUN
app01-10633	22	24	.	.	PUNCT
app01-10633	23	1	this	this	DET
app01-10633	23	2	effect	effect	NOUN
app01-10633	23	3	is	be	AUX
app01-10633	23	4	most	most	ADV
app01-10633	23	5	commonly	commonly	ADV
app01-10633	23	6	observed	observe	VERB
app01-10633	23	7	on	on	ADP
app01-10633	23	8	highways	highway	NOUN
app01-10633	23	9	and	and	CCONJ
app01-10633	23	10	rural	rural	ADJ
app01-10633	23	11	roads	road	NOUN
app01-10633	23	12	,	,	PUNCT
app01-10633	23	13	with	with	ADP
app01-10633	23	14	minimal	minimal	ADJ
app01-10633	23	15	visual	visual	ADJ
app01-10633	23	16	feedback	feedback	NOUN
app01-10633	23	17	.	.	PUNCT
app01-10633	24	1	studies	study	NOUN
app01-10633	24	2	show	show	VERB
app01-10633	24	3	that	that	SCONJ
app01-10633	24	4	drivers	driver	NOUN
app01-10633	24	5	on	on	ADP
app01-10633	24	6	roads	road	NOUN
app01-10633	24	7	bordered	border	VERB
app01-10633	24	8	by	by	ADP
app01-10633	24	9	wide	wide	ADJ
app01-10633	24	10	fields	field	NOUN
app01-10633	24	11	or	or	CCONJ
app01-10633	24	12	open	open	ADJ
app01-10633	24	13	landscapes	landscape	NOUN
app01-10633	24	14	tend	tend	VERB
app01-10633	24	15	to	to	PART
app01-10633	24	16	accelerate	accelerate	VERB
app01-10633	24	17	beyond	beyond	ADP
app01-10633	24	18	safe	safe	ADJ
app01-10633	24	19	limits	limit	NOUN
app01-10633	24	20	[	[	X
app01-10633	24	21	3	3	NUM
app01-10633	24	22	]	]	PUNCT
app01-10633	24	23	.	.	PUNCT
app01-10633	25	1	roadside	roadside	ADJ
app01-10633	25	2	vegetation	vegetation	NOUN
app01-10633	25	3	,	,	PUNCT
app01-10633	25	4	such	such	ADJ
app01-10633	25	5	as	as	ADP
app01-10633	25	6	shrubs	shrub	NOUN
app01-10633	25	7	and	and	CCONJ
app01-10633	25	8	bushes	bush	NOUN
app01-10633	25	9	,	,	PUNCT
app01-10633	25	10	provides	provide	VERB
app01-10633	25	11	moderate	moderate	ADJ
app01-10633	25	12	visual	visual	ADJ
app01-10633	25	13	feedback	feedback	NOUN
app01-10633	25	14	that	that	PRON
app01-10633	25	15	can	can	AUX
app01-10633	25	16	influence	influence	VERB
app01-10633	25	17	speed	speed	NOUN
app01-10633	25	18	perception	perception	NOUN
app01-10633	25	19	.	.	PUNCT
app01-10633	26	1	while	while	SCONJ
app01-10633	26	2	not	not	PART
app01-10633	26	3	as	as	ADV
app01-10633	26	4	dramatic	dramatic	ADJ
app01-10633	26	5	as	as	ADP
app01-10633	26	6	large	large	ADJ
app01-10633	26	7	trees	tree	NOUN
app01-10633	26	8	or	or	CCONJ
app01-10633	26	9	buildings	building	NOUN
app01-10633	26	10	,	,	PUNCT
app01-10633	26	11	roadside	roadside	ADJ
app01-10633	26	12	vegetation	vegetation	NOUN
app01-10633	26	13	helps	help	VERB
app01-10633	26	14	create	create	VERB
app01-10633	26	15	a	a	DET
app01-10633	26	16	continuous	continuous	ADJ
app01-10633	26	17	visual	visual	ADJ
app01-10633	26	18	flow	flow	NOUN
app01-10633	26	19	that	that	PRON
app01-10633	26	20	gently	gently	ADV
app01-10633	26	21	encourages	encourage	VERB
app01-10633	26	22	drivers	driver	NOUN
app01-10633	26	23	to	to	PART
app01-10633	26	24	maintain	maintain	VERB
app01-10633	26	25	a	a	DET
app01-10633	26	26	slower	slow	ADJ
app01-10633	26	27	speed	speed	NOUN
app01-10633	26	28	,	,	PUNCT
app01-10633	26	29	particularly	particularly	ADV
app01-10633	26	30	in	in	ADP
app01-10633	26	31	suburban	suburban	ADJ
app01-10633	26	32	or	or	CCONJ
app01-10633	26	33	residential	residential	ADJ
app01-10633	26	34	areas	area	NOUN
app01-10633	26	35	.	.	PUNCT
app01-10633	27	1	research	research	NOUN
app01-10633	27	2	has	have	AUX
app01-10633	27	3	found	find	VERB
app01-10633	27	4	that	that	SCONJ
app01-10633	27	5	roads	road	NOUN
app01-10633	27	6	lined	line	VERB
app01-10633	27	7	with	with	ADP
app01-10633	27	8	trees	tree	NOUN
app01-10633	27	9	or	or	CCONJ
app01-10633	27	10	vegetation	vegetation	NOUN
app01-10633	27	11	reduce	reduce	VERB
app01-10633	27	12	perceived	perceive	VERB
app01-10633	27	13	speed	speed	NOUN
app01-10633	27	14	and	and	CCONJ
app01-10633	27	15	promote	promote	VERB
app01-10633	27	16	safer	safe	ADJ
app01-10633	27	17	driving	driving	NOUN
app01-10633	27	18	practices	practice	NOUN
app01-10633	27	19	[	[	X
app01-10633	27	20	1	1	NUM
app01-10633	27	21	,	,	PUNCT
app01-10633	27	22	2	2	NUM
app01-10633	27	23	]	]	PUNCT
app01-10633	27	24	.	.	PUNCT
app01-10633	28	1	road	road	NOUN
app01-10633	28	2	design	design	NOUN
app01-10633	28	3	plays	play	VERB
app01-10633	28	4	a	a	DET
app01-10633	28	5	critical	critical	ADJ
app01-10633	28	6	role	role	NOUN
app01-10633	28	7	in	in	ADP
app01-10633	28	8	influencing	influence	VERB
app01-10633	28	9	speed	speed	NOUN
app01-10633	28	10	perception	perception	NOUN
app01-10633	28	11	through	through	ADP
app01-10633	28	12	elements	element	NOUN
app01-10633	28	13	like	like	ADP
app01-10633	28	14	slopes	slope	NOUN
app01-10633	28	15	and	and	CCONJ
app01-10633	28	16	guardrails	guardrail	NOUN
app01-10633	28	17	.	.	PUNCT
app01-10633	29	1	guardrails	guardrail	NOUN
app01-10633	29	2	close	close	ADJ
app01-10633	29	3	to	to	ADP
app01-10633	29	4	the	the	DET
app01-10633	29	5	road	road	NOUN
app01-10633	29	6	’s	’s	PART
app01-10633	29	7	edge	edge	PROPN
app01-10633	29	8	act	act	PROPN
app01-10633	29	9	as	as	ADP
app01-10633	29	10	a	a	DET
app01-10633	29	11	visual	visual	ADJ
app01-10633	29	12	boundary	boundary	NOUN
app01-10633	29	13	,	,	PUNCT
app01-10633	29	14	narrowing	narrow	VERB
app01-10633	29	15	the	the	DET
app01-10633	29	16	perceived	perceive	VERB
app01-10633	29	17	road	road	NOUN
app01-10633	29	18	width	width	NOUN
app01-10633	29	19	and	and	CCONJ
app01-10633	29	20	encouraging	encourage	VERB
app01-10633	29	21	slower	slow	ADJ
app01-10633	29	22	speeds	speed	NOUN
app01-10633	29	23	.	.	PUNCT
app01-10633	30	1	additionally	additionally	ADV
app01-10633	30	2	,	,	PUNCT
app01-10633	30	3	sloping	slope	VERB
app01-10633	30	4	terrain	terrain	NOUN
app01-10633	30	5	,	,	PUNCT
app01-10633	30	6	particularly	particularly	ADV
app01-10633	30	7	slopes	slope	NOUN
app01-10633	30	8	that	that	PRON
app01-10633	30	9	rise	rise	VERB
app01-10633	30	10	away	away	ADV
app01-10633	30	11	from	from	ADP
app01-10633	30	12	the	the	DET
app01-10633	30	13	road	road	NOUN
app01-10633	30	14	,	,	PUNCT
app01-10633	30	15	can	can	AUX
app01-10633	30	16	create	create	VERB
app01-10633	30	17	an	an	DET
app01-10633	30	18	open	open	ADJ
app01-10633	30	19	feel	feel	NOUN
app01-10633	30	20	that	that	PRON
app01-10633	30	21	leads	lead	VERB
app01-10633	30	22	to	to	ADP
app01-10633	30	23	speed	speed	NOUN
app01-10633	30	24	underestimation	underestimation	NOUN
app01-10633	30	25	.	.	PUNCT
app01-10633	31	1	conversely	conversely	ADV
app01-10633	31	2	,	,	PUNCT
app01-10633	31	3	steep	steep	ADJ
app01-10633	31	4	roadside	roadside	NOUN
app01-10633	31	5	slopes	slope	NOUN
app01-10633	31	6	can	can	AUX
app01-10633	31	7	enhance	enhance	VERB
app01-10633	31	8	the	the	DET
app01-10633	31	9	tunnel	tunnel	NOUN
app01-10633	31	10	effect	effect	NOUN
app01-10633	31	11	by	by	ADP
app01-10633	31	12	making	make	VERB
app01-10633	31	13	the	the	DET
app01-10633	31	14	road	road	NOUN
app01-10633	31	15	feel	feel	VERB
app01-10633	31	16	more	more	ADV
app01-10633	31	17	confined	confined	ADJ
app01-10633	31	18	[	[	X
app01-10633	31	19	1	1	NUM
app01-10633	31	20	]	]	PUNCT
app01-10633	31	21	.	.	PUNCT
app01-10633	32	1	recent	recent	ADJ
app01-10633	32	2	studies	study	NOUN
app01-10633	32	3	using	use	VERB
app01-10633	32	4	dynamic	dynamic	ADJ
app01-10633	32	5	measurement	measurement	NOUN
app01-10633	32	6	techniques	technique	NOUN
app01-10633	32	7	reveal	reveal	VERB
app01-10633	32	8	that	that	SCONJ
app01-10633	32	9	drivers	driver	NOUN
app01-10633	32	10	continuously	continuously	ADV
app01-10633	32	11	adjust	adjust	VERB
app01-10633	32	12	their	their	PRON
app01-10633	32	13	speed	speed	NOUN
app01-10633	32	14	based	base	VERB
app01-10633	32	15	on	on	ADP
app01-10633	32	16	the	the	DET
app01-10633	32	17	real	real	ADJ
app01-10633	32	18	-	-	PUNCT
app01-10633	32	19	time	time	NOUN
app01-10633	32	20	visual	visual	ADJ
app01-10633	32	21	information	information	NOUN
app01-10633	32	22	they	they	PRON
app01-10633	32	23	receive	receive	VERB
app01-10633	32	24	from	from	ADP
app01-10633	32	25	their	their	PRON
app01-10633	32	26	surroundings	surrounding	NOUN
app01-10633	32	27	.	.	PUNCT
app01-10633	33	1	misjudgments	misjudgment	NOUN
app01-10633	33	2	,	,	PUNCT
app01-10633	33	3	such	such	ADJ
app01-10633	33	4	as	as	ADP
app01-10633	33	5	underestimating	underestimate	VERB
app01-10633	33	6	speed	speed	NOUN
app01-10633	33	7	in	in	ADP
app01-10633	33	8	open	open	ADJ
app01-10633	33	9	areas	area	NOUN
app01-10633	33	10	,	,	PUNCT
app01-10633	33	11	can	can	AUX
app01-10633	33	12	lead	lead	VERB
app01-10633	33	13	to	to	ADP
app01-10633	33	14	excessive	excessive	ADJ
app01-10633	33	15	speeds	speed	NOUN
app01-10633	33	16	in	in	ADP
app01-10633	33	17	environments	environment	NOUN
app01-10633	33	18	with	with	ADP
app01-10633	33	19	fewer	few	ADJ
app01-10633	33	20	roadside	roadside	NOUN
app01-10633	33	21	cues	cue	NOUN
app01-10633	33	22	.	.	PUNCT
app01-10633	34	1	these	these	DET
app01-10633	34	2	studies	study	NOUN
app01-10633	34	3	emphasize	emphasize	VERB
app01-10633	34	4	the	the	DET
app01-10633	34	5	need	need	NOUN
app01-10633	34	6	for	for	ADP
app01-10633	34	7	road	road	NOUN
app01-10633	34	8	designs	design	NOUN
app01-10633	34	9	that	that	PRON
app01-10633	34	10	provide	provide	VERB
app01-10633	34	11	more	more	ADV
app01-10633	34	12	consistent	consistent	ADJ
app01-10633	34	13	feedback	feedback	NOUN
app01-10633	34	14	,	,	PUNCT
app01-10633	34	15	especially	especially	ADV
app01-10633	34	16	on	on	ADP
app01-10633	34	17	highways	highway	NOUN
app01-10633	34	18	and	and	CCONJ
app01-10633	34	19	rural	rural	ADJ
app01-10633	34	20	roads	road	NOUN
app01-10633	34	21	[	[	X
app01-10633	34	22	2	2	NUM
app01-10633	34	23	]	]	PUNCT
app01-10633	34	24	.	.	PUNCT
app01-10633	35	1	the	the	DET
app01-10633	35	2	effect	effect	NOUN
app01-10633	35	3	of	of	ADP
app01-10633	35	4	the	the	DET
app01-10633	35	5	roadside	roadside	NOUN
app01-10633	35	6	environment	environment	NOUN
app01-10633	35	7	on	on	ADP
app01-10633	35	8	speed	speed	NOUN
app01-10633	35	9	perception	perception	NOUN
app01-10633	35	10	is	be	AUX
app01-10633	35	11	not	not	PART
app01-10633	35	12	purely	purely	ADV
app01-10633	35	13	visual	visual	ADJ
app01-10633	35	14	;	;	PUNCT
app01-10633	35	15	psychological	psychological	ADJ
app01-10633	35	16	mechanisms	mechanism	NOUN
app01-10633	35	17	play	play	VERB
app01-10633	35	18	a	a	DET
app01-10633	35	19	significant	significant	ADJ
app01-10633	35	20	role	role	NOUN
app01-10633	35	21	.	.	PUNCT
app01-10633	36	1	for	for	ADP
app01-10633	36	2	example	example	NOUN
app01-10633	36	3	,	,	PUNCT
app01-10633	36	4	when	when	SCONJ
app01-10633	36	5	drivers	driver	NOUN
app01-10633	36	6	feel	feel	VERB
app01-10633	36	7	that	that	SCONJ
app01-10633	36	8	a	a	DET
app01-10633	36	9	road	road	NOUN
app01-10633	36	10	is	be	AUX
app01-10633	36	11	narrow	narrow	ADJ
app01-10633	36	12	or	or	CCONJ
app01-10633	36	13	enclosed	enclose	VERB
app01-10633	36	14	due	due	ADJ
app01-10633	36	15	to	to	ADP
app01-10633	36	16	roadside	roadside	ADJ
app01-10633	36	17	elements	element	NOUN
app01-10633	36	18	,	,	PUNCT
app01-10633	36	19	they	they	PRON
app01-10633	36	20	perceive	perceive	VERB
app01-10633	36	21	a	a	DET
app01-10633	36	22	higher	high	ADJ
app01-10633	36	23	level	level	NOUN
app01-10633	36	24	of	of	ADP
app01-10633	36	25	risk	risk	NOUN
app01-10633	36	26	,	,	PUNCT
app01-10633	36	27	leading	lead	VERB
app01-10633	36	28	to	to	ADP
app01-10633	36	29	reduced	reduced	ADJ
app01-10633	36	30	speed	speed	NOUN
app01-10633	36	31	.	.	PUNCT
app01-10633	37	1	on	on	ADP
app01-10633	37	2	the	the	DET
app01-10633	37	3	other	other	ADJ
app01-10633	37	4	hand	hand	NOUN
app01-10633	37	5	,	,	PUNCT
app01-10633	37	6	open	open	ADJ
app01-10633	37	7	roads	road	NOUN
app01-10633	37	8	with	with	ADP
app01-10633	37	9	fewer	few	ADJ
app01-10633	37	10	obstacles	obstacle	NOUN
app01-10633	37	11	are	be	AUX
app01-10633	37	12	perceived	perceive	VERB
app01-10633	37	13	as	as	ADP
app01-10633	37	14	less	less	ADV
app01-10633	37	15	risky	risky	ADJ
app01-10633	37	16	,	,	PUNCT
app01-10633	37	17	leading	lead	VERB
app01-10633	37	18	to	to	ADP
app01-10633	37	19	faster	fast	ADJ
app01-10633	37	20	driving	driving	NOUN
app01-10633	37	21	speeds	speed	NOUN
app01-10633	37	22	,	,	PUNCT
app01-10633	37	23	often	often	ADV
app01-10633	37	24	beyond	beyond	ADP
app01-10633	37	25	the	the	DET
app01-10633	37	26	posted	post	VERB
app01-10633	37	27	limits	limit	NOUN
app01-10633	37	28	[	[	X
app01-10633	37	29	3	3	NUM
app01-10633	37	30	]	]	PUNCT
app01-10633	37	31	.	.	PUNCT
app01-10633	38	1	understanding	understand	VERB
app01-10633	38	2	these	these	DET
app01-10633	38	3	psychological	psychological	ADJ
app01-10633	38	4	responses	response	NOUN
app01-10633	38	5	is	be	AUX
app01-10633	38	6	essential	essential	ADJ
app01-10633	38	7	for	for	ADP
app01-10633	38	8	designing	design	VERB
app01-10633	38	9	roadways	roadway	NOUN
app01-10633	38	10	that	that	PRON
app01-10633	38	11	naturally	naturally	ADV
app01-10633	38	12	encourage	encourage	VERB
app01-10633	38	13	safe	safe	ADJ
app01-10633	38	14	driving	driving	NOUN
app01-10633	38	15	behavior	behavior	NOUN
app01-10633	38	16	.	.	PUNCT
app01-10633	39	1	116	116	NUM
app01-10633	39	2	https://doi.org/10.14311/app.2025.52.0116	https://doi.org/10.14311/app.2025.52.0116	PROPN
app01-10633	39	3	https://creativecommons.org/licenses/by/4.0/	https://creativecommons.org/licenses/by/4.0/	PROPN
app01-10633	39	4	https://www.cvut.cz/en	https://www.cvut.cz/en	PROPN
app01-10633	39	5	vol	vol	NOUN
app01-10633	39	6	.	.	PUNCT
app01-10633	40	1	52/2025	52/2025	NUM
app01-10633	40	2	the	the	DET
app01-10633	40	3	effect	effect	NOUN
app01-10633	40	4	of	of	ADP
app01-10633	40	5	roadside	roadside	NOUN
app01-10633	40	6	on	on	ADP
app01-10633	40	7	speed	speed	NOUN
app01-10633	40	8	perception	perception	NOUN
app01-10633	40	9	roads	road	NOUN
app01-10633	40	10	that	that	PRON
app01-10633	40	11	transition	transition	NOUN
app01-10633	40	12	from	from	ADP
app01-10633	40	13	dense	dense	ADJ
app01-10633	40	14	,	,	PUNCT
app01-10633	40	15	visually	visually	ADV
app01-10633	40	16	stimulating	stimulate	VERB
app01-10633	40	17	environments	environment	NOUN
app01-10633	40	18	(	(	PUNCT
app01-10633	40	19	such	such	ADJ
app01-10633	40	20	as	as	ADP
app01-10633	40	21	urban	urban	ADJ
app01-10633	40	22	streets	street	NOUN
app01-10633	40	23	)	)	PUNCT
app01-10633	40	24	to	to	PART
app01-10633	40	25	open	open	VERB
app01-10633	40	26	,	,	PUNCT
app01-10633	40	27	less	less	ADV
app01-10633	40	28	stimulating	stimulating	ADJ
app01-10633	40	29	environments	environment	NOUN
app01-10633	40	30	(	(	PUNCT
app01-10633	40	31	such	such	ADJ
app01-10633	40	32	as	as	ADP
app01-10633	40	33	rural	rural	ADJ
app01-10633	40	34	highways	highway	NOUN
app01-10633	40	35	)	)	PUNCT
app01-10633	40	36	can	can	AUX
app01-10633	40	37	cause	cause	VERB
app01-10633	40	38	fluctuations	fluctuation	NOUN
app01-10633	40	39	in	in	ADP
app01-10633	40	40	speed	speed	NOUN
app01-10633	40	41	perception	perception	NOUN
app01-10633	40	42	.	.	PUNCT
app01-10633	41	1	drivers	driver	NOUN
app01-10633	41	2	moving	move	VERB
app01-10633	41	3	from	from	ADP
app01-10633	41	4	a	a	DET
app01-10633	41	5	visually	visually	ADV
app01-10633	41	6	confined	confine	VERB
app01-10633	41	7	area	area	NOUN
app01-10633	41	8	to	to	ADP
app01-10633	41	9	an	an	DET
app01-10633	41	10	open	open	ADJ
app01-10633	41	11	space	space	NOUN
app01-10633	41	12	may	may	AUX
app01-10633	41	13	suddenly	suddenly	ADV
app01-10633	41	14	feel	feel	VERB
app01-10633	41	15	that	that	SCONJ
app01-10633	41	16	they	they	PRON
app01-10633	41	17	are	be	AUX
app01-10633	41	18	moving	move	VERB
app01-10633	41	19	too	too	ADV
app01-10633	41	20	slowly	slowly	ADV
app01-10633	41	21	and	and	CCONJ
app01-10633	41	22	accelerate	accelerate	VERB
app01-10633	41	23	,	,	PUNCT
app01-10633	41	24	sometimes	sometimes	ADV
app01-10633	41	25	dangerously	dangerously	ADV
app01-10633	41	26	.	.	PUNCT
app01-10633	42	1	this	this	DET
app01-10633	42	2	variability	variability	NOUN
app01-10633	42	3	in	in	ADP
app01-10633	42	4	speed	speed	NOUN
app01-10633	42	5	perception	perception	NOUN
app01-10633	42	6	highlights	highlight	NOUN
app01-10633	42	7	the	the	DET
app01-10633	42	8	need	need	NOUN
app01-10633	42	9	for	for	ADP
app01-10633	42	10	carefully	carefully	ADV
app01-10633	42	11	managed	manage	VERB
app01-10633	42	12	transition	transition	NOUN
app01-10633	42	13	zones	zone	NOUN
app01-10633	42	14	to	to	PART
app01-10633	42	15	maintain	maintain	VERB
app01-10633	42	16	consistent	consistent	ADJ
app01-10633	42	17	speeds	speed	NOUN
app01-10633	42	18	across	across	ADP
app01-10633	42	19	different	different	ADJ
app01-10633	42	20	driving	drive	VERB
app01-10633	42	21	environments	environment	NOUN
app01-10633	42	22	[	[	X
app01-10633	42	23	1	1	NUM
app01-10633	42	24	]	]	PUNCT
app01-10633	42	25	.	.	PUNCT
app01-10633	43	1	according	accord	VERB
app01-10633	43	2	to	to	ADP
app01-10633	43	3	hurwitz	hurwitz	PROPN
app01-10633	43	4	et	et	PROPN
app01-10633	43	5	al	al	PROPN
app01-10633	43	6	.	.	PUNCT
app01-10633	44	1	[	[	X
app01-10633	44	2	4	4	NUM
app01-10633	44	3	]	]	PUNCT
app01-10633	44	4	,	,	PUNCT
app01-10633	44	5	drivers	driver	NOUN
app01-10633	44	6	tend	tend	VERB
app01-10633	44	7	to	to	PART
app01-10633	44	8	underestimate	underestimate	VERB
app01-10633	44	9	their	their	PRON
app01-10633	44	10	speed	speed	NOUN
app01-10633	44	11	,	,	PUNCT
app01-10633	44	12	particularly	particularly	ADV
app01-10633	44	13	in	in	ADP
app01-10633	44	14	environments	environment	NOUN
app01-10633	44	15	where	where	SCONJ
app01-10633	44	16	visual	visual	ADJ
app01-10633	44	17	cues	cue	NOUN
app01-10633	44	18	,	,	PUNCT
app01-10633	44	19	such	such	ADJ
app01-10633	44	20	as	as	ADP
app01-10633	44	21	horizontal	horizontal	ADJ
app01-10633	44	22	curves	curve	NOUN
app01-10633	44	23	and	and	CCONJ
app01-10633	44	24	surrounding	surround	VERB
app01-10633	44	25	landscape	landscape	NOUN
app01-10633	44	26	,	,	PUNCT
app01-10633	44	27	play	play	VERB
app01-10633	44	28	a	a	DET
app01-10633	44	29	role	role	NOUN
app01-10633	44	30	.	.	PUNCT
app01-10633	45	1	these	these	DET
app01-10633	45	2	findings	finding	NOUN
app01-10633	45	3	suggest	suggest	VERB
app01-10633	45	4	that	that	SCONJ
app01-10633	45	5	elements	element	NOUN
app01-10633	45	6	like	like	ADP
app01-10633	45	7	road	road	NOUN
app01-10633	45	8	curvature	curvature	NOUN
app01-10633	45	9	,	,	PUNCT
app01-10633	45	10	visual	visual	ADJ
app01-10633	45	11	landmarks	landmark	NOUN
app01-10633	45	12	,	,	PUNCT
app01-10633	45	13	and	and	CCONJ
app01-10633	45	14	the	the	DET
app01-10633	45	15	type	type	NOUN
app01-10633	45	16	of	of	ADP
app01-10633	45	17	environment	environment	NOUN
app01-10633	45	18	(	(	PUNCT
app01-10633	45	19	e.g.	e.g.	ADV
app01-10633	45	20	,	,	PUNCT
app01-10633	45	21	urban	urban	ADJ
app01-10633	45	22	vs.	vs.	X
app01-10633	45	23	rural	rural	NOUN
app01-10633	45	24	)	)	PUNCT
app01-10633	45	25	can	can	AUX
app01-10633	45	26	significantly	significantly	ADV
app01-10633	45	27	alter	alter	VERB
app01-10633	45	28	drivers	driver	NOUN
app01-10633	45	29	’	’	PART
app01-10633	45	30	perception	perception	NOUN
app01-10633	45	31	of	of	ADP
app01-10633	45	32	speed	speed	NOUN
app01-10633	45	33	.	.	PUNCT
app01-10633	46	1	the	the	DET
app01-10633	46	2	study	study	NOUN
app01-10633	46	3	highlights	highlight	NOUN
app01-10633	46	4	that	that	SCONJ
app01-10633	46	5	drivers	driver	NOUN
app01-10633	46	6	’	’	PART
app01-10633	46	7	accuracy	accuracy	NOUN
app01-10633	46	8	in	in	ADP
app01-10633	46	9	estimating	estimate	VERB
app01-10633	46	10	their	their	PRON
app01-10633	46	11	speed	speed	NOUN
app01-10633	46	12	decreases	decrease	NOUN
app01-10633	46	13	in	in	ADP
app01-10633	46	14	more	more	ADJ
app01-10633	46	15	complex	complex	ADJ
app01-10633	46	16	visual	visual	ADJ
app01-10633	46	17	environments	environment	NOUN
app01-10633	46	18	.	.	PUNCT
app01-10633	47	1	this	this	PRON
app01-10633	47	2	supports	support	VERB
app01-10633	47	3	the	the	DET
app01-10633	47	4	idea	idea	NOUN
app01-10633	47	5	that	that	SCONJ
app01-10633	47	6	roadside	roadside	NOUN
app01-10633	47	7	features	feature	VERB
app01-10633	47	8	and	and	CCONJ
app01-10633	47	9	the	the	DET
app01-10633	47	10	immediate	immediate	ADJ
app01-10633	47	11	surroundings	surrounding	NOUN
app01-10633	47	12	impact	impact	NOUN
app01-10633	47	13	speed	speed	NOUN
app01-10633	47	14	perception	perception	NOUN
app01-10633	47	15	.	.	PUNCT
app01-10633	48	1	this	this	DET
app01-10633	48	2	observation	observation	NOUN
app01-10633	48	3	aligns	align	VERB
app01-10633	48	4	well	well	ADV
app01-10633	48	5	with	with	ADP
app01-10633	48	6	your	your	PRON
app01-10633	48	7	focus	focus	NOUN
app01-10633	48	8	on	on	ADP
app01-10633	48	9	evaluating	evaluate	VERB
app01-10633	48	10	the	the	DET
app01-10633	48	11	influence	influence	NOUN
app01-10633	48	12	of	of	ADP
app01-10633	48	13	proximity	proximity	NOUN
app01-10633	48	14	to	to	ADP
app01-10633	48	15	roadside	roadside	NOUN
app01-10633	48	16	elements	element	NOUN
app01-10633	48	17	and	and	CCONJ
app01-10633	48	18	the	the	DET
app01-10633	48	19	broader	broad	ADJ
app01-10633	48	20	environmental	environmental	ADJ
app01-10633	48	21	context	context	NOUN
app01-10633	48	22	on	on	ADP
app01-10633	48	23	speed	speed	NOUN
app01-10633	48	24	perception	perception	NOUN
app01-10633	48	25	.	.	PUNCT
app01-10633	49	1	additionally	additionally	ADV
app01-10633	49	2	,	,	PUNCT
app01-10633	49	3	research	research	NOUN
app01-10633	49	4	on	on	ADP
app01-10633	49	5	speed	speed	NOUN
app01-10633	49	6	perception	perception	NOUN
app01-10633	49	7	has	have	AUX
app01-10633	49	8	consistently	consistently	ADV
app01-10633	49	9	shown	show	VERB
app01-10633	49	10	that	that	SCONJ
app01-10633	49	11	environmental	environmental	ADJ
app01-10633	49	12	factors	factor	NOUN
app01-10633	49	13	,	,	PUNCT
app01-10633	49	14	such	such	ADJ
app01-10633	49	15	as	as	ADP
app01-10633	49	16	road	road	NOUN
app01-10633	49	17	geometry	geometry	NOUN
app01-10633	49	18	and	and	CCONJ
app01-10633	49	19	surrounding	surround	VERB
app01-10633	49	20	visual	visual	ADJ
app01-10633	49	21	cues	cue	NOUN
app01-10633	49	22	,	,	PUNCT
app01-10633	49	23	play	play	VERB
app01-10633	49	24	a	a	DET
app01-10633	49	25	crucial	crucial	ADJ
app01-10633	49	26	role	role	NOUN
app01-10633	49	27	in	in	ADP
app01-10633	49	28	influencing	influence	VERB
app01-10633	49	29	how	how	SCONJ
app01-10633	49	30	drivers	driver	NOUN
app01-10633	49	31	perceive	perceive	VERB
app01-10633	49	32	their	their	PRON
app01-10633	49	33	speed	speed	NOUN
app01-10633	49	34	[	[	X
app01-10633	49	35	5	5	NUM
app01-10633	49	36	]	]	PUNCT
app01-10633	49	37	.	.	PUNCT
app01-10633	50	1	studies	study	NOUN
app01-10633	50	2	,	,	PUNCT
app01-10633	50	3	including	include	VERB
app01-10633	50	4	those	those	PRON
app01-10633	50	5	focusing	focus	VERB
app01-10633	50	6	on	on	ADP
app01-10633	50	7	freeway	freeway	NOUN
app01-10633	50	8	curves	curve	NOUN
app01-10633	50	9	,	,	PUNCT
app01-10633	50	10	demonstrate	demonstrate	VERB
app01-10633	50	11	that	that	SCONJ
app01-10633	50	12	drivers	driver	NOUN
app01-10633	50	13	often	often	ADV
app01-10633	50	14	underestimate	underestimate	VERB
app01-10633	50	15	their	their	PRON
app01-10633	50	16	speed	speed	NOUN
app01-10633	50	17	when	when	SCONJ
app01-10633	50	18	navigating	navigate	VERB
app01-10633	50	19	certain	certain	ADJ
app01-10633	50	20	road	road	NOUN
app01-10633	50	21	configurations	configuration	NOUN
app01-10633	50	22	,	,	PUNCT
app01-10633	50	23	particularly	particularly	ADV
app01-10633	50	24	curves	curve	NOUN
app01-10633	50	25	with	with	ADP
app01-10633	50	26	smaller	small	ADJ
app01-10633	50	27	radii	radius	NOUN
app01-10633	50	28	or	or	CCONJ
app01-10633	50	29	complex	complex	ADJ
app01-10633	50	30	curve	curve	NOUN
app01-10633	50	31	combinations	combination	NOUN
app01-10633	50	32	.	.	PUNCT
app01-10633	51	1	for	for	ADP
app01-10633	51	2	example	example	NOUN
app01-10633	51	3	,	,	PUNCT
app01-10633	51	4	research	research	NOUN
app01-10633	51	5	on	on	ADP
app01-10633	51	6	freeway	freeway	NOUN
app01-10633	51	7	curves	curve	NOUN
app01-10633	51	8	shows	show	VERB
app01-10633	51	9	that	that	SCONJ
app01-10633	51	10	drivers	driver	NOUN
app01-10633	51	11	are	be	AUX
app01-10633	51	12	most	most	ADV
app01-10633	51	13	prone	prone	ADJ
app01-10633	51	14	to	to	ADP
app01-10633	51	15	underestimating	underestimate	VERB
app01-10633	51	16	their	their	PRON
app01-10633	51	17	speed	speed	NOUN
app01-10633	51	18	at	at	ADP
app01-10633	51	19	a	a	DET
app01-10633	51	20	curve	curve	NOUN
app01-10633	51	21	’s	’s	PART
app01-10633	51	22	tangent	tangent	NOUN
app01-10633	51	23	-	-	PUNCT
app01-10633	51	24	to	to	ADP
app01-10633	51	25	-	-	PUNCT
app01-10633	51	26	spiral	spiral	ADJ
app01-10633	51	27	(	(	PUNCT
app01-10633	51	28	ts	ts	NOUN
app01-10633	51	29	)	)	PUNCT
app01-10633	51	30	point	point	NOUN
app01-10633	51	31	,	,	PUNCT
app01-10633	51	32	especially	especially	ADV
app01-10633	51	33	when	when	SCONJ
app01-10633	51	34	the	the	DET
app01-10633	51	35	curve	curve	NOUN
app01-10633	51	36	radius	radius	NOUN
app01-10633	51	37	is	be	AUX
app01-10633	51	38	tight	tight	ADJ
app01-10633	51	39	.	.	PUNCT
app01-10633	52	1	this	this	PRON
app01-10633	52	2	highlights	highlight	VERB
app01-10633	52	3	the	the	DET
app01-10633	52	4	importance	importance	NOUN
app01-10633	52	5	of	of	ADP
app01-10633	52	6	understanding	understand	VERB
app01-10633	52	7	how	how	SCONJ
app01-10633	52	8	road	road	NOUN
app01-10633	52	9	characteristics	characteristic	NOUN
app01-10633	52	10	and	and	CCONJ
app01-10633	52	11	environmental	environmental	ADJ
app01-10633	52	12	visual	visual	ADJ
app01-10633	52	13	feedback	feedback	NOUN
app01-10633	52	14	affect	affect	VERB
app01-10633	52	15	speed	speed	NOUN
app01-10633	52	16	perception	perception	NOUN
app01-10633	52	17	.	.	PUNCT
app01-10633	53	1	such	such	ADJ
app01-10633	53	2	findings	finding	NOUN
app01-10633	53	3	are	be	AUX
app01-10633	53	4	directly	directly	ADV
app01-10633	53	5	relevant	relevant	ADJ
app01-10633	53	6	to	to	ADP
app01-10633	53	7	this	this	DET
app01-10633	53	8	study	study	NOUN
app01-10633	53	9	’s	’s	PART
app01-10633	53	10	focus	focus	NOUN
app01-10633	53	11	on	on	ADP
app01-10633	53	12	how	how	SCONJ
app01-10633	53	13	roadside	roadside	ADJ
app01-10633	53	14	environments	environment	NOUN
app01-10633	53	15	–	–	PUNCT
app01-10633	53	16	including	include	VERB
app01-10633	53	17	proximity	proximity	NOUN
app01-10633	53	18	to	to	ADP
app01-10633	53	19	the	the	DET
app01-10633	53	20	road	road	NOUN
app01-10633	53	21	and	and	CCONJ
app01-10633	53	22	broader	broad	ADJ
app01-10633	53	23	landscape	landscape	NOUN
app01-10633	53	24	features	feature	VERB
app01-10633	53	25	–	–	PUNCT
app01-10633	53	26	affect	affect	VERB
app01-10633	53	27	drivers	driver	NOUN
app01-10633	53	28	’	’	PART
app01-10633	53	29	speed	speed	NOUN
app01-10633	53	30	estimation	estimation	NOUN
app01-10633	53	31	.	.	PUNCT
app01-10633	54	1	by	by	ADP
app01-10633	54	2	exploring	explore	VERB
app01-10633	54	3	the	the	DET
app01-10633	54	4	influence	influence	NOUN
app01-10633	54	5	of	of	ADP
app01-10633	54	6	roadside	roadside	ADJ
app01-10633	54	7	elements	element	NOUN
app01-10633	54	8	like	like	ADP
app01-10633	54	9	trees	tree	NOUN
app01-10633	54	10	,	,	PUNCT
app01-10633	54	11	barriers	barrier	NOUN
app01-10633	54	12	,	,	PUNCT
app01-10633	54	13	or	or	CCONJ
app01-10633	54	14	open	open	ADJ
app01-10633	54	15	fields	field	NOUN
app01-10633	54	16	,	,	PUNCT
app01-10633	54	17	this	this	DET
app01-10633	54	18	research	research	NOUN
app01-10633	54	19	aims	aim	VERB
app01-10633	54	20	to	to	PART
app01-10633	54	21	extend	extend	VERB
app01-10633	54	22	the	the	DET
app01-10633	54	23	understanding	understanding	NOUN
app01-10633	54	24	of	of	ADP
app01-10633	54	25	how	how	SCONJ
app01-10633	54	26	visual	visual	ADJ
app01-10633	54	27	factors	factor	NOUN
app01-10633	54	28	surrounding	surround	VERB
app01-10633	54	29	the	the	DET
app01-10633	54	30	road	road	NOUN
app01-10633	54	31	contribute	contribute	NOUN
app01-10633	54	32	to	to	ADP
app01-10633	54	33	misestimations	misestimation	NOUN
app01-10633	54	34	of	of	ADP
app01-10633	54	35	speed	speed	NOUN
app01-10633	54	36	,	,	PUNCT
app01-10633	54	37	much	much	ADV
app01-10633	54	38	like	like	ADP
app01-10633	54	39	how	how	SCONJ
app01-10633	54	40	curve	curve	NOUN
app01-10633	54	41	geometry	geometry	NOUN
app01-10633	54	42	has	have	AUX
app01-10633	54	43	been	be	AUX
app01-10633	54	44	shown	show	VERB
app01-10633	54	45	to	to	PART
app01-10633	54	46	influence	influence	VERB
app01-10633	54	47	drivers	driver	NOUN
app01-10633	54	48	’	’	PART
app01-10633	54	49	perception	perception	NOUN
app01-10633	54	50	in	in	ADP
app01-10633	54	51	freeway	freeway	NOUN
app01-10633	54	52	settings	setting	NOUN
app01-10633	54	53	.	.	PUNCT
app01-10633	55	1	previous	previous	ADJ
app01-10633	55	2	theses	thesis	NOUN
app01-10633	55	3	on	on	ADP
app01-10633	55	4	speed	speed	NOUN
app01-10633	55	5	perception	perception	NOUN
app01-10633	55	6	have	have	AUX
app01-10633	55	7	primarily	primarily	ADV
app01-10633	55	8	focused	focus	VERB
app01-10633	55	9	on	on	ADP
app01-10633	55	10	demographic	demographic	ADJ
app01-10633	55	11	factors	factor	NOUN
app01-10633	55	12	,	,	PUNCT
app01-10633	55	13	such	such	ADJ
app01-10633	55	14	as	as	ADP
app01-10633	55	15	the	the	DET
app01-10633	55	16	age	age	NOUN
app01-10633	55	17	,	,	PUNCT
app01-10633	55	18	gender	gender	NOUN
app01-10633	55	19	,	,	PUNCT
app01-10633	55	20	and	and	CCONJ
app01-10633	55	21	driving	drive	VERB
app01-10633	55	22	experience	experience	NOUN
app01-10633	55	23	of	of	ADP
app01-10633	55	24	respondents	respondent	NOUN
app01-10633	55	25	,	,	PUNCT
app01-10633	55	26	or	or	CCONJ
app01-10633	55	27	on	on	ADP
app01-10633	55	28	the	the	DET
app01-10633	55	29	estimated	estimate	VERB
app01-10633	55	30	vehicles	vehicle	NOUN
app01-10633	55	31	’	'	PUNCT
app01-10633	55	32	characteristics	characteristic	NOUN
app01-10633	55	33	.	.	PUNCT
app01-10633	56	1	these	these	DET
app01-10633	56	2	studies	study	NOUN
app01-10633	56	3	aimed	aim	VERB
app01-10633	56	4	to	to	PART
app01-10633	56	5	understand	understand	VERB
app01-10633	56	6	how	how	SCONJ
app01-10633	56	7	personal	personal	ADJ
app01-10633	56	8	attributes	attribute	NOUN
app01-10633	56	9	or	or	CCONJ
app01-10633	56	10	vehicle	vehicle	NOUN
app01-10633	56	11	types	type	NOUN
app01-10633	56	12	influenced	influence	VERB
app01-10633	56	13	speed	speed	NOUN
app01-10633	56	14	estimation	estimation	NOUN
app01-10633	56	15	[	[	X
app01-10633	56	16	6–11	6–11	NOUN
app01-10633	56	17	]	]	PUNCT
app01-10633	56	18	.	.	PUNCT
app01-10633	57	1	however	however	ADV
app01-10633	57	2	,	,	PUNCT
app01-10633	57	3	this	this	DET
app01-10633	57	4	study	study	NOUN
app01-10633	57	5	diverges	diverge	VERB
app01-10633	57	6	by	by	ADP
app01-10633	57	7	focusing	focus	VERB
app01-10633	57	8	solely	solely	ADV
app01-10633	57	9	on	on	ADP
app01-10633	57	10	the	the	DET
app01-10633	57	11	impact	impact	NOUN
app01-10633	57	12	of	of	ADP
app01-10633	57	13	roadside	roadside	ADJ
app01-10633	57	14	elements	element	NOUN
app01-10633	57	15	on	on	ADP
app01-10633	57	16	speed	speed	NOUN
app01-10633	57	17	perception	perception	NOUN
app01-10633	57	18	,	,	PUNCT
app01-10633	57	19	without	without	ADP
app01-10633	57	20	considering	consider	VERB
app01-10633	57	21	other	other	ADJ
app01-10633	57	22	factors	factor	NOUN
app01-10633	57	23	like	like	ADP
app01-10633	57	24	respondent	respondent	NOUN
app01-10633	57	25	demographics	demographic	NOUN
app01-10633	57	26	or	or	CCONJ
app01-10633	57	27	vehicle	vehicle	NOUN
app01-10633	57	28	characteristics	characteristic	NOUN
app01-10633	57	29	.	.	PUNCT
app01-10633	58	1	data	datum	NOUN
app01-10633	58	2	from	from	ADP
app01-10633	58	3	earlier	early	ADJ
app01-10633	58	4	theses	thesis	NOUN
app01-10633	58	5	,	,	PUNCT
app01-10633	58	6	where	where	SCONJ
app01-10633	58	7	still	still	ADV
app01-10633	58	8	available	available	ADJ
app01-10633	58	9	,	,	PUNCT
app01-10633	58	10	were	be	AUX
app01-10633	58	11	repurposed	repurpose	VERB
app01-10633	58	12	to	to	PART
app01-10633	58	13	create	create	VERB
app01-10633	58	14	a	a	DET
app01-10633	58	15	new	new	ADJ
app01-10633	58	16	dataset	dataset	NOUN
app01-10633	58	17	for	for	ADP
app01-10633	58	18	this	this	DET
app01-10633	58	19	research	research	NOUN
app01-10633	58	20	.	.	PUNCT
app01-10633	59	1	this	this	DET
app01-10633	59	2	dataset	dataset	NOUN
app01-10633	59	3	has	have	AUX
app01-10633	59	4	been	be	AUX
app01-10633	59	5	reanalyzed	reanalyze	VERB
app01-10633	59	6	with	with	ADP
app01-10633	59	7	a	a	DET
app01-10633	59	8	specific	specific	ADJ
app01-10633	59	9	focus	focus	NOUN
app01-10633	59	10	on	on	ADP
app01-10633	59	11	roadside	roadside	ADJ
app01-10633	59	12	environments	environment	NOUN
app01-10633	59	13	,	,	PUNCT
app01-10633	59	14	such	such	ADJ
app01-10633	59	15	as	as	ADP
app01-10633	59	16	the	the	DET
app01-10633	59	17	proximity	proximity	NOUN
app01-10633	59	18	of	of	ADP
app01-10633	59	19	trees	tree	NOUN
app01-10633	59	20	,	,	PUNCT
app01-10633	59	21	barriers	barrier	NOUN
app01-10633	59	22	,	,	PUNCT
app01-10633	59	23	and	and	CCONJ
app01-10633	59	24	open	open	ADJ
app01-10633	59	25	spaces	space	NOUN
app01-10633	59	26	,	,	PUNCT
app01-10633	59	27	to	to	PART
app01-10633	59	28	understand	understand	VERB
app01-10633	59	29	better	well	ADV
app01-10633	59	30	how	how	SCONJ
app01-10633	59	31	these	these	DET
app01-10633	59	32	elements	element	NOUN
app01-10633	59	33	influence	influence	VERB
app01-10633	59	34	drivers	driver	NOUN
app01-10633	59	35	’	’	PART
app01-10633	59	36	ability	ability	NOUN
app01-10633	59	37	to	to	PART
app01-10633	59	38	perceive	perceive	VERB
app01-10633	59	39	speed	speed	NOUN
app01-10633	59	40	accurately	accurately	ADV
app01-10633	59	41	.	.	PUNCT
app01-10633	60	1	by	by	ADP
app01-10633	60	2	eliminating	eliminate	VERB
app01-10633	60	3	the	the	DET
app01-10633	60	4	influence	influence	NOUN
app01-10633	60	5	of	of	ADP
app01-10633	60	6	demographic	demographic	ADJ
app01-10633	60	7	or	or	CCONJ
app01-10633	60	8	vehicle	vehicle	NOUN
app01-10633	60	9	-	-	PUNCT
app01-10633	60	10	specific	specific	ADJ
app01-10633	60	11	variables	variable	NOUN
app01-10633	60	12	,	,	PUNCT
app01-10633	60	13	this	this	DET
app01-10633	60	14	study	study	NOUN
app01-10633	60	15	aims	aim	VERB
app01-10633	60	16	to	to	PART
app01-10633	60	17	isolate	isolate	VERB
app01-10633	60	18	the	the	DET
app01-10633	60	19	effects	effect	NOUN
app01-10633	60	20	of	of	ADP
app01-10633	60	21	roadside	roadside	NOUN
app01-10633	60	22	features	feature	NOUN
app01-10633	60	23	on	on	ADP
app01-10633	60	24	speed	speed	NOUN
app01-10633	60	25	perception	perception	NOUN
app01-10633	60	26	.	.	PUNCT
app01-10633	61	1	2	2	X
app01-10633	61	2	.	.	X
app01-10633	61	3	dataset	dataset	NOUN
app01-10633	61	4	and	and	CCONJ
app01-10633	61	5	method	method	VERB
app01-10633	61	6	this	this	DET
app01-10633	61	7	study	study	NOUN
app01-10633	61	8	builds	build	VERB
app01-10633	61	9	upon	upon	SCONJ
app01-10633	61	10	data	datum	NOUN
app01-10633	61	11	previously	previously	ADV
app01-10633	61	12	collected	collect	VERB
app01-10633	61	13	from	from	ADP
app01-10633	61	14	several	several	ADJ
app01-10633	61	15	completed	complete	VERB
app01-10633	61	16	master	master	NOUN
app01-10633	61	17	’s	’s	PART
app01-10633	61	18	theses	theses	X
app01-10633	61	19	and	and	CCONJ
app01-10633	61	20	one	one	NUM
app01-10633	61	21	related	relate	VERB
app01-10633	61	22	study	study	NOUN
app01-10633	61	23	,	,	PUNCT
app01-10633	61	24	repurposing	repurpose	VERB
app01-10633	61	25	the	the	DET
app01-10633	61	26	existing	exist	VERB
app01-10633	61	27	datasets	dataset	NOUN
app01-10633	61	28	to	to	PART
app01-10633	61	29	create	create	VERB
app01-10633	61	30	a	a	DET
app01-10633	61	31	new	new	ADJ
app01-10633	61	32	,	,	PUNCT
app01-10633	61	33	comprehensive	comprehensive	ADJ
app01-10633	61	34	dataset	dataset	NOUN
app01-10633	61	35	.	.	PUNCT
app01-10633	62	1	while	while	SCONJ
app01-10633	62	2	the	the	DET
app01-10633	62	3	original	original	ADJ
app01-10633	62	4	focus	focus	NOUN
app01-10633	62	5	of	of	ADP
app01-10633	62	6	these	these	DET
app01-10633	62	7	works	work	NOUN
app01-10633	62	8	was	be	AUX
app01-10633	62	9	not	not	PART
app01-10633	62	10	specifically	specifically	ADV
app01-10633	62	11	on	on	ADP
app01-10633	62	12	the	the	DET
app01-10633	62	13	impact	impact	NOUN
app01-10633	62	14	of	of	ADP
app01-10633	62	15	roadside	roadside	ADJ
app01-10633	62	16	environments	environment	NOUN
app01-10633	62	17	on	on	ADP
app01-10633	62	18	speed	speed	NOUN
app01-10633	62	19	perception	perception	NOUN
app01-10633	62	20	,	,	PUNCT
app01-10633	62	21	this	this	DET
app01-10633	62	22	new	new	ADJ
app01-10633	62	23	analysis	analysis	NOUN
app01-10633	62	24	shifts	shift	NOUN
app01-10633	62	25	the	the	DET
app01-10633	62	26	attention	attention	NOUN
app01-10633	62	27	to	to	ADP
app01-10633	62	28	how	how	SCONJ
app01-10633	62	29	different	different	ADJ
app01-10633	62	30	surroundings	surrounding	NOUN
app01-10633	62	31	might	might	AUX
app01-10633	62	32	influence	influence	VERB
app01-10633	62	33	drivers	driver	NOUN
app01-10633	62	34	’	'	PUNCT
app01-10633	62	35	and	and	CCONJ
app01-10633	62	36	witnesses	witness	NOUN
app01-10633	62	37	’	'	PUNCT
app01-10633	62	38	ability	ability	NOUN
app01-10633	62	39	to	to	PART
app01-10633	62	40	estimate	estimate	VERB
app01-10633	62	41	vehicle	vehicle	NOUN
app01-10633	62	42	speed	speed	NOUN
app01-10633	62	43	accurately	accurately	ADV
app01-10633	62	44	.	.	PUNCT
app01-10633	63	1	the	the	DET
app01-10633	63	2	newly	newly	ADV
app01-10633	63	3	formed	form	VERB
app01-10633	63	4	dataset	dataset	NOUN
app01-10633	63	5	incorporates	incorporate	VERB
app01-10633	63	6	observations	observation	NOUN
app01-10633	63	7	and	and	CCONJ
app01-10633	63	8	speed	speed	NOUN
app01-10633	63	9	estimates	estimate	NOUN
app01-10633	63	10	from	from	ADP
app01-10633	63	11	various	various	ADJ
app01-10633	63	12	experiments	experiment	NOUN
app01-10633	63	13	but	but	CCONJ
app01-10633	63	14	applies	apply	VERB
app01-10633	63	15	fresh	fresh	ADJ
app01-10633	63	16	evaluation	evaluation	NOUN
app01-10633	63	17	criteria	criterion	NOUN
app01-10633	63	18	centered	center	VERB
app01-10633	63	19	around	around	ADP
app01-10633	63	20	the	the	DET
app01-10633	63	21	proximity	proximity	NOUN
app01-10633	63	22	and	and	CCONJ
app01-10633	63	23	characteristics	characteristic	NOUN
app01-10633	63	24	of	of	ADP
app01-10633	63	25	the	the	DET
app01-10633	63	26	roadside	roadside	NOUN
app01-10633	63	27	environment	environment	NOUN
app01-10633	63	28	.	.	PUNCT
app01-10633	64	1	these	these	DET
app01-10633	64	2	criteria	criterion	NOUN
app01-10633	64	3	include	include	VERB
app01-10633	64	4	elements	element	NOUN
app01-10633	64	5	such	such	ADJ
app01-10633	64	6	as	as	ADP
app01-10633	64	7	the	the	DET
app01-10633	64	8	type	type	NOUN
app01-10633	64	9	of	of	ADP
app01-10633	64	10	surrounding	surround	VERB
app01-10633	64	11	landscape	landscape	NOUN
app01-10633	64	12	(	(	PUNCT
app01-10633	64	13	e.g.	e.g.	ADV
app01-10633	64	14	,	,	PUNCT
app01-10633	64	15	forest	forest	NOUN
app01-10633	64	16	,	,	PUNCT
app01-10633	64	17	urban	urban	ADJ
app01-10633	64	18	,	,	PUNCT
app01-10633	64	19	rural	rural	ADJ
app01-10633	64	20	)	)	PUNCT
app01-10633	64	21	,	,	PUNCT
app01-10633	64	22	distance	distance	NOUN
app01-10633	64	23	of	of	ADP
app01-10633	64	24	roadside	roadside	NOUN
app01-10633	64	25	features	feature	NOUN
app01-10633	64	26	from	from	ADP
app01-10633	64	27	the	the	DET
app01-10633	64	28	road	road	NOUN
app01-10633	64	29	(	(	PUNCT
app01-10633	64	30	such	such	ADJ
app01-10633	64	31	as	as	ADP
app01-10633	64	32	trees	tree	NOUN
app01-10633	64	33	,	,	PUNCT
app01-10633	64	34	barriers	barrier	NOUN
app01-10633	64	35	,	,	PUNCT
app01-10633	64	36	or	or	CCONJ
app01-10633	64	37	open	open	ADJ
app01-10633	64	38	fields	field	NOUN
app01-10633	64	39	)	)	PUNCT
app01-10633	64	40	,	,	PUNCT
app01-10633	64	41	and	and	CCONJ
app01-10633	64	42	visibility	visibility	NOUN
app01-10633	64	43	conditions	condition	NOUN
app01-10633	64	44	.	.	PUNCT
app01-10633	65	1	by	by	ADP
app01-10633	65	2	reorganizing	reorganize	VERB
app01-10633	65	3	and	and	CCONJ
app01-10633	65	4	analyzing	analyze	VERB
app01-10633	65	5	the	the	DET
app01-10633	65	6	data	datum	NOUN
app01-10633	65	7	through	through	ADP
app01-10633	65	8	this	this	DET
app01-10633	65	9	new	new	ADJ
app01-10633	65	10	lens	len	NOUN
app01-10633	65	11	,	,	PUNCT
app01-10633	65	12	the	the	DET
app01-10633	65	13	study	study	NOUN
app01-10633	65	14	aims	aim	VERB
app01-10633	65	15	to	to	PART
app01-10633	65	16	explore	explore	VERB
app01-10633	65	17	how	how	SCONJ
app01-10633	65	18	these	these	DET
app01-10633	65	19	environmental	environmental	ADJ
app01-10633	65	20	factors	factor	NOUN
app01-10633	65	21	affect	affect	VERB
app01-10633	65	22	speed	speed	NOUN
app01-10633	65	23	perception	perception	NOUN
app01-10633	65	24	in	in	ADP
app01-10633	65	25	ways	way	NOUN
app01-10633	65	26	not	not	PART
app01-10633	65	27	considered	consider	VERB
app01-10633	65	28	in	in	ADP
app01-10633	65	29	the	the	DET
app01-10633	65	30	original	original	ADJ
app01-10633	65	31	analyses	analysis	NOUN
app01-10633	65	32	.	.	PUNCT
app01-10633	66	1	this	this	DET
app01-10633	66	2	approach	approach	NOUN
app01-10633	66	3	provides	provide	VERB
app01-10633	66	4	a	a	DET
app01-10633	66	5	novel	novel	ADJ
app01-10633	66	6	understanding	understanding	NOUN
app01-10633	66	7	of	of	ADP
app01-10633	66	8	roadside	roadside	ADJ
app01-10633	66	9	environments	environment	NOUN
app01-10633	66	10	’	'	PUNCT
app01-10633	66	11	role	role	NOUN
app01-10633	66	12	in	in	ADP
app01-10633	66	13	speed	speed	NOUN
app01-10633	66	14	estimation	estimation	NOUN
app01-10633	66	15	,	,	PUNCT
app01-10633	66	16	contributing	contribute	VERB
app01-10633	66	17	to	to	ADP
app01-10633	66	18	more	more	ADV
app01-10633	66	19	effective	effective	ADJ
app01-10633	66	20	traffic	traffic	NOUN
app01-10633	66	21	safety	safety	NOUN
app01-10633	66	22	measures	measure	NOUN
app01-10633	66	23	and	and	CCONJ
app01-10633	66	24	road	road	NOUN
app01-10633	66	25	design	design	NOUN
app01-10633	66	26	.	.	PUNCT
app01-10633	67	1	2.1	2.1	NUM
app01-10633	67	2	.	.	PUNCT
app01-10633	67	3	original	original	ADJ
app01-10633	67	4	datasets	dataset	NOUN
app01-10633	67	5	the	the	DET
app01-10633	67	6	master	master	NOUN
app01-10633	67	7	thesis	thesis	NOUN
app01-10633	67	8	focuses	focus	VERB
app01-10633	67	9	on	on	ADP
app01-10633	67	10	the	the	DET
app01-10633	67	11	perception	perception	NOUN
app01-10633	67	12	of	of	ADP
app01-10633	67	13	vehicle	vehicle	NOUN
app01-10633	67	14	speed	speed	NOUN
app01-10633	67	15	from	from	ADP
app01-10633	67	16	the	the	DET
app01-10633	67	17	pedestrian	pedestrian	NOUN
app01-10633	67	18	’s	’s	PART
app01-10633	67	19	perspective	perspective	NOUN
app01-10633	68	1	[	[	X
app01-10633	68	2	8	8	NUM
app01-10633	68	3	]	]	PUNCT
app01-10633	68	4	,	,	PUNCT
app01-10633	68	5	with	with	ADP
app01-10633	68	6	an	an	DET
app01-10633	68	7	experiment	experiment	NOUN
app01-10633	68	8	designed	design	VERB
app01-10633	68	9	to	to	PART
app01-10633	68	10	gather	gather	VERB
app01-10633	68	11	speed	speed	NOUN
app01-10633	68	12	estimation	estimation	NOUN
app01-10633	68	13	data	datum	NOUN
app01-10633	68	14	under	under	ADP
app01-10633	68	15	various	various	ADJ
app01-10633	68	16	conditions	condition	NOUN
app01-10633	68	17	.	.	PUNCT
app01-10633	69	1	the	the	DET
app01-10633	69	2	measurement	measurement	NOUN
app01-10633	69	3	setup	setup	NOUN
app01-10633	69	4	involved	involve	VERB
app01-10633	69	5	a	a	DET
app01-10633	69	6	sample	sample	NOUN
app01-10633	69	7	of	of	ADP
app01-10633	69	8	13	13	NUM
app01-10633	69	9	respondents	respondent	NOUN
app01-10633	69	10	(	(	PUNCT
app01-10633	69	11	7	7	NUM
app01-10633	69	12	men	man	NOUN
app01-10633	69	13	and	and	CCONJ
app01-10633	69	14	6	6	NUM
app01-10633	69	15	women	woman	NOUN
app01-10633	69	16	)	)	PUNCT
app01-10633	69	17	who	who	PRON
app01-10633	69	18	participated	participate	VERB
app01-10633	69	19	in	in	ADP
app01-10633	69	20	two	two	NUM
app01-10633	69	21	days	day	NOUN
app01-10633	69	22	of	of	ADP
app01-10633	69	23	measurements	measurement	NOUN
app01-10633	69	24	.	.	PUNCT
app01-10633	70	1	the	the	DET
app01-10633	70	2	experiment	experiment	NOUN
app01-10633	70	3	was	be	AUX
app01-10633	70	4	conducted	conduct	VERB
app01-10633	70	5	at	at	ADP
app01-10633	70	6	multiple	multiple	ADJ
app01-10633	70	7	locations	location	NOUN
app01-10633	70	8	,	,	PUNCT
app01-10633	70	9	with	with	ADP
app01-10633	70	10	vehicles	vehicle	NOUN
app01-10633	70	11	traveling	travel	VERB
app01-10633	70	12	at	at	ADP
app01-10633	70	13	specified	specified	ADJ
app01-10633	70	14	speeds	speed	NOUN
app01-10633	70	15	(	(	PUNCT
app01-10633	70	16	e.g.	e.g.	ADV
app01-10633	70	17	,	,	PUNCT
app01-10633	70	18	30	30	NUM
app01-10633	70	19	km	km	NOUN
app01-10633	70	20	h−1	h−1	PROPN
app01-10633	70	21	,	,	PUNCT
app01-10633	70	22	50	50	NUM
app01-10633	70	23	km	km	NOUN
app01-10633	70	24	h−1	h−1	PROPN
app01-10633	70	25	,	,	PUNCT
app01-10633	70	26	and	and	CCONJ
app01-10633	70	27	90	90	NUM
app01-10633	70	28	km	km	NOUN
app01-10633	70	29	h−1	h−1	PROPN
app01-10633	70	30	)	)	PUNCT
app01-10633	70	31	.	.	PUNCT
app01-10633	71	1	the	the	DET
app01-10633	71	2	participants	participant	NOUN
app01-10633	71	3	observed	observe	VERB
app01-10633	71	4	these	these	DET
app01-10633	71	5	vehicles	vehicle	NOUN
app01-10633	71	6	and	and	CCONJ
app01-10633	71	7	provided	provide	VERB
app01-10633	71	8	estimates	estimate	NOUN
app01-10633	71	9	of	of	ADP
app01-10633	71	10	their	their	PRON
app01-10633	71	11	speeds	speed	NOUN
app01-10633	71	12	.	.	PUNCT
app01-10633	72	1	the	the	DET
app01-10633	72	2	total	total	ADJ
app01-10633	72	3	dataset	dataset	NOUN
app01-10633	72	4	comprised	comprise	VERB
app01-10633	72	5	2	2	NUM
app01-10633	72	6	090	090	NUM
app01-10633	72	7	speed	speed	NOUN
app01-10633	72	8	estimates	estimate	NOUN
app01-10633	72	9	,	,	PUNCT
app01-10633	72	10	with	with	ADP
app01-10633	72	11	895	895	NUM
app01-10633	72	12	estimates	estimate	NOUN
app01-10633	72	13	from	from	ADP
app01-10633	72	14	men	man	NOUN
app01-10633	72	15	and	and	CCONJ
app01-10633	72	16	1	1	NUM
app01-10633	72	17	195	195	NUM
app01-10633	72	18	from	from	ADP
app01-10633	72	19	women	woman	NOUN
app01-10633	72	20	.	.	PUNCT
app01-10633	73	1	these	these	DET
app01-10633	73	2	estimates	estimate	NOUN
app01-10633	73	3	were	be	AUX
app01-10633	73	4	later	later	ADV
app01-10633	73	5	analyzed	analyze	VERB
app01-10633	73	6	to	to	PART
app01-10633	73	7	understand	understand	VERB
app01-10633	73	8	the	the	DET
app01-10633	73	9	factors	factor	NOUN
app01-10633	73	10	that	that	PRON
app01-10633	73	11	influenced	influence	VERB
app01-10633	73	12	the	the	DET
app01-10633	73	13	accuracy	accuracy	NOUN
app01-10633	73	14	of	of	ADP
app01-10633	73	15	speed	speed	NOUN
app01-10633	73	16	perception	perception	NOUN
app01-10633	73	17	,	,	PUNCT
app01-10633	73	18	such	such	ADJ
app01-10633	73	19	as	as	ADP
app01-10633	73	20	vehicle	vehicle	NOUN
app01-10633	73	21	type	type	NOUN
app01-10633	73	22	,	,	PUNCT
app01-10633	73	23	gender	gender	NOUN
app01-10633	73	24	,	,	PUNCT
app01-10633	73	25	and	and	CCONJ
app01-10633	73	26	the	the	DET
app01-10633	73	27	roadside	roadside	NOUN
app01-10633	73	28	environment	environment	NOUN
app01-10633	73	29	.	.	PUNCT
app01-10633	74	1	117	117	NUM
app01-10633	74	2	martin	martin	PROPN
app01-10633	74	3	rak	rak	PROPN
app01-10633	74	4	,	,	PUNCT
app01-10633	74	5	martin	martin	PROPN
app01-10633	74	6	bilík	bilík	PROPN
app01-10633	74	7	acta	acta	PROPN
app01-10633	74	8	polytechnica	polytechnica	PROPN
app01-10633	74	9	ctu	ctu	NOUN
app01-10633	74	10	proceedings	proceeding	NOUN
app01-10633	74	11	the	the	DET
app01-10633	74	12	experiment	experiment	NOUN
app01-10633	74	13	in	in	ADP
app01-10633	74	14	barbora	barbora	PROPN
app01-10633	74	15	formanová	formanová	PROPN
app01-10633	74	16	’s	’s	PART
app01-10633	74	17	thesis	thesis	NOUN
app01-10633	74	18	[	[	X
app01-10633	74	19	9	9	NUM
app01-10633	74	20	]	]	PUNCT
app01-10633	74	21	took	take	VERB
app01-10633	74	22	place	place	NOUN
app01-10633	74	23	on	on	ADP
app01-10633	74	24	a	a	DET
app01-10633	74	25	1.9	1.9	NUM
app01-10633	74	26	km	km	NOUN
app01-10633	74	27	-	-	PUNCT
app01-10633	74	28	long	long	ADJ
app01-10633	74	29	road	road	NOUN
app01-10633	74	30	,	,	PUNCT
app01-10633	74	31	chosen	choose	VERB
app01-10633	74	32	for	for	ADP
app01-10633	74	33	its	its	PRON
app01-10633	74	34	low	low	ADJ
app01-10633	74	35	traffic	traffic	NOUN
app01-10633	74	36	intensity	intensity	NOUN
app01-10633	74	37	and	and	CCONJ
app01-10633	74	38	suitability	suitability	NOUN
app01-10633	74	39	for	for	ADP
app01-10633	74	40	testing	testing	NOUN
app01-10633	74	41	speeds	speed	NOUN
app01-10633	74	42	at	at	ADP
app01-10633	74	43	30	30	NUM
app01-10633	74	44	km	km	NOUN
app01-10633	74	45	h−1	h−1	PROPN
app01-10633	74	46	,	,	PUNCT
app01-10633	74	47	50	50	NUM
app01-10633	74	48	km	km	NOUN
app01-10633	74	49	h−1	h−1	PROPN
app01-10633	74	50	,	,	PUNCT
app01-10633	74	51	and	and	CCONJ
app01-10633	74	52	70	70	NUM
app01-10633	74	53	km	km	NOUN
app01-10633	74	54	h−1	h−1	PROPN
app01-10633	74	55	.	.	PUNCT
app01-10633	75	1	the	the	DET
app01-10633	75	2	road	road	NOUN
app01-10633	75	3	surface	surface	NOUN
app01-10633	75	4	was	be	AUX
app01-10633	75	5	asphalt	asphalt	NOUN
app01-10633	75	6	but	but	CCONJ
app01-10633	75	7	showed	show	VERB
app01-10633	75	8	signs	sign	NOUN
app01-10633	75	9	of	of	ADP
app01-10633	75	10	wear	wear	NOUN
app01-10633	75	11	,	,	PUNCT
app01-10633	75	12	including	include	VERB
app01-10633	75	13	cracks	crack	NOUN
app01-10633	75	14	and	and	CCONJ
app01-10633	75	15	potholes	pothole	NOUN
app01-10633	75	16	,	,	PUNCT
app01-10633	75	17	providing	provide	VERB
app01-10633	75	18	a	a	DET
app01-10633	75	19	realistic	realistic	ADJ
app01-10633	75	20	driving	driving	NOUN
app01-10633	75	21	environment	environment	NOUN
app01-10633	75	22	.	.	PUNCT
app01-10633	76	1	the	the	DET
app01-10633	76	2	surroundings	surrounding	NOUN
app01-10633	76	3	of	of	ADP
app01-10633	76	4	the	the	DET
app01-10633	76	5	test	test	NOUN
app01-10633	76	6	road	road	NOUN
app01-10633	76	7	were	be	AUX
app01-10633	76	8	primarily	primarily	ADV
app01-10633	76	9	agricultural	agricultural	ADJ
app01-10633	76	10	fields	field	NOUN
app01-10633	76	11	,	,	PUNCT
app01-10633	76	12	offering	offer	VERB
app01-10633	76	13	minimal	minimal	ADJ
app01-10633	76	14	distractions	distraction	NOUN
app01-10633	76	15	,	,	PUNCT
app01-10633	76	16	which	which	PRON
app01-10633	76	17	allowed	allow	VERB
app01-10633	76	18	drivers	driver	NOUN
app01-10633	76	19	to	to	PART
app01-10633	76	20	focus	focus	VERB
app01-10633	76	21	on	on	ADP
app01-10633	76	22	estimating	estimate	VERB
app01-10633	76	23	vehicle	vehicle	NOUN
app01-10633	76	24	speed	speed	NOUN
app01-10633	76	25	.	.	PUNCT
app01-10633	77	1	600	600	NUM
app01-10633	77	2	-	-	PUNCT
app01-10633	77	3	speed	speed	NOUN
app01-10633	77	4	estimates	estimate	NOUN
app01-10633	77	5	were	be	AUX
app01-10633	77	6	collected	collect	VERB
app01-10633	77	7	from	from	ADP
app01-10633	77	8	10	10	NUM
app01-10633	77	9	drivers	driver	NOUN
app01-10633	77	10	across	across	ADP
app01-10633	77	11	10	10	NUM
app01-10633	77	12	test	test	NOUN
app01-10633	77	13	drives	drive	NOUN
app01-10633	77	14	,	,	PUNCT
app01-10633	77	15	with	with	ADP
app01-10633	77	16	drivers	driver	NOUN
app01-10633	77	17	estimating	estimate	VERB
app01-10633	77	18	speeds	speed	NOUN
app01-10633	77	19	in	in	ADP
app01-10633	77	20	both	both	CCONJ
app01-10633	77	21	their	their	PRON
app01-10633	77	22	vehicles	vehicle	NOUN
app01-10633	77	23	and	and	CCONJ
app01-10633	77	24	borrowed	borrow	VERB
app01-10633	77	25	ones	one	NOUN
app01-10633	77	26	.	.	PUNCT
app01-10633	78	1	this	this	DET
app01-10633	78	2	setup	setup	NOUN
app01-10633	78	3	allowed	allow	VERB
app01-10633	78	4	for	for	ADP
app01-10633	78	5	investigating	investigate	VERB
app01-10633	78	6	how	how	SCONJ
app01-10633	78	7	drivers	driver	NOUN
app01-10633	78	8	perceive	perceive	ADJ
app01-10633	78	9	vehicle	vehicle	NOUN
app01-10633	78	10	speed	speed	NOUN
app01-10633	78	11	in	in	ADP
app01-10633	78	12	real	real	ADJ
app01-10633	78	13	-	-	PUNCT
app01-10633	78	14	world	world	NOUN
app01-10633	78	15	conditions	condition	NOUN
app01-10633	78	16	.	.	PUNCT
app01-10633	79	1	the	the	DET
app01-10633	79	2	thesis	thesis	NOUN
app01-10633	79	3	by	by	ADP
app01-10633	79	4	faruk	faruk	PROPN
app01-10633	79	5	pršeš	pršeš	PROPN
app01-10633	79	6	[	[	X
app01-10633	79	7	10	10	NUM
app01-10633	79	8	]	]	PUNCT
app01-10633	79	9	focuses	focus	VERB
app01-10633	79	10	on	on	ADP
app01-10633	79	11	passengers	passenger	NOUN
app01-10633	79	12	’	'	PUNCT
app01-10633	79	13	perceptions	perception	NOUN
app01-10633	79	14	of	of	ADP
app01-10633	79	15	oncoming	oncoming	ADJ
app01-10633	79	16	vehicle	vehicle	NOUN
app01-10633	79	17	speed	speed	NOUN
app01-10633	79	18	in	in	ADP
app01-10633	79	19	moving	move	VERB
app01-10633	79	20	vehicles	vehicle	NOUN
app01-10633	79	21	.	.	PUNCT
app01-10633	80	1	the	the	DET
app01-10633	80	2	objective	objective	NOUN
app01-10633	80	3	was	be	AUX
app01-10633	80	4	to	to	PART
app01-10633	80	5	evaluate	evaluate	VERB
app01-10633	80	6	how	how	SCONJ
app01-10633	80	7	accurately	accurately	ADV
app01-10633	80	8	passengers	passenger	NOUN
app01-10633	80	9	can	can	AUX
app01-10633	80	10	estimate	estimate	VERB
app01-10633	80	11	the	the	DET
app01-10633	80	12	speed	speed	NOUN
app01-10633	80	13	of	of	ADP
app01-10633	80	14	an	an	DET
app01-10633	80	15	oncoming	oncoming	ADJ
app01-10633	80	16	vehicle	vehicle	NOUN
app01-10633	80	17	under	under	ADP
app01-10633	80	18	different	different	ADJ
app01-10633	80	19	conditions	condition	NOUN
app01-10633	80	20	,	,	PUNCT
app01-10633	80	21	considering	consider	VERB
app01-10633	80	22	factors	factor	NOUN
app01-10633	80	23	such	such	ADJ
app01-10633	80	24	as	as	ADP
app01-10633	80	25	age	age	NOUN
app01-10633	80	26	,	,	PUNCT
app01-10633	80	27	gender	gender	NOUN
app01-10633	80	28	,	,	PUNCT
app01-10633	80	29	driving	driving	NOUN
app01-10633	80	30	experience	experience	NOUN
app01-10633	80	31	,	,	PUNCT
app01-10633	80	32	and	and	CCONJ
app01-10633	80	33	vehicle	vehicle	NOUN
app01-10633	80	34	type	type	NOUN
app01-10633	80	35	.	.	PUNCT
app01-10633	81	1	the	the	DET
app01-10633	81	2	experiment	experiment	NOUN
app01-10633	81	3	was	be	AUX
app01-10633	81	4	conducted	conduct	VERB
app01-10633	81	5	over	over	ADP
app01-10633	81	6	two	two	NUM
app01-10633	81	7	days	day	NOUN
app01-10633	81	8	with	with	ADP
app01-10633	81	9	23	23	NUM
app01-10633	81	10	participants	participant	NOUN
app01-10633	81	11	(	(	PUNCT
app01-10633	81	12	15	15	NUM
app01-10633	81	13	men	man	NOUN
app01-10633	81	14	and	and	CCONJ
app01-10633	81	15	8	8	NUM
app01-10633	81	16	women	woman	NOUN
app01-10633	81	17	)	)	PUNCT
app01-10633	81	18	,	,	PUNCT
app01-10633	81	19	including	include	VERB
app01-10633	81	20	drivers	driver	NOUN
app01-10633	81	21	and	and	CCONJ
app01-10633	81	22	non	non	NOUN
app01-10633	81	23	-	-	NOUN
app01-10633	81	24	drivers	driver	NOUN
app01-10633	81	25	.	.	PUNCT
app01-10633	82	1	the	the	DET
app01-10633	82	2	participants	participant	NOUN
app01-10633	82	3	were	be	AUX
app01-10633	82	4	seated	seat	VERB
app01-10633	82	5	in	in	ADP
app01-10633	82	6	various	various	ADJ
app01-10633	82	7	vehicles	vehicle	NOUN
app01-10633	82	8	and	and	CCONJ
app01-10633	82	9	tasked	task	VERB
app01-10633	82	10	with	with	ADP
app01-10633	82	11	estimating	estimate	VERB
app01-10633	82	12	the	the	DET
app01-10633	82	13	speed	speed	NOUN
app01-10633	82	14	of	of	ADP
app01-10633	82	15	oncoming	oncoming	ADJ
app01-10633	82	16	vehicles	vehicle	NOUN
app01-10633	82	17	under	under	ADP
app01-10633	82	18	real	real	ADJ
app01-10633	82	19	-	-	PUNCT
app01-10633	82	20	world	world	NOUN
app01-10633	82	21	traffic	traffic	NOUN
app01-10633	82	22	conditions	condition	NOUN
app01-10633	82	23	.	.	PUNCT
app01-10633	83	1	the	the	DET
app01-10633	83	2	study	study	NOUN
app01-10633	83	3	was	be	AUX
app01-10633	83	4	conducted	conduct	VERB
app01-10633	83	5	on	on	ADP
app01-10633	83	6	a	a	DET
app01-10633	83	7	2	2	NUM
app01-10633	83	8	km	km	NOUN
app01-10633	83	9	road	road	NOUN
app01-10633	83	10	with	with	ADP
app01-10633	83	11	low	low	ADJ
app01-10633	83	12	traffic	traffic	NOUN
app01-10633	83	13	intensity	intensity	NOUN
app01-10633	83	14	in	in	ADP
app01-10633	83	15	a	a	DET
app01-10633	83	16	city	city	NOUN
app01-10633	83	17	.	.	PUNCT
app01-10633	84	1	the	the	DET
app01-10633	84	2	experiment	experiment	NOUN
app01-10633	84	3	assessed	assess	VERB
app01-10633	84	4	speeds	speed	NOUN
app01-10633	84	5	of	of	ADP
app01-10633	84	6	50	50	NUM
app01-10633	84	7	km	km	NOUN
app01-10633	84	8	h−1	h−1	PROPN
app01-10633	84	9	,	,	PUNCT
app01-10633	84	10	70	70	NUM
app01-10633	84	11	km	km	NOUN
app01-10633	84	12	h−1	h−1	PROPN
app01-10633	84	13	,	,	PUNCT
app01-10633	84	14	and	and	CCONJ
app01-10633	84	15	90	90	NUM
app01-10633	84	16	km	km	NOUN
app01-10633	84	17	h−1	h−1	PROPN
app01-10633	84	18	.	.	PUNCT
app01-10633	85	1	the	the	DET
app01-10633	85	2	experiment	experiment	NOUN
app01-10633	85	3	gathered	gather	VERB
app01-10633	85	4	3	3	NUM
app01-10633	85	5	240	240	NUM
app01-10633	85	6	speed	speed	NOUN
app01-10633	85	7	estimates	estimate	NOUN
app01-10633	85	8	–	–	PUNCT
app01-10633	85	9	1	1	NUM
app01-10633	85	10	620	620	NUM
app01-10633	85	11	estimates	estimate	NOUN
app01-10633	85	12	for	for	ADP
app01-10633	85	13	the	the	DET
app01-10633	85	14	speed	speed	NOUN
app01-10633	85	15	of	of	ADP
app01-10633	85	16	oncoming	oncoming	ADJ
app01-10633	85	17	vehicles	vehicle	NOUN
app01-10633	85	18	and	and	CCONJ
app01-10633	85	19	1	1	NUM
app01-10633	85	20	620	620	NUM
app01-10633	85	21	estimates	estimate	NOUN
app01-10633	85	22	for	for	ADP
app01-10633	85	23	the	the	DET
app01-10633	85	24	speed	speed	NOUN
app01-10633	85	25	of	of	ADP
app01-10633	85	26	the	the	DET
app01-10633	85	27	vehicle	vehicle	NOUN
app01-10633	85	28	in	in	ADP
app01-10633	85	29	which	which	PRON
app01-10633	85	30	the	the	DET
app01-10633	85	31	participants	participant	NOUN
app01-10633	85	32	were	be	AUX
app01-10633	85	33	seated	seat	VERB
app01-10633	85	34	.	.	PUNCT
app01-10633	86	1	the	the	DET
app01-10633	86	2	results	result	NOUN
app01-10633	86	3	were	be	AUX
app01-10633	86	4	analyzed	analyze	VERB
app01-10633	86	5	to	to	PART
app01-10633	86	6	assess	assess	VERB
app01-10633	86	7	the	the	DET
app01-10633	86	8	accuracy	accuracy	NOUN
app01-10633	86	9	of	of	ADP
app01-10633	86	10	speed	speed	NOUN
app01-10633	86	11	estimations	estimation	NOUN
app01-10633	86	12	,	,	PUNCT
app01-10633	86	13	focusing	focus	VERB
app01-10633	86	14	on	on	ADP
app01-10633	86	15	how	how	SCONJ
app01-10633	86	16	these	these	DET
app01-10633	86	17	estimations	estimation	NOUN
app01-10633	86	18	were	be	AUX
app01-10633	86	19	influenced	influence	VERB
app01-10633	86	20	by	by	ADP
app01-10633	86	21	the	the	DET
app01-10633	86	22	participant	participant	NOUN
app01-10633	86	23	’s	’s	PART
app01-10633	86	24	age	age	NOUN
app01-10633	86	25	,	,	PUNCT
app01-10633	86	26	gender	gender	NOUN
app01-10633	86	27	,	,	PUNCT
app01-10633	86	28	driving	driving	NOUN
app01-10633	86	29	experience	experience	NOUN
app01-10633	86	30	,	,	PUNCT
app01-10633	86	31	and	and	CCONJ
app01-10633	86	32	position	position	NOUN
app01-10633	86	33	in	in	ADP
app01-10633	86	34	the	the	DET
app01-10633	86	35	vehicle	vehicle	NOUN
app01-10633	86	36	.	.	PUNCT
app01-10633	87	1	nela	nela	PROPN
app01-10633	87	2	budinová	budinová	PROPN
app01-10633	87	3	’s	’s	PART
app01-10633	87	4	thesis	thesis	NOUN
app01-10633	87	5	[	[	X
app01-10633	87	6	11	11	NUM
app01-10633	87	7	]	]	AUX
app01-10633	87	8	examines	examine	VERB
app01-10633	87	9	passengers	passenger	NOUN
app01-10633	87	10	’	'	PUNCT
app01-10633	87	11	perception	perception	NOUN
app01-10633	87	12	of	of	ADP
app01-10633	87	13	vehicle	vehicle	NOUN
app01-10633	87	14	speed	speed	NOUN
app01-10633	87	15	,	,	PUNCT
app01-10633	87	16	focusing	focus	VERB
app01-10633	87	17	on	on	ADP
app01-10633	87	18	the	the	DET
app01-10633	87	19	influence	influence	NOUN
app01-10633	87	20	of	of	ADP
app01-10633	87	21	driving	drive	VERB
app01-10633	87	22	experience	experience	NOUN
app01-10633	87	23	and	and	CCONJ
app01-10633	87	24	distractions	distraction	NOUN
app01-10633	87	25	.	.	PUNCT
app01-10633	88	1	the	the	DET
app01-10633	88	2	experiment	experiment	NOUN
app01-10633	88	3	was	be	AUX
app01-10633	88	4	conducted	conduct	VERB
app01-10633	88	5	on	on	ADP
app01-10633	88	6	a	a	DET
app01-10633	88	7	12	12	NUM
app01-10633	88	8	km	km	NOUN
app01-10633	88	9	route	route	NOUN
app01-10633	88	10	,	,	PUNCT
app01-10633	88	11	utilizing	utilize	VERB
app01-10633	88	12	different	different	ADJ
app01-10633	88	13	road	road	NOUN
app01-10633	88	14	types	type	NOUN
app01-10633	88	15	such	such	ADJ
app01-10633	88	16	as	as	ADP
app01-10633	88	17	urban	urban	ADJ
app01-10633	88	18	,	,	PUNCT
app01-10633	88	19	rural	rural	ADJ
app01-10633	88	20	,	,	PUNCT
app01-10633	88	21	and	and	CCONJ
app01-10633	88	22	highway	highway	NOUN
app01-10633	88	23	settings	setting	NOUN
app01-10633	88	24	.	.	PUNCT
app01-10633	89	1	participants	participant	NOUN
app01-10633	89	2	with	with	ADP
app01-10633	89	3	varying	vary	VERB
app01-10633	89	4	levels	level	NOUN
app01-10633	89	5	of	of	ADP
app01-10633	89	6	driving	drive	VERB
app01-10633	89	7	experience	experience	NOUN
app01-10633	89	8	were	be	AUX
app01-10633	89	9	asked	ask	VERB
app01-10633	89	10	to	to	PART
app01-10633	89	11	estimate	estimate	VERB
app01-10633	89	12	the	the	DET
app01-10633	89	13	vehicle	vehicle	NOUN
app01-10633	89	14	’s	’s	PART
app01-10633	89	15	speed	speed	NOUN
app01-10633	89	16	under	under	ADP
app01-10633	89	17	two	two	NUM
app01-10633	89	18	conditions	condition	NOUN
app01-10633	89	19	:	:	PUNCT
app01-10633	89	20	one	one	NUM
app01-10633	89	21	where	where	SCONJ
app01-10633	89	22	they	they	PRON
app01-10633	89	23	were	be	AUX
app01-10633	89	24	fully	fully	ADV
app01-10633	89	25	focused	focus	VERB
app01-10633	89	26	on	on	ADP
app01-10633	89	27	the	the	DET
app01-10633	89	28	road	road	NOUN
app01-10633	89	29	and	and	CCONJ
app01-10633	89	30	another	another	PRON
app01-10633	89	31	where	where	SCONJ
app01-10633	89	32	they	they	PRON
app01-10633	89	33	were	be	AUX
app01-10633	89	34	distracted	distract	VERB
app01-10633	89	35	by	by	ADP
app01-10633	89	36	solving	solve	VERB
app01-10633	89	37	sudoku	sudoku	ADJ
app01-10633	89	38	puzzles	puzzle	NOUN
app01-10633	89	39	.	.	PUNCT
app01-10633	90	1	the	the	DET
app01-10633	90	2	experiment	experiment	NOUN
app01-10633	90	3	aimed	aim	VERB
app01-10633	90	4	to	to	PART
app01-10633	90	5	assess	assess	VERB
app01-10633	90	6	how	how	SCONJ
app01-10633	90	7	attention	attention	NOUN
app01-10633	90	8	and	and	CCONJ
app01-10633	90	9	distraction	distraction	NOUN
app01-10633	90	10	impact	impact	NOUN
app01-10633	90	11	speed	speed	NOUN
app01-10633	90	12	perception	perception	NOUN
app01-10633	90	13	across	across	ADP
app01-10633	90	14	different	different	ADJ
app01-10633	90	15	types	type	NOUN
app01-10633	90	16	of	of	ADP
app01-10633	90	17	vehicles	vehicle	NOUN
app01-10633	90	18	.	.	PUNCT
app01-10633	91	1	2	2	NUM
app01-10633	91	2	119	119	NUM
app01-10633	91	3	speed	speed	NOUN
app01-10633	91	4	estimates	estimate	NOUN
app01-10633	91	5	were	be	AUX
app01-10633	91	6	collected	collect	VERB
app01-10633	91	7	,	,	PUNCT
app01-10633	91	8	with	with	ADP
app01-10633	91	9	2	2	NUM
app01-10633	91	10	174	174	NUM
app01-10633	91	11	actual	actual	ADJ
app01-10633	91	12	speed	speed	NOUN
app01-10633	91	13	measurements	measurement	NOUN
app01-10633	91	14	recorded	record	VERB
app01-10633	91	15	.	.	PUNCT
app01-10633	92	1	a	a	DET
app01-10633	92	2	slight	slight	ADJ
app01-10633	92	3	discrepancy	discrepancy	NOUN
app01-10633	92	4	in	in	ADP
app01-10633	92	5	the	the	DET
app01-10633	92	6	number	number	NOUN
app01-10633	92	7	of	of	ADP
app01-10633	92	8	estimates	estimate	NOUN
app01-10633	92	9	was	be	AUX
app01-10633	92	10	due	due	ADJ
app01-10633	92	11	to	to	PART
app01-10633	92	12	signal	signal	VERB
app01-10633	92	13	transmission	transmission	NOUN
app01-10633	92	14	issues	issue	NOUN
app01-10633	92	15	encountered	encounter	VERB
app01-10633	92	16	during	during	ADP
app01-10633	92	17	the	the	DET
app01-10633	92	18	experiment	experiment	NOUN
app01-10633	92	19	.	.	PUNCT
app01-10633	93	1	the	the	DET
app01-10633	93	2	results	result	NOUN
app01-10633	93	3	provided	provide	VERB
app01-10633	93	4	valuable	valuable	ADJ
app01-10633	93	5	insights	insight	NOUN
app01-10633	93	6	into	into	ADP
app01-10633	93	7	how	how	SCONJ
app01-10633	93	8	distractions	distraction	NOUN
app01-10633	93	9	and	and	CCONJ
app01-10633	93	10	driving	drive	VERB
app01-10633	93	11	experience	experience	NOUN
app01-10633	93	12	affect	affect	VERB
app01-10633	93	13	passengers	passenger	NOUN
app01-10633	93	14	’	'	PUNCT
app01-10633	93	15	ability	ability	NOUN
app01-10633	93	16	to	to	PART
app01-10633	93	17	accurately	accurately	ADV
app01-10633	93	18	estimate	estimate	VERB
app01-10633	93	19	vehicle	vehicle	NOUN
app01-10633	93	20	speed	speed	NOUN
app01-10633	93	21	in	in	ADP
app01-10633	93	22	real	real	ADJ
app01-10633	93	23	-	-	PUNCT
app01-10633	93	24	world	world	NOUN
app01-10633	93	25	conditions	condition	NOUN
app01-10633	93	26	.	.	PUNCT
app01-10633	94	1	an	an	DET
app01-10633	94	2	additional	additional	ADJ
app01-10633	94	3	study	study	NOUN
app01-10633	94	4	[	[	X
app01-10633	94	5	12	12	NUM
app01-10633	94	6	]	]	PUNCT
app01-10633	94	7	examined	examine	VERB
app01-10633	94	8	how	how	SCONJ
app01-10633	94	9	accurately	accurately	ADV
app01-10633	94	10	individuals	individual	NOUN
app01-10633	94	11	can	can	AUX
app01-10633	94	12	estimate	estimate	VERB
app01-10633	94	13	vehicle	vehicle	NOUN
app01-10633	94	14	speeds	speed	NOUN
app01-10633	94	15	during	during	ADP
app01-10633	94	16	nighttime	nighttime	ADJ
app01-10633	94	17	conditions	condition	NOUN
app01-10633	94	18	.	.	PUNCT
app01-10633	95	1	the	the	DET
app01-10633	95	2	study	study	NOUN
app01-10633	95	3	involved	involve	VERB
app01-10633	95	4	10	10	NUM
app01-10633	95	5	respondents	respondent	NOUN
app01-10633	95	6	(	(	PUNCT
app01-10633	95	7	5	5	NUM
app01-10633	95	8	men	man	NOUN
app01-10633	95	9	and	and	CCONJ
app01-10633	95	10	5	5	NUM
app01-10633	95	11	women	woman	NOUN
app01-10633	95	12	)	)	PUNCT
app01-10633	95	13	who	who	PRON
app01-10633	95	14	were	be	AUX
app01-10633	95	15	tasked	task	VERB
app01-10633	95	16	with	with	ADP
app01-10633	95	17	estimating	estimate	VERB
app01-10633	95	18	the	the	DET
app01-10633	95	19	speed	speed	NOUN
app01-10633	95	20	of	of	ADP
app01-10633	95	21	passing	pass	VERB
app01-10633	95	22	vehicles	vehicle	NOUN
app01-10633	95	23	.	.	PUNCT
app01-10633	96	1	the	the	DET
app01-10633	96	2	experiment	experiment	NOUN
app01-10633	96	3	was	be	AUX
app01-10633	96	4	conducted	conduct	VERB
app01-10633	96	5	over	over	ADP
app01-10633	96	6	two	two	NUM
app01-10633	96	7	days	day	NOUN
app01-10633	96	8	,	,	PUNCT
app01-10633	96	9	with	with	ADP
app01-10633	96	10	respondents	respondent	NOUN
app01-10633	96	11	positioned	position	VERB
app01-10633	96	12	15	15	NUM
app01-10633	96	13	meters	meter	NOUN
app01-10633	96	14	from	from	ADP
app01-10633	96	15	the	the	DET
app01-10633	96	16	road	road	NOUN
app01-10633	96	17	.	.	PUNCT
app01-10633	97	1	a	a	DET
app01-10633	97	2	total	total	NOUN
app01-10633	97	3	of	of	ADP
app01-10633	97	4	1	1	NUM
app01-10633	97	5	593	593	NUM
app01-10633	97	6	speed	speed	NOUN
app01-10633	97	7	estimates	estimate	NOUN
app01-10633	97	8	were	be	AUX
app01-10633	97	9	collected	collect	VERB
app01-10633	97	10	during	during	ADP
app01-10633	97	11	the	the	DET
app01-10633	97	12	experiment	experiment	NOUN
app01-10633	97	13	.	.	PUNCT
app01-10633	98	1	the	the	DET
app01-10633	98	2	results	result	NOUN
app01-10633	98	3	showed	show	VERB
app01-10633	98	4	that	that	SCONJ
app01-10633	98	5	women	woman	NOUN
app01-10633	98	6	generally	generally	ADV
app01-10633	98	7	overestimated	overestimate	VERB
app01-10633	98	8	speeds	speed	NOUN
app01-10633	98	9	,	,	PUNCT
app01-10633	98	10	while	while	SCONJ
app01-10633	98	11	men	man	NOUN
app01-10633	98	12	were	be	AUX
app01-10633	98	13	likelier	likeli	ADJ
app01-10633	98	14	to	to	PART
app01-10633	98	15	underestimate	underestimate	VERB
app01-10633	98	16	them	they	PRON
app01-10633	98	17	.	.	PUNCT
app01-10633	99	1	the	the	DET
app01-10633	99	2	observer	observer	NOUN
app01-10633	99	3	’s	’s	PART
app01-10633	99	4	position	position	NOUN
app01-10633	99	5	also	also	ADV
app01-10633	99	6	influenced	influence	VERB
app01-10633	99	7	the	the	DET
app01-10633	99	8	accuracy	accuracy	NOUN
app01-10633	99	9	,	,	PUNCT
app01-10633	99	10	with	with	ADP
app01-10633	99	11	estimates	estimate	NOUN
app01-10633	99	12	being	be	AUX
app01-10633	99	13	more	more	ADV
app01-10633	99	14	accurate	accurate	ADJ
app01-10633	99	15	when	when	SCONJ
app01-10633	99	16	respondents	respondent	NOUN
app01-10633	99	17	observed	observe	VERB
app01-10633	99	18	vehicles	vehicle	NOUN
app01-10633	99	19	from	from	ADP
app01-10633	99	20	a	a	DET
app01-10633	99	21	30	30	NUM
app01-10633	99	22	-	-	PUNCT
app01-10633	99	23	degree	degree	NOUN
app01-10633	99	24	angle	angle	NOUN
app01-10633	99	25	compared	compare	VERB
app01-10633	99	26	to	to	ADP
app01-10633	99	27	a	a	DET
app01-10633	99	28	90	90	NUM
app01-10633	99	29	-	-	PUNCT
app01-10633	99	30	degree	degree	NOUN
app01-10633	99	31	angle	angle	NOUN
app01-10633	99	32	.	.	PUNCT
app01-10633	100	1	other	other	ADJ
app01-10633	100	2	factors	factor	NOUN
app01-10633	100	3	,	,	PUNCT
app01-10633	100	4	such	such	ADJ
app01-10633	100	5	as	as	ADP
app01-10633	100	6	visual	visual	ADJ
app01-10633	100	7	and	and	CCONJ
app01-10633	100	8	auditory	auditory	ADJ
app01-10633	100	9	abilities	ability	NOUN
app01-10633	100	10	,	,	PUNCT
app01-10633	100	11	also	also	ADV
app01-10633	100	12	contributed	contribute	VERB
app01-10633	100	13	to	to	ADP
app01-10633	100	14	variations	variation	NOUN
app01-10633	100	15	in	in	ADP
app01-10633	100	16	speed	speed	NOUN
app01-10633	100	17	estimates	estimate	NOUN
app01-10633	100	18	.	.	PUNCT
app01-10633	101	1	overall	overall	ADV
app01-10633	101	2	,	,	PUNCT
app01-10633	101	3	the	the	DET
app01-10633	101	4	new	new	ADJ
app01-10633	101	5	dataset	dataset	NOUN
app01-10633	101	6	used	use	VERB
app01-10633	101	7	in	in	ADP
app01-10633	101	8	this	this	DET
app01-10633	101	9	study	study	NOUN
app01-10633	101	10	consists	consist	VERB
app01-10633	101	11	of	of	ADP
app01-10633	101	12	9	9	NUM
app01-10633	101	13	776	776	NUM
app01-10633	101	14	estimates	estimate	NOUN
app01-10633	101	15	.	.	PUNCT
app01-10633	102	1	2.2	2.2	NUM
app01-10633	102	2	.	.	PUNCT
app01-10633	103	1	new	new	ADJ
app01-10633	103	2	criteria	criterion	NOUN
app01-10633	103	3	this	this	DET
app01-10633	103	4	study	study	NOUN
app01-10633	103	5	builds	build	VERB
app01-10633	103	6	on	on	ADP
app01-10633	103	7	data	datum	NOUN
app01-10633	103	8	from	from	ADP
app01-10633	103	9	previously	previously	ADV
app01-10633	103	10	conducted	conduct	VERB
app01-10633	103	11	theses	thesis	NOUN
app01-10633	103	12	and	and	CCONJ
app01-10633	103	13	one	one	NUM
app01-10633	103	14	related	relate	VERB
app01-10633	103	15	study	study	NOUN
app01-10633	103	16	,	,	PUNCT
app01-10633	103	17	creating	create	VERB
app01-10633	103	18	a	a	DET
app01-10633	103	19	new	new	ADJ
app01-10633	103	20	dataset	dataset	NOUN
app01-10633	103	21	to	to	PART
app01-10633	103	22	explore	explore	VERB
app01-10633	103	23	the	the	DET
app01-10633	103	24	impact	impact	NOUN
app01-10633	103	25	of	of	ADP
app01-10633	103	26	roadside	roadside	ADJ
app01-10633	103	27	environments	environment	NOUN
app01-10633	103	28	on	on	ADP
app01-10633	103	29	speed	speed	NOUN
app01-10633	103	30	perception	perception	NOUN
app01-10633	103	31	.	.	PUNCT
app01-10633	104	1	although	although	SCONJ
app01-10633	104	2	the	the	DET
app01-10633	104	3	original	original	ADJ
app01-10633	104	4	research	research	NOUN
app01-10633	104	5	was	be	AUX
app01-10633	104	6	not	not	PART
app01-10633	104	7	focused	focus	VERB
app01-10633	104	8	on	on	ADP
app01-10633	104	9	this	this	DET
app01-10633	104	10	specific	specific	ADJ
app01-10633	104	11	area	area	NOUN
app01-10633	104	12	,	,	PUNCT
app01-10633	104	13	the	the	DET
app01-10633	104	14	existing	exist	VERB
app01-10633	104	15	data	datum	NOUN
app01-10633	104	16	has	have	AUX
app01-10633	104	17	been	be	AUX
app01-10633	104	18	reanalyzed	reanalyze	VERB
app01-10633	104	19	using	use	VERB
app01-10633	104	20	new	new	ADJ
app01-10633	104	21	criteria	criterion	NOUN
app01-10633	104	22	designed	design	VERB
app01-10633	104	23	to	to	PART
app01-10633	104	24	assess	assess	VERB
app01-10633	104	25	how	how	SCONJ
app01-10633	104	26	different	different	ADJ
app01-10633	104	27	surroundings	surrounding	NOUN
app01-10633	104	28	influence	influence	VERB
app01-10633	104	29	the	the	DET
app01-10633	104	30	accuracy	accuracy	NOUN
app01-10633	104	31	of	of	ADP
app01-10633	104	32	speed	speed	NOUN
app01-10633	104	33	estimates	estimate	NOUN
app01-10633	104	34	.	.	PUNCT
app01-10633	105	1	the	the	DET
app01-10633	105	2	new	new	ADJ
app01-10633	105	3	criteria	criterion	NOUN
app01-10633	105	4	are	be	AUX
app01-10633	105	5	based	base	VERB
app01-10633	105	6	on	on	ADP
app01-10633	105	7	the	the	DET
app01-10633	105	8	proximity	proximity	NOUN
app01-10633	105	9	of	of	ADP
app01-10633	105	10	roadside	roadside	NOUN
app01-10633	105	11	features	feature	NOUN
app01-10633	105	12	,	,	PUNCT
app01-10633	105	13	which	which	PRON
app01-10633	105	14	were	be	AUX
app01-10633	105	15	divided	divide	VERB
app01-10633	105	16	into	into	ADP
app01-10633	105	17	several	several	ADJ
app01-10633	105	18	categories	category	NOUN
app01-10633	105	19	.	.	PUNCT
app01-10633	106	1	these	these	PRON
app01-10633	106	2	include	include	VERB
app01-10633	106	3	the	the	DET
app01-10633	106	4	area	area	NOUN
app01-10633	106	5	directly	directly	ADV
app01-10633	106	6	adjacent	adjacent	ADJ
app01-10633	106	7	to	to	ADP
app01-10633	106	8	the	the	DET
app01-10633	106	9	road	road	NOUN
app01-10633	106	10	,	,	PUNCT
app01-10633	106	11	defined	define	VERB
app01-10633	106	12	as	as	ADP
app01-10633	106	13	within	within	ADP
app01-10633	106	14	1	1	NUM
app01-10633	106	15	meter	meter	NOUN
app01-10633	106	16	of	of	ADP
app01-10633	106	17	the	the	DET
app01-10633	106	18	road	road	NOUN
app01-10633	106	19	’s	’s	PART
app01-10633	106	20	edge	edge	NOUN
app01-10633	106	21	(	(	PUNCT
app01-10633	106	22	“	"	PUNCT
app01-10633	106	23	surroundings	surrounding	NOUN
app01-10633	106	24	at	at	ADP
app01-10633	106	25	1	1	NUM
app01-10633	106	26	m	m	NOUN
app01-10633	106	27	”	"	PUNCT
app01-10633	106	28	)	)	PUNCT
app01-10633	106	29	,	,	PUNCT
app01-10633	106	30	and	and	CCONJ
app01-10633	106	31	the	the	DET
app01-10633	106	32	immediate	immediate	ADJ
app01-10633	106	33	surroundings	surrounding	NOUN
app01-10633	106	34	,	,	PUNCT
app01-10633	106	35	which	which	PRON
app01-10633	106	36	extend	extend	VERB
app01-10633	106	37	up	up	ADP
app01-10633	106	38	to	to	PART
app01-10633	106	39	5	5	NUM
app01-10633	106	40	meters	meter	NOUN
app01-10633	106	41	from	from	ADP
app01-10633	106	42	the	the	DET
app01-10633	106	43	road	road	NOUN
app01-10633	106	44	(	(	PUNCT
app01-10633	106	45	“	"	PUNCT
app01-10633	106	46	surroundings	surrounding	NOUN
app01-10633	106	47	at	at	ADP
app01-10633	106	48	5	5	NUM
app01-10633	106	49	m	m	NOUN
app01-10633	106	50	”	"	PUNCT
app01-10633	106	51	)	)	PUNCT
app01-10633	106	52	.	.	PUNCT
app01-10633	107	1	a	a	DET
app01-10633	107	2	broader	broad	ADJ
app01-10633	107	3	category	category	NOUN
app01-10633	107	4	considers	consider	VERB
app01-10633	107	5	the	the	DET
app01-10633	107	6	wider	wide	ADJ
app01-10633	107	7	surroundings	surrounding	NOUN
app01-10633	107	8	beyond	beyond	ADP
app01-10633	107	9	5	5	NUM
app01-10633	107	10	meters	meter	NOUN
app01-10633	107	11	and	and	CCONJ
app01-10633	107	12	approximately	approximately	ADV
app01-10633	107	13	up	up	ADP
app01-10633	107	14	to	to	PART
app01-10633	107	15	15	15	NUM
app01-10633	107	16	meters	meter	NOUN
app01-10633	107	17	(	(	PUNCT
app01-10633	107	18	“	"	PUNCT
app01-10633	107	19	surroundings	surrounding	NOUN
app01-10633	107	20	beyond	beyond	ADP
app01-10633	107	21	5	5	NUM
app01-10633	107	22	m	m	NOUN
app01-10633	107	23	”	"	PUNCT
app01-10633	107	24	)	)	PUNCT
app01-10633	107	25	.	.	PUNCT
app01-10633	108	1	in	in	ADP
app01-10633	108	2	addition	addition	NOUN
app01-10633	108	3	to	to	ADP
app01-10633	108	4	these	these	DET
app01-10633	108	5	proximity	proximity	NOUN
app01-10633	108	6	-	-	PUNCT
app01-10633	108	7	based	base	VERB
app01-10633	108	8	factors	factor	NOUN
app01-10633	108	9	,	,	PUNCT
app01-10633	108	10	the	the	DET
app01-10633	108	11	study	study	NOUN
app01-10633	108	12	also	also	ADV
app01-10633	108	13	evaluates	evaluate	VERB
app01-10633	108	14	the	the	DET
app01-10633	108	15	overall	overall	ADJ
app01-10633	108	16	location	location	NOUN
app01-10633	108	17	of	of	ADP
app01-10633	108	18	the	the	DET
app01-10633	108	19	landscape	landscape	NOUN
app01-10633	108	20	,	,	PUNCT
app01-10633	108	21	such	such	ADJ
app01-10633	108	22	as	as	ADP
app01-10633	108	23	whether	whether	SCONJ
app01-10633	108	24	the	the	DET
app01-10633	108	25	road	road	NOUN
app01-10633	108	26	is	be	AUX
app01-10633	108	27	situated	situate	VERB
app01-10633	108	28	in	in	ADP
app01-10633	108	29	an	an	DET
app01-10633	108	30	urban	urban	ADJ
app01-10633	108	31	area	area	NOUN
app01-10633	108	32	,	,	PUNCT
app01-10633	108	33	rural	rural	ADJ
app01-10633	108	34	environment	environment	NOUN
app01-10633	108	35	,	,	PUNCT
app01-10633	108	36	or	or	CCONJ
app01-10633	108	37	near	near	ADP
app01-10633	108	38	forested	forest	VERB
app01-10633	108	39	regions	region	NOUN
app01-10633	108	40	(	(	PUNCT
app01-10633	108	41	“	"	PUNCT
app01-10633	108	42	landscape	landscape	NOUN
app01-10633	108	43	”	"	PUNCT
app01-10633	108	44	)	)	PUNCT
app01-10633	108	45	.	.	PUNCT
app01-10633	109	1	by	by	ADP
app01-10633	109	2	applying	apply	VERB
app01-10633	109	3	these	these	DET
app01-10633	109	4	criteria	criterion	NOUN
app01-10633	109	5	to	to	ADP
app01-10633	109	6	the	the	DET
app01-10633	109	7	dataset	dataset	NOUN
app01-10633	109	8	,	,	PUNCT
app01-10633	109	9	the	the	DET
app01-10633	109	10	study	study	NOUN
app01-10633	109	11	aims	aim	VERB
app01-10633	109	12	to	to	PART
app01-10633	109	13	analyze	analyze	VERB
app01-10633	109	14	how	how	SCONJ
app01-10633	109	15	the	the	DET
app01-10633	109	16	presence	presence	NOUN
app01-10633	109	17	of	of	ADP
app01-10633	109	18	nearby	nearby	ADJ
app01-10633	109	19	objects	object	NOUN
app01-10633	109	20	,	,	PUNCT
app01-10633	109	21	open	open	ADJ
app01-10633	109	22	spaces	space	NOUN
app01-10633	109	23	,	,	PUNCT
app01-10633	109	24	and	and	CCONJ
app01-10633	109	25	various	various	ADJ
app01-10633	109	26	types	type	NOUN
app01-10633	109	27	of	of	ADP
app01-10633	109	28	development	development	NOUN
app01-10633	109	29	influence	influence	NOUN
app01-10633	109	30	drivers	driver	NOUN
app01-10633	109	31	’	'	PUNCT
app01-10633	109	32	and	and	CCONJ
app01-10633	109	33	witnesses	witness	NOUN
app01-10633	109	34	’	'	PUNCT
app01-10633	109	35	ability	ability	NOUN
app01-10633	109	36	to	to	PART
app01-10633	109	37	estimate	estimate	VERB
app01-10633	109	38	vehicle	vehicle	NOUN
app01-10633	109	39	speeds	speed	NOUN
app01-10633	109	40	accurately	accurately	ADV
app01-10633	109	41	.	.	PUNCT
app01-10633	110	1	table	table	NOUN
app01-10633	110	2	1	1	NUM
app01-10633	110	3	shows	show	VERB
app01-10633	110	4	individual	individual	ADJ
app01-10633	110	5	categories	category	NOUN
app01-10633	110	6	that	that	PRON
app01-10633	110	7	were	be	AUX
app01-10633	110	8	identified	identify	VERB
app01-10633	110	9	within	within	ADP
app01-10633	110	10	the	the	DET
app01-10633	110	11	defined	define	VERB
app01-10633	110	12	variables	variable	NOUN
app01-10633	110	13	.	.	PUNCT
app01-10633	111	1	the	the	DET
app01-10633	111	2	mann	mann	PROPN
app01-10633	111	3	-	-	PUNCT
app01-10633	111	4	whitney	whitney	PROPN
app01-10633	111	5	u	u	PROPN
app01-10633	111	6	test	test	NOUN
app01-10633	111	7	was	be	AUX
app01-10633	111	8	used	use	VERB
app01-10633	111	9	to	to	PART
app01-10633	111	10	evaluate	evaluate	VERB
app01-10633	111	11	the	the	DET
app01-10633	111	12	differences	difference	NOUN
app01-10633	111	13	between	between	ADP
app01-10633	111	14	two	two	NUM
app01-10633	111	15	independent	independent	ADJ
app01-10633	111	16	groups	group	NOUN
app01-10633	111	17	.	.	PUNCT
app01-10633	112	1	the	the	DET
app01-10633	112	2	pvalue	pvalue	NOUN
app01-10633	112	3	(	(	PUNCT
app01-10633	112	4	also	also	ADV
app01-10633	112	5	referred	refer	VERB
app01-10633	112	6	to	to	ADP
app01-10633	112	7	as	as	ADP
app01-10633	112	8	significance	significance	NOUN
app01-10633	112	9	or	or	CCONJ
app01-10633	112	10	simply	simply	ADV
app01-10633	112	11	p	p	X
app01-10633	112	12	)	)	PUNCT
app01-10633	112	13	was	be	AUX
app01-10633	112	14	calculated	calculate	VERB
app01-10633	112	15	for	for	ADP
app01-10633	112	16	each	each	DET
app01-10633	112	17	factor	factor	NOUN
app01-10633	112	18	,	,	PUNCT
app01-10633	112	19	which	which	PRON
app01-10633	112	20	is	be	AUX
app01-10633	112	21	a	a	DET
app01-10633	112	22	numerical	numerical	ADJ
app01-10633	112	23	value	value	NOUN
app01-10633	112	24	used	use	VERB
app01-10633	112	25	in	in	ADP
app01-10633	112	26	statistical	statistical	ADJ
app01-10633	112	27	hypothesis	hypothesis	NOUN
app01-10633	112	28	testing	testing	NOUN
app01-10633	112	29	.	.	PUNCT
app01-10633	113	1	a	a	DET
app01-10633	113	2	significance	significance	NOUN
app01-10633	113	3	level	level	NOUN
app01-10633	113	4	(	(	PUNCT
app01-10633	113	5	95	95	NUM
app01-10633	113	6	%	%	NOUN
app01-10633	113	7	)	)	PUNCT
app01-10633	113	8	was	be	AUX
app01-10633	113	9	established	establish	VERB
app01-10633	113	10	,	,	PUNCT
app01-10633	113	11	after	after	ADP
app01-10633	113	12	which	which	PRON
app01-10633	113	13	the	the	DET
app01-10633	113	14	p	p	NOUN
app01-10633	113	15	-	-	PUNCT
app01-10633	113	16	value	value	NOUN
app01-10633	113	17	was	be	AUX
app01-10633	113	18	computed	compute	VERB
app01-10633	113	19	and	and	CCONJ
app01-10633	113	20	compared	compare	VERB
app01-10633	113	21	with	with	ADP
app01-10633	113	22	the	the	DET
app01-10633	113	23	significance	significance	NOUN
app01-10633	113	24	level	level	NOUN
app01-10633	113	25	.	.	PUNCT
app01-10633	114	1	if	if	SCONJ
app01-10633	114	2	the	the	DET
app01-10633	114	3	calculated	calculated	ADJ
app01-10633	114	4	p	p	NOUN
app01-10633	114	5	-	-	PUNCT
app01-10633	114	6	value	value	NOUN
app01-10633	114	7	was	be	AUX
app01-10633	114	8	less	less	ADJ
app01-10633	114	9	than	than	ADP
app01-10633	114	10	0.05	0.05	NUM
app01-10633	114	11	,	,	PUNCT
app01-10633	114	12	the	the	DET
app01-10633	114	13	null	null	ADJ
app01-10633	114	14	hypothesis	hypothesis	NOUN
app01-10633	114	15	(	(	PUNCT
app01-10633	114	16	that	that	SCONJ
app01-10633	114	17	the	the	DET
app01-10633	114	18	examined	examine	VERB
app01-10633	114	19	factor	factor	NOUN
app01-10633	114	20	affects	affect	VERB
app01-10633	114	21	speed	speed	NOUN
app01-10633	114	22	estimates	estimate	NOUN
app01-10633	114	23	)	)	PUNCT
app01-10633	114	24	was	be	AUX
app01-10633	114	25	considered	consider	VERB
app01-10633	114	26	credible	credible	ADJ
app01-10633	114	27	.	.	PUNCT
app01-10633	115	1	118	118	NUM
app01-10633	115	2	vol	vol	NOUN
app01-10633	115	3	.	.	PUNCT
app01-10633	116	1	52/2025	52/2025	NUM
app01-10633	116	2	the	the	DET
app01-10633	116	3	effect	effect	NOUN
app01-10633	116	4	of	of	ADP
app01-10633	116	5	roadside	roadside	NOUN
app01-10633	116	6	on	on	ADP
app01-10633	116	7	speed	speed	NOUN
app01-10633	116	8	perception	perception	NOUN
app01-10633	116	9	variable	variable	ADJ
app01-10633	116	10	category	category	NOUN
app01-10633	116	11	surroundings	surrounding	VERB
app01-10633	116	12	at	at	ADP
app01-10633	116	13	1	1	NUM
app01-10633	116	14	m	m	NOUN
app01-10633	116	15	flat	flat	ADJ
app01-10633	116	16	area	area	NOUN
app01-10633	116	17	ditch	ditch	NOUN
app01-10633	116	18	guardrails	guardrail	NOUN
app01-10633	116	19	uphill	uphill	ADJ
app01-10633	116	20	slope	slope	NOUN
app01-10633	116	21	downhill	downhill	ADV
app01-10633	116	22	slope	slope	VERB
app01-10633	116	23	surroundings	surrounding	NOUN
app01-10633	116	24	at	at	ADP
app01-10633	116	25	5	5	NUM
app01-10633	116	26	m	m	PROPN
app01-10633	116	27	flat	flat	ADJ
app01-10633	116	28	area	area	NOUN
app01-10633	116	29	trees	tree	NOUN
app01-10633	116	30	fence	fence	NOUN
app01-10633	116	31	buildings	building	NOUN
app01-10633	116	32	uphill	uphill	ADJ
app01-10633	116	33	slope	slope	NOUN
app01-10633	117	1	downhill	downhill	ADV
app01-10633	117	2	slope	slope	VERB
app01-10633	117	3	surroundings	surrounding	NOUN
app01-10633	117	4	beyond	beyond	ADP
app01-10633	117	5	5	5	NUM
app01-10633	117	6	m	m	PROPN
app01-10633	117	7	flat	flat	ADJ
app01-10633	117	8	area	area	NOUN
app01-10633	117	9	trees	tree	NOUN
app01-10633	117	10	buildings	building	NOUN
app01-10633	117	11	landscape	landscape	VERB
app01-10633	117	12	urban	urban	ADJ
app01-10633	117	13	area	area	PROPN
app01-10633	117	14	industrial	industrial	PROPN
app01-10633	117	15	area	area	PROPN
app01-10633	117	16	forest	forest	NOUN
app01-10633	117	17	field	field	NOUN
app01-10633	117	18	table	table	NOUN
app01-10633	117	19	1	1	NUM
app01-10633	117	20	.	.	PUNCT
app01-10633	118	1	variables	variable	NOUN
app01-10633	118	2	and	and	CCONJ
app01-10633	118	3	their	their	PRON
app01-10633	118	4	categories	category	NOUN
app01-10633	118	5	.	.	PUNCT
app01-10633	119	1	figure	figure	NOUN
app01-10633	119	2	1	1	NUM
app01-10633	119	3	.	.	PUNCT
app01-10633	119	4	deviation	deviation	NOUN
app01-10633	119	5	distribution	distribution	NOUN
app01-10633	119	6	by	by	ADP
app01-10633	119	7	“	"	PUNCT
app01-10633	119	8	surroundings	surrounding	NOUN
app01-10633	119	9	at	at	ADP
app01-10633	119	10	1	1	NUM
app01-10633	119	11	m	m	NOUN
app01-10633	119	12	”	"	PUNCT
app01-10633	119	13	.	.	PUNCT
app01-10633	120	1	3	3	X
app01-10633	120	2	.	.	NOUN
app01-10633	120	3	results	result	NOUN
app01-10633	120	4	in	in	ADP
app01-10633	120	5	the	the	DET
app01-10633	120	6	variable	variable	NOUN
app01-10633	120	7	“	"	PUNCT
app01-10633	120	8	surroundings	surrounding	NOUN
app01-10633	120	9	at	at	ADP
app01-10633	120	10	1	1	NUM
app01-10633	120	11	m	m	NOUN
app01-10633	120	12	”	"	PUNCT
app01-10633	120	13	,	,	PUNCT
app01-10633	120	14	significant	significant	ADJ
app01-10633	120	15	differences	difference	NOUN
app01-10633	120	16	were	be	AUX
app01-10633	120	17	found	find	VERB
app01-10633	120	18	between	between	ADP
app01-10633	120	19	several	several	ADJ
app01-10633	120	20	categories	category	NOUN
app01-10633	120	21	.	.	PUNCT
app01-10633	121	1	“	"	PUNCT
app01-10633	121	2	flat	flat	ADJ
app01-10633	121	3	area	area	NOUN
app01-10633	121	4	”	"	PUNCT
app01-10633	121	5	has	have	VERB
app01-10633	121	6	a	a	DET
app01-10633	121	7	positive	positive	ADJ
app01-10633	121	8	effect	effect	NOUN
app01-10633	121	9	on	on	ADP
app01-10633	121	10	the	the	DET
app01-10633	121	11	deviation	deviation	NOUN
app01-10633	121	12	,	,	PUNCT
app01-10633	121	13	meaning	mean	VERB
app01-10633	121	14	the	the	DET
app01-10633	121	15	estimated	estimate	VERB
app01-10633	121	16	speed	speed	NOUN
app01-10633	121	17	is	be	AUX
app01-10633	121	18	higher	high	ADJ
app01-10633	121	19	than	than	ADP
app01-10633	121	20	the	the	DET
app01-10633	121	21	actual	actual	ADJ
app01-10633	121	22	speed	speed	NOUN
app01-10633	121	23	,	,	PUNCT
app01-10633	121	24	while	while	SCONJ
app01-10633	121	25	“	"	PUNCT
app01-10633	121	26	ditch	ditch	NOUN
app01-10633	121	27	”	"	PUNCT
app01-10633	121	28	also	also	ADV
app01-10633	121	29	has	have	VERB
app01-10633	121	30	a	a	DET
app01-10633	121	31	positive	positive	ADJ
app01-10633	121	32	but	but	CCONJ
app01-10633	121	33	smaller	small	ADJ
app01-10633	121	34	effect	effect	NOUN
app01-10633	121	35	.	.	PUNCT
app01-10633	122	1	a	a	DET
app01-10633	122	2	significant	significant	ADJ
app01-10633	122	3	difference	difference	NOUN
app01-10633	122	4	was	be	AUX
app01-10633	122	5	found	find	VERB
app01-10633	122	6	between	between	ADP
app01-10633	122	7	“	"	PUNCT
app01-10633	122	8	flat	flat	ADJ
app01-10633	122	9	area	area	NOUN
app01-10633	122	10	”	"	PUNCT
app01-10633	122	11	and	and	CCONJ
app01-10633	122	12	“	"	PUNCT
app01-10633	122	13	ditch	ditch	NOUN
app01-10633	122	14	”	"	PUNCT
app01-10633	122	15	(	(	PUNCT
app01-10633	122	16	p	p	NOUN
app01-10633	122	17	-	-	PUNCT
app01-10633	122	18	value	value	NOUN
app01-10633	122	19	<	<	NOUN
app01-10633	122	20	0.05	0.05	NUM
app01-10633	122	21	)	)	PUNCT
app01-10633	122	22	,	,	PUNCT
app01-10633	122	23	with	with	ADP
app01-10633	122	24	the	the	DET
app01-10633	122	25	flat	flat	ADJ
app01-10633	122	26	area	area	NOUN
app01-10633	122	27	causing	cause	VERB
app01-10633	122	28	a	a	DET
app01-10633	122	29	larger	large	ADJ
app01-10633	122	30	deviation	deviation	NOUN
app01-10633	122	31	.	.	PUNCT
app01-10633	123	1	similarly	similarly	ADV
app01-10633	123	2	,	,	PUNCT
app01-10633	123	3	“	"	PUNCT
app01-10633	123	4	flat	flat	ADJ
app01-10633	123	5	area	area	NOUN
app01-10633	123	6	”	"	PUNCT
app01-10633	123	7	increases	increase	VERB
app01-10633	123	8	the	the	DET
app01-10633	123	9	deviation	deviation	NOUN
app01-10633	123	10	compared	compare	VERB
app01-10633	123	11	to	to	ADP
app01-10633	123	12	“	"	PUNCT
app01-10633	123	13	guardrails	guardrail	NOUN
app01-10633	123	14	”	"	PUNCT
app01-10633	123	15	(	(	PUNCT
app01-10633	123	16	p	p	NOUN
app01-10633	123	17	-	-	PUNCT
app01-10633	123	18	value	value	NOUN
app01-10633	123	19	<	<	NOUN
app01-10633	123	20	0.05	0.05	NUM
app01-10633	123	21	)	)	PUNCT
app01-10633	123	22	,	,	PUNCT
app01-10633	123	23	where	where	SCONJ
app01-10633	123	24	guardrails	guardrail	NOUN
app01-10633	123	25	have	have	AUX
app01-10633	123	26	a	a	DET
app01-10633	123	27	negative	negative	ADJ
app01-10633	123	28	effect	effect	NOUN
app01-10633	123	29	on	on	ADP
app01-10633	123	30	the	the	DET
app01-10633	123	31	deviation	deviation	NOUN
app01-10633	123	32	,	,	PUNCT
app01-10633	123	33	meaning	mean	VERB
app01-10633	123	34	the	the	DET
app01-10633	123	35	actual	actual	ADJ
app01-10633	123	36	speed	speed	NOUN
app01-10633	123	37	is	be	AUX
app01-10633	123	38	closer	close	ADJ
app01-10633	123	39	to	to	ADP
app01-10633	123	40	the	the	DET
app01-10633	123	41	estimate	estimate	NOUN
app01-10633	123	42	.	.	PUNCT
app01-10633	124	1	in	in	ADP
app01-10633	124	2	the	the	DET
app01-10633	124	3	comparison	comparison	NOUN
app01-10633	124	4	between	between	ADP
app01-10633	124	5	“	"	PUNCT
app01-10633	124	6	flat	flat	ADJ
app01-10633	124	7	area	area	NOUN
app01-10633	124	8	”	"	PUNCT
app01-10633	124	9	and	and	CCONJ
app01-10633	124	10	“	"	PUNCT
app01-10633	124	11	uphill	uphill	ADJ
app01-10633	124	12	slope	slope	NOUN
app01-10633	124	13	”	"	PUNCT
app01-10633	124	14	(	(	PUNCT
app01-10633	124	15	p	p	NOUN
app01-10633	124	16	-	-	PUNCT
app01-10633	124	17	value	value	NOUN
app01-10633	124	18	<	<	NOUN
app01-10633	124	19	0.05	0.05	NUM
app01-10633	124	20	)	)	PUNCT
app01-10633	124	21	,	,	PUNCT
app01-10633	124	22	the	the	DET
app01-10633	124	23	flat	flat	ADJ
app01-10633	124	24	area	area	NOUN
app01-10633	124	25	has	have	VERB
app01-10633	124	26	a	a	DET
app01-10633	124	27	positive	positive	ADJ
app01-10633	124	28	effect	effect	NOUN
app01-10633	124	29	on	on	ADP
app01-10633	124	30	the	the	DET
app01-10633	124	31	deviation	deviation	NOUN
app01-10633	124	32	.	.	PUNCT
app01-10633	125	1	in	in	ADP
app01-10633	125	2	contrast	contrast	NOUN
app01-10633	125	3	,	,	PUNCT
app01-10633	125	4	the	the	DET
app01-10633	125	5	uphill	uphill	ADJ
app01-10633	125	6	slope	slope	NOUN
app01-10633	125	7	has	have	VERB
app01-10633	125	8	the	the	DET
app01-10633	125	9	opposite	opposite	ADJ
app01-10633	125	10	effect	effect	NOUN
app01-10633	125	11	–	–	PUNCT
app01-10633	125	12	reducing	reduce	VERB
app01-10633	125	13	the	the	DET
app01-10633	125	14	deviation	deviation	NOUN
app01-10633	125	15	.	.	PUNCT
app01-10633	126	1	however	however	ADV
app01-10633	126	2	,	,	PUNCT
app01-10633	126	3	the	the	DET
app01-10633	126	4	difference	difference	NOUN
app01-10633	126	5	between	between	ADP
app01-10633	126	6	“	"	PUNCT
app01-10633	126	7	flat	flat	ADJ
app01-10633	126	8	area	area	NOUN
app01-10633	126	9	”	"	PUNCT
app01-10633	126	10	and	and	CCONJ
app01-10633	126	11	“	"	PUNCT
app01-10633	126	12	downhill	downhill	ADV
app01-10633	126	13	slope	slope	NOUN
app01-10633	126	14	”	"	PUNCT
app01-10633	126	15	(	(	PUNCT
app01-10633	126	16	p	p	NOUN
app01-10633	126	17	-	-	PUNCT
app01-10633	126	18	value	value	NOUN
app01-10633	126	19	=	=	NOUN
app01-10633	126	20	0.395	0.395	NUM
app01-10633	126	21	)	)	PUNCT
app01-10633	126	22	was	be	AUX
app01-10633	126	23	not	not	PART
app01-10633	126	24	statistically	statistically	ADV
app01-10633	126	25	significant	significant	ADJ
app01-10633	126	26	.	.	PUNCT
app01-10633	127	1	additionally	additionally	ADV
app01-10633	127	2	,	,	PUNCT
app01-10633	127	3	the	the	DET
app01-10633	127	4	difference	difference	NOUN
app01-10633	127	5	between	between	ADP
app01-10633	127	6	“	"	PUNCT
app01-10633	127	7	ditch	ditch	NOUN
app01-10633	127	8	”	"	PUNCT
app01-10633	127	9	and	and	CCONJ
app01-10633	127	10	“	"	PUNCT
app01-10633	127	11	guardrails	guardrail	NOUN
app01-10633	127	12	”	"	PUNCT
app01-10633	127	13	(	(	PUNCT
app01-10633	127	14	p	p	NOUN
app01-10633	127	15	-	-	PUNCT
app01-10633	127	16	value	value	NOUN
app01-10633	127	17	=	=	NOUN
app01-10633	127	18	0.206	0.206	NUM
app01-10633	127	19	)	)	PUNCT
app01-10633	127	20	was	be	AUX
app01-10633	127	21	also	also	ADV
app01-10633	127	22	not	not	PART
app01-10633	127	23	significant	significant	ADJ
app01-10633	127	24	.	.	PUNCT
app01-10633	128	1	figure	figure	NOUN
app01-10633	128	2	1	1	NUM
app01-10633	128	3	shows	show	VERB
app01-10633	128	4	the	the	DET
app01-10633	128	5	deviation	deviation	NOUN
app01-10633	128	6	distribution	distribution	NOUN
app01-10633	128	7	of	of	ADP
app01-10633	128	8	each	each	DET
app01-10633	128	9	category	category	NOUN
app01-10633	128	10	.	.	PUNCT
app01-10633	129	1	in	in	ADP
app01-10633	129	2	the	the	DET
app01-10633	129	3	variable	variable	ADJ
app01-10633	129	4	“	"	PUNCT
app01-10633	129	5	surroundings	surrounding	NOUN
app01-10633	129	6	at	at	ADP
app01-10633	129	7	5	5	NUM
app01-10633	129	8	m	m	NOUN
app01-10633	129	9	”	"	PUNCT
app01-10633	129	10	,	,	PUNCT
app01-10633	129	11	significant	significant	ADJ
app01-10633	129	12	differences	difference	NOUN
app01-10633	129	13	were	be	AUX
app01-10633	129	14	found	find	VERB
app01-10633	129	15	between	between	ADP
app01-10633	129	16	categories	category	NOUN
app01-10633	129	17	.	.	PUNCT
app01-10633	130	1	“	"	PUNCT
app01-10633	130	2	flat	flat	ADJ
app01-10633	130	3	area	area	NOUN
app01-10633	130	4	”	"	PUNCT
app01-10633	130	5	increases	increase	VERB
app01-10633	130	6	the	the	DET
app01-10633	130	7	deviation	deviation	NOUN
app01-10633	130	8	compared	compare	VERB
app01-10633	130	9	to	to	ADP
app01-10633	130	10	“	"	PUNCT
app01-10633	130	11	trees	tree	NOUN
app01-10633	130	12	”	"	PUNCT
app01-10633	130	13	(	(	PUNCT
app01-10633	130	14	p	p	NOUN
app01-10633	130	15	-	-	PUNCT
app01-10633	130	16	value	value	NOUN
app01-10633	130	17	<	<	NOUN
app01-10633	130	18	0.05	0.05	NUM
app01-10633	130	19	)	)	PUNCT
app01-10633	130	20	,	,	PUNCT
app01-10633	130	21	which	which	PRON
app01-10633	130	22	have	have	VERB
app01-10633	130	23	a	a	DET
app01-10633	130	24	stabilizing	stabilize	VERB
app01-10633	130	25	effect	effect	NOUN
app01-10633	130	26	and	and	CCONJ
app01-10633	130	27	reduce	reduce	VERB
app01-10633	130	28	the	the	DET
app01-10633	130	29	deviation	deviation	NOUN
app01-10633	130	30	.	.	PUNCT
app01-10633	131	1	“	"	PUNCT
app01-10633	131	2	flat	flat	ADJ
app01-10633	131	3	area	area	NOUN
app01-10633	131	4	”	"	PUNCT
app01-10633	131	5	also	also	ADV
app01-10633	131	6	shows	show	VERB
app01-10633	131	7	a	a	DET
app01-10633	131	8	higher	high	ADJ
app01-10633	131	9	deviation	deviation	NOUN
app01-10633	131	10	compared	compare	VERB
app01-10633	131	11	to	to	ADP
app01-10633	131	12	“	"	PUNCT
app01-10633	131	13	fence	fence	NOUN
app01-10633	131	14	”	"	PUNCT
app01-10633	131	15	(	(	PUNCT
app01-10633	131	16	p	p	NOUN
app01-10633	131	17	-	-	PUNCT
app01-10633	131	18	value	value	NOUN
app01-10633	131	19	<	<	NOUN
app01-10633	131	20	0.05	0.05	NUM
app01-10633	131	21	)	)	PUNCT
app01-10633	131	22	,	,	PUNCT
app01-10633	131	23	where	where	SCONJ
app01-10633	131	24	the	the	DET
app01-10633	131	25	fence	fence	NOUN
app01-10633	131	26	has	have	VERB
app01-10633	131	27	a	a	DET
app01-10633	131	28	slightly	slightly	ADV
app01-10633	131	29	negative	negative	ADJ
app01-10633	131	30	effect	effect	NOUN
app01-10633	131	31	and	and	CCONJ
app01-10633	131	32	reduces	reduce	VERB
app01-10633	131	33	the	the	DET
app01-10633	131	34	overestimation	overestimation	NOUN
app01-10633	131	35	of	of	ADP
app01-10633	131	36	the	the	DET
app01-10633	131	37	estimated	estimate	VERB
app01-10633	131	38	speed	speed	NOUN
app01-10633	131	39	.	.	PUNCT
app01-10633	132	1	a	a	DET
app01-10633	132	2	significant	significant	ADJ
app01-10633	132	3	difference	difference	NOUN
app01-10633	132	4	is	be	AUX
app01-10633	132	5	also	also	ADV
app01-10633	132	6	found	find	VERB
app01-10633	132	7	between	between	ADP
app01-10633	132	8	“	"	PUNCT
app01-10633	132	9	flat	flat	ADJ
app01-10633	132	10	area	area	NOUN
app01-10633	132	11	”	"	PUNCT
app01-10633	132	12	and	and	CCONJ
app01-10633	132	13	“	"	PUNCT
app01-10633	132	14	buildings	building	NOUN
app01-10633	132	15	”	"	PUNCT
app01-10633	132	16	(	(	PUNCT
app01-10633	132	17	p	p	NOUN
app01-10633	132	18	-	-	PUNCT
app01-10633	132	19	value	value	NOUN
app01-10633	132	20	<	<	NOUN
app01-10633	132	21	0.05	0.05	NUM
app01-10633	132	22	)	)	PUNCT
app01-10633	132	23	,	,	PUNCT
app01-10633	132	24	where	where	SCONJ
app01-10633	132	25	both	both	DET
app01-10633	132	26	categories	category	NOUN
app01-10633	132	27	figure	figure	VERB
app01-10633	132	28	2	2	NUM
app01-10633	132	29	.	.	PUNCT
app01-10633	132	30	deviation	deviation	NOUN
app01-10633	132	31	distribution	distribution	NOUN
app01-10633	132	32	by	by	ADP
app01-10633	132	33	“	"	PUNCT
app01-10633	132	34	surroundings	surrounding	NOUN
app01-10633	132	35	at	at	ADP
app01-10633	132	36	5	5	NUM
app01-10633	132	37	m	m	NOUN
app01-10633	132	38	”	"	PUNCT
app01-10633	132	39	.	.	PUNCT
app01-10633	133	1	increase	increase	VERB
app01-10633	133	2	the	the	DET
app01-10633	133	3	deviation	deviation	NOUN
app01-10633	133	4	,	,	PUNCT
app01-10633	133	5	but	but	CCONJ
app01-10633	133	6	buildings	building	NOUN
app01-10633	133	7	have	have	VERB
app01-10633	133	8	a	a	DET
app01-10633	133	9	stronger	strong	ADJ
app01-10633	133	10	effect	effect	NOUN
app01-10633	133	11	.	.	PUNCT
app01-10633	134	1	however	however	ADV
app01-10633	134	2	,	,	PUNCT
app01-10633	134	3	some	some	DET
app01-10633	134	4	“	"	PUNCT
app01-10633	134	5	surroundings	surrounding	NOUN
app01-10633	134	6	at	at	ADP
app01-10633	134	7	5	5	NUM
app01-10633	134	8	m	m	NOUN
app01-10633	134	9	”	"	PUNCT
app01-10633	134	10	comparisons	comparison	NOUN
app01-10633	134	11	were	be	AUX
app01-10633	134	12	insignificant	insignificant	ADJ
app01-10633	134	13	.	.	PUNCT
app01-10633	135	1	the	the	DET
app01-10633	135	2	differences	difference	NOUN
app01-10633	135	3	between	between	ADP
app01-10633	135	4	“	"	PUNCT
app01-10633	135	5	flat	flat	ADJ
app01-10633	135	6	area	area	NOUN
app01-10633	135	7	”	"	PUNCT
app01-10633	135	8	and	and	CCONJ
app01-10633	135	9	“	"	PUNCT
app01-10633	135	10	downhill	downhill	ADV
app01-10633	135	11	slope	slope	NOUN
app01-10633	135	12	”	"	PUNCT
app01-10633	135	13	(	(	PUNCT
app01-10633	135	14	p	p	NOUN
app01-10633	135	15	-	-	PUNCT
app01-10633	135	16	value	value	NOUN
app01-10633	135	17	=	=	NOUN
app01-10633	135	18	0.605	0.605	NUM
app01-10633	135	19	)	)	PUNCT
app01-10633	135	20	,	,	PUNCT
app01-10633	135	21	“	"	PUNCT
app01-10633	135	22	trees	tree	NOUN
app01-10633	135	23	”	"	PUNCT
app01-10633	135	24	vs.	vs.	X
app01-10633	135	25	“	"	PUNCT
app01-10633	135	26	downhill	downhill	ADV
app01-10633	135	27	slope	slope	NOUN
app01-10633	135	28	”	"	PUNCT
app01-10633	135	29	(	(	PUNCT
app01-10633	135	30	p	p	NOUN
app01-10633	135	31	-	-	PUNCT
app01-10633	135	32	value	value	NOUN
app01-10633	135	33	=	=	NOUN
app01-10633	135	34	0.222	0.222	NUM
app01-10633	135	35	)	)	PUNCT
app01-10633	135	36	,	,	PUNCT
app01-10633	135	37	and	and	CCONJ
app01-10633	135	38	“	"	PUNCT
app01-10633	135	39	trees	tree	NOUN
app01-10633	135	40	”	"	PUNCT
app01-10633	135	41	vs.	vs.	ADP
app01-10633	135	42	“	"	PUNCT
app01-10633	135	43	uphill	uphill	ADJ
app01-10633	135	44	slope	slope	NOUN
app01-10633	135	45	”	"	PUNCT
app01-10633	135	46	(	(	PUNCT
app01-10633	135	47	p	p	NOUN
app01-10633	135	48	-	-	PUNCT
app01-10633	135	49	value	value	NOUN
app01-10633	135	50	=	=	NOUN
app01-10633	135	51	0.187	0.187	NUM
app01-10633	135	52	)	)	PUNCT
app01-10633	135	53	were	be	AUX
app01-10633	135	54	all	all	ADV
app01-10633	135	55	not	not	PART
app01-10633	135	56	statistically	statistically	ADV
app01-10633	135	57	significant	significant	ADJ
app01-10633	135	58	.	.	PUNCT
app01-10633	136	1	figure	figure	NOUN
app01-10633	136	2	2	2	NUM
app01-10633	136	3	shows	show	VERB
app01-10633	136	4	the	the	DET
app01-10633	136	5	deviation	deviation	NOUN
app01-10633	136	6	distribution	distribution	NOUN
app01-10633	136	7	of	of	ADP
app01-10633	136	8	each	each	DET
app01-10633	136	9	category	category	NOUN
app01-10633	136	10	.	.	PUNCT
app01-10633	137	1	in	in	ADP
app01-10633	137	2	the	the	DET
app01-10633	137	3	variable	variable	ADJ
app01-10633	137	4	“	"	PUNCT
app01-10633	137	5	surroundings	surrounding	NOUN
app01-10633	137	6	beyond	beyond	ADP
app01-10633	137	7	5	5	NUM
app01-10633	137	8	m	m	NOUN
app01-10633	137	9	”	"	PUNCT
app01-10633	137	10	,	,	PUNCT
app01-10633	137	11	significant	significant	ADJ
app01-10633	137	12	differences	difference	NOUN
app01-10633	137	13	were	be	AUX
app01-10633	137	14	found	find	VERB
app01-10633	137	15	between	between	ADP
app01-10633	137	16	categories	category	NOUN
app01-10633	137	17	.	.	PUNCT
app01-10633	138	1	“	"	PUNCT
app01-10633	138	2	flat	flat	ADJ
app01-10633	138	3	area	area	NOUN
app01-10633	138	4	”	"	PUNCT
app01-10633	138	5	increases	increase	VERB
app01-10633	138	6	the	the	DET
app01-10633	138	7	deviation	deviation	NOUN
app01-10633	138	8	compared	compare	VERB
app01-10633	138	9	to	to	ADP
app01-10633	138	10	“	"	PUNCT
app01-10633	138	11	trees	tree	NOUN
app01-10633	138	12	”	"	PUNCT
app01-10633	138	13	(	(	PUNCT
app01-10633	138	14	pvalue	pvalue	VERB
app01-10633	138	15	<	<	NOUN
app01-10633	138	16	0.05	0.05	NUM
app01-10633	138	17	)	)	PUNCT
app01-10633	138	18	,	,	PUNCT
app01-10633	138	19	which	which	PRON
app01-10633	138	20	have	have	VERB
app01-10633	138	21	a	a	DET
app01-10633	138	22	stabilizing	stabilize	VERB
app01-10633	138	23	effect	effect	NOUN
app01-10633	138	24	and	and	CCONJ
app01-10633	138	25	reduce	reduce	VERB
app01-10633	138	26	the	the	DET
app01-10633	138	27	deviation	deviation	NOUN
app01-10633	138	28	.	.	PUNCT
app01-10633	139	1	buildings	building	NOUN
app01-10633	139	2	increase	increase	VERB
app01-10633	139	3	the	the	DET
app01-10633	139	4	deviation	deviation	NOUN
app01-10633	139	5	more	more	ADJ
app01-10633	139	6	than	than	ADP
app01-10633	139	7	“	"	PUNCT
app01-10633	139	8	trees	tree	NOUN
app01-10633	139	9	”	"	PUNCT
app01-10633	139	10	(	(	PUNCT
app01-10633	139	11	p	p	NOUN
app01-10633	139	12	-	-	PUNCT
app01-10633	139	13	value	value	NOUN
app01-10633	139	14	<	<	NOUN
app01-10633	139	15	0.05	0.05	NUM
app01-10633	139	16	)	)	PUNCT
app01-10633	139	17	,	,	PUNCT
app01-10633	139	18	where	where	SCONJ
app01-10633	139	19	trees	tree	NOUN
app01-10633	139	20	stabilize	stabilize	VERB
app01-10633	139	21	the	the	DET
app01-10633	139	22	difference	difference	NOUN
app01-10633	139	23	between	between	ADP
app01-10633	139	24	actual	actual	ADJ
app01-10633	139	25	and	and	CCONJ
app01-10633	139	26	estimated	estimated	ADJ
app01-10633	139	27	speed	speed	NOUN
app01-10633	139	28	.	.	PUNCT
app01-10633	140	1	however	however	ADV
app01-10633	140	2	,	,	PUNCT
app01-10633	140	3	the	the	DET
app01-10633	140	4	comparison	comparison	NOUN
app01-10633	140	5	between	between	ADP
app01-10633	140	6	“	"	PUNCT
app01-10633	140	7	flat	flat	ADJ
app01-10633	140	8	area	area	NOUN
app01-10633	140	9	”	"	PUNCT
app01-10633	140	10	and	and	CCONJ
app01-10633	140	11	“	"	PUNCT
app01-10633	140	12	buildings	building	NOUN
app01-10633	140	13	”	"	PUNCT
app01-10633	140	14	(	(	PUNCT
app01-10633	140	15	p	p	NOUN
app01-10633	140	16	-	-	PUNCT
app01-10633	140	17	value	value	NOUN
app01-10633	140	18	=	=	NOUN
app01-10633	140	19	0.224	0.224	NUM
app01-10633	140	20	)	)	PUNCT
app01-10633	140	21	was	be	AUX
app01-10633	140	22	not	not	PART
app01-10633	140	23	statistically	statistically	ADV
app01-10633	140	24	significant	significant	ADJ
app01-10633	140	25	.	.	PUNCT
app01-10633	141	1	figure	figure	NOUN
app01-10633	141	2	3	3	NUM
app01-10633	141	3	shows	show	VERB
app01-10633	141	4	the	the	DET
app01-10633	141	5	deviation	deviation	NOUN
app01-10633	141	6	distribution	distribution	NOUN
app01-10633	141	7	of	of	ADP
app01-10633	141	8	each	each	DET
app01-10633	141	9	category	category	NOUN
app01-10633	141	10	.	.	PUNCT
app01-10633	142	1	in	in	ADP
app01-10633	142	2	the	the	DET
app01-10633	142	3	variable	variable	ADJ
app01-10633	142	4	“	"	PUNCT
app01-10633	142	5	landscape	landscape	NOUN
app01-10633	142	6	”	"	PUNCT
app01-10633	142	7	,	,	PUNCT
app01-10633	142	8	significant	significant	ADJ
app01-10633	142	9	differences	difference	NOUN
app01-10633	142	10	were	be	AUX
app01-10633	142	11	found	find	VERB
app01-10633	142	12	between	between	ADP
app01-10633	142	13	categories	category	NOUN
app01-10633	142	14	.	.	PUNCT
app01-10633	143	1	“	"	PUNCT
app01-10633	143	2	industrial	industrial	ADJ
app01-10633	143	3	zone	zone	NOUN
app01-10633	143	4	”	"	PUNCT
app01-10633	143	5	greatly	greatly	ADV
app01-10633	143	6	increases	increase	VERB
app01-10633	143	7	the	the	DET
app01-10633	143	8	deviation	deviation	NOUN
app01-10633	143	9	compared	compare	VERB
app01-10633	143	10	to	to	ADP
app01-10633	143	11	“	"	PUNCT
app01-10633	143	12	forest	forest	NOUN
app01-10633	143	13	”	"	PUNCT
app01-10633	143	14	(	(	PUNCT
app01-10633	143	15	p	p	NOUN
app01-10633	143	16	-	-	PUNCT
app01-10633	143	17	value	value	NOUN
app01-10633	143	18	<	<	NOUN
app01-10633	143	19	0.05	0.05	NUM
app01-10633	143	20	)	)	PUNCT
app01-10633	143	21	,	,	PUNCT
app01-10633	143	22	where	where	SCONJ
app01-10633	143	23	the	the	DET
app01-10633	143	24	forest	forest	NOUN
app01-10633	143	25	has	have	VERB
app01-10633	143	26	a	a	DET
app01-10633	143	27	stabilizing	stabilize	VERB
app01-10633	143	28	effect	effect	NOUN
app01-10633	143	29	and	and	CCONJ
app01-10633	143	30	reduces	reduce	VERB
app01-10633	143	31	the	the	DET
app01-10633	143	32	deviation	deviation	NOUN
app01-10633	143	33	.	.	PUNCT
app01-10633	144	1	field	field	NOUN
app01-10633	144	2	increases	increase	VERB
app01-10633	144	3	the	the	DET
app01-10633	144	4	deviation	deviation	NOUN
app01-10633	144	5	,	,	PUNCT
app01-10633	144	6	but	but	CCONJ
app01-10633	144	7	less	less	ADV
app01-10633	144	8	so	so	ADV
app01-10633	144	9	than	than	ADP
app01-10633	144	10	the	the	DET
app01-10633	144	11	industrial	industrial	ADJ
app01-10633	144	12	zone	zone	NOUN
app01-10633	144	13	,	,	PUNCT
app01-10633	144	14	while	while	SCONJ
app01-10633	144	15	“	"	PUNCT
app01-10633	144	16	forest	forest	NOUN
app01-10633	144	17	”	"	PUNCT
app01-10633	144	18	again	again	ADV
app01-10633	144	19	reduces	reduce	VERB
app01-10633	144	20	the	the	DET
app01-10633	144	21	deviation	deviation	NOUN
app01-10633	144	22	(	(	PUNCT
app01-10633	144	23	p	p	NOUN
app01-10633	144	24	-	-	PUNCT
app01-10633	144	25	value	value	NOUN
app01-10633	144	26	<	<	NOUN
app01-10633	144	27	0.05	0.05	NUM
app01-10633	144	28	)	)	PUNCT
app01-10633	144	29	.	.	PUNCT
app01-10633	145	1	in	in	ADP
app01-10633	145	2	the	the	DET
app01-10633	145	3	comparison	comparison	NOUN
app01-10633	145	4	between	between	ADP
app01-10633	145	5	“	"	PUNCT
app01-10633	145	6	urban	urban	ADJ
app01-10633	145	7	area	area	NOUN
app01-10633	145	8	”	"	PUNCT
app01-10633	145	9	vs.	vs.	ADP
app01-10633	145	10	“	"	PUNCT
app01-10633	145	11	forest	forest	NOUN
app01-10633	145	12	”	"	PUNCT
app01-10633	145	13	(	(	PUNCT
app01-10633	145	14	p	p	NOUN
app01-10633	145	15	-	-	PUNCT
app01-10633	145	16	value	value	NOUN
app01-10633	145	17	<	<	NOUN
app01-10633	145	18	0.05	0.05	NUM
app01-10633	145	19	)	)	PUNCT
app01-10633	145	20	,	,	PUNCT
app01-10633	145	21	the	the	DET
app01-10633	145	22	urban	urban	ADJ
app01-10633	145	23	area	area	NOUN
app01-10633	145	24	increases	increase	VERB
app01-10633	145	25	the	the	DET
app01-10633	145	26	deviation	deviation	NOUN
app01-10633	145	27	,	,	PUNCT
app01-10633	145	28	but	but	CCONJ
app01-10633	145	29	less	less	ADJ
app01-10633	145	30	than	than	ADP
app01-10633	145	31	the	the	DET
app01-10633	145	32	industrial	industrial	ADJ
app01-10633	145	33	zone	zone	NOUN
app01-10633	145	34	.	.	PUNCT
app01-10633	146	1	in	in	ADP
app01-10633	146	2	contrast	contrast	NOUN
app01-10633	146	3	,	,	PUNCT
app01-10633	146	4	the	the	DET
app01-10633	146	5	forest	forest	NOUN
app01-10633	146	6	has	have	VERB
app01-10633	146	7	a	a	DET
app01-10633	146	8	negative	negative	ADJ
app01-10633	146	9	effect	effect	NOUN
app01-10633	146	10	and	and	CCONJ
app01-10633	146	11	stabilizes	stabilize	VERB
app01-10633	146	12	the	the	DET
app01-10633	146	13	dif119	dif119	PROPN
app01-10633	146	14	martin	martin	PROPN
app01-10633	146	15	rak	rak	PROPN
app01-10633	146	16	,	,	PUNCT
app01-10633	146	17	martin	martin	PROPN
app01-10633	146	18	bilík	bilík	PROPN
app01-10633	146	19	acta	acta	PROPN
app01-10633	146	20	polytechnica	polytechnica	PROPN
app01-10633	146	21	ctu	ctu	PROPN
app01-10633	146	22	proceedings	proceeding	NOUN
app01-10633	146	23	figure	figure	VERB
app01-10633	146	24	3	3	NUM
app01-10633	146	25	.	.	PUNCT
app01-10633	146	26	deviation	deviation	NOUN
app01-10633	146	27	distribution	distribution	NOUN
app01-10633	146	28	by	by	ADP
app01-10633	146	29	“	"	PUNCT
app01-10633	146	30	surroundings	surrounding	NOUN
app01-10633	146	31	beyond	beyond	ADP
app01-10633	146	32	5	5	NUM
app01-10633	146	33	m	m	NOUN
app01-10633	146	34	”	"	PUNCT
app01-10633	146	35	.	.	PUNCT
app01-10633	147	1	figure	figure	VERB
app01-10633	147	2	4	4	NUM
app01-10633	147	3	.	.	PUNCT
app01-10633	147	4	deviation	deviation	NOUN
app01-10633	147	5	distribution	distribution	NOUN
app01-10633	147	6	by	by	ADP
app01-10633	147	7	“	"	PUNCT
app01-10633	147	8	landscape	landscape	NOUN
app01-10633	147	9	”	"	PUNCT
app01-10633	147	10	.	.	PUNCT
app01-10633	148	1	ference	ference	NOUN
app01-10633	148	2	between	between	ADP
app01-10633	148	3	actual	actual	ADJ
app01-10633	148	4	and	and	CCONJ
app01-10633	148	5	estimated	estimated	ADJ
app01-10633	148	6	speed	speed	NOUN
app01-10633	148	7	.	.	PUNCT
app01-10633	149	1	figure	figure	NOUN
app01-10633	149	2	4	4	NUM
app01-10633	149	3	shows	show	VERB
app01-10633	149	4	the	the	DET
app01-10633	149	5	deviation	deviation	NOUN
app01-10633	149	6	distribution	distribution	NOUN
app01-10633	149	7	of	of	ADP
app01-10633	149	8	each	each	DET
app01-10633	149	9	category	category	NOUN
app01-10633	149	10	.	.	PUNCT
app01-10633	150	1	4	4	X
app01-10633	150	2	.	.	X
app01-10633	150	3	discussion	discussion	NOUN
app01-10633	150	4	analyzing	analyze	VERB
app01-10633	150	5	the	the	DET
app01-10633	150	6	surroundings	surrounding	NOUN
app01-10633	150	7	at	at	ADP
app01-10633	150	8	various	various	ADJ
app01-10633	150	9	distances	distance	NOUN
app01-10633	150	10	(	(	PUNCT
app01-10633	150	11	1	1	NUM
app01-10633	150	12	m	m	NOUN
app01-10633	150	13	,	,	PUNCT
app01-10633	150	14	5	5	NUM
app01-10633	150	15	m	m	NOUN
app01-10633	150	16	,	,	PUNCT
app01-10633	150	17	beyond	beyond	ADP
app01-10633	150	18	5	5	NUM
app01-10633	150	19	m	m	NOUN
app01-10633	150	20	)	)	PUNCT
app01-10633	150	21	and	and	CCONJ
app01-10633	150	22	landscape	landscape	NOUN
app01-10633	150	23	provides	provide	VERB
app01-10633	150	24	valuable	valuable	ADJ
app01-10633	150	25	insights	insight	NOUN
app01-10633	150	26	into	into	ADP
app01-10633	150	27	how	how	SCONJ
app01-10633	150	28	different	different	ADJ
app01-10633	150	29	environments	environment	NOUN
app01-10633	150	30	influence	influence	VERB
app01-10633	150	31	human	human	ADJ
app01-10633	150	32	perception	perception	NOUN
app01-10633	150	33	of	of	ADP
app01-10633	150	34	speed	speed	NOUN
app01-10633	150	35	.	.	PUNCT
app01-10633	151	1	one	one	NUM
app01-10633	151	2	clear	clear	ADJ
app01-10633	151	3	pattern	pattern	NOUN
app01-10633	151	4	is	be	AUX
app01-10633	151	5	that	that	SCONJ
app01-10633	151	6	flat	flat	ADJ
app01-10633	151	7	areas	area	NOUN
app01-10633	151	8	tend	tend	VERB
app01-10633	151	9	to	to	PART
app01-10633	151	10	lead	lead	VERB
app01-10633	151	11	to	to	ADP
app01-10633	151	12	overestimation	overestimation	NOUN
app01-10633	151	13	of	of	ADP
app01-10633	151	14	speed	speed	NOUN
app01-10633	151	15	.	.	PUNCT
app01-10633	152	1	this	this	PRON
app01-10633	152	2	suggests	suggest	VERB
app01-10633	152	3	that	that	SCONJ
app01-10633	152	4	in	in	ADP
app01-10633	152	5	environments	environment	NOUN
app01-10633	152	6	characterized	characterize	VERB
app01-10633	152	7	by	by	ADP
app01-10633	152	8	flat	flat	ADJ
app01-10633	152	9	terrain	terrain	NOUN
app01-10633	152	10	,	,	PUNCT
app01-10633	152	11	people	people	NOUN
app01-10633	152	12	are	be	AUX
app01-10633	152	13	likely	likely	ADJ
app01-10633	152	14	to	to	PART
app01-10633	152	15	think	think	VERB
app01-10633	152	16	vehicles	vehicle	NOUN
app01-10633	152	17	are	be	AUX
app01-10633	152	18	moving	move	VERB
app01-10633	152	19	faster	fast	ADV
app01-10633	152	20	than	than	SCONJ
app01-10633	152	21	they	they	PRON
app01-10633	152	22	actually	actually	ADV
app01-10633	152	23	are	be	AUX
app01-10633	152	24	.	.	PUNCT
app01-10633	153	1	the	the	DET
app01-10633	153	2	lack	lack	NOUN
app01-10633	153	3	of	of	ADP
app01-10633	153	4	visual	visual	ADJ
app01-10633	153	5	obstacles	obstacle	NOUN
app01-10633	153	6	or	or	CCONJ
app01-10633	153	7	cues	cue	NOUN
app01-10633	153	8	,	,	PUNCT
app01-10633	153	9	such	such	ADJ
app01-10633	153	10	as	as	ADP
app01-10633	153	11	changes	change	NOUN
app01-10633	153	12	in	in	ADP
app01-10633	153	13	elevation	elevation	NOUN
app01-10633	153	14	,	,	PUNCT
app01-10633	153	15	might	might	AUX
app01-10633	153	16	contribute	contribute	VERB
app01-10633	153	17	to	to	ADP
app01-10633	153	18	this	this	DET
app01-10633	153	19	overestimation	overestimation	NOUN
app01-10633	153	20	,	,	PUNCT
app01-10633	153	21	as	as	SCONJ
app01-10633	153	22	it	it	PRON
app01-10633	153	23	may	may	AUX
app01-10633	153	24	create	create	VERB
app01-10633	153	25	a	a	DET
app01-10633	153	26	sense	sense	NOUN
app01-10633	153	27	of	of	ADP
app01-10633	153	28	openness	openness	NOUN
app01-10633	153	29	where	where	SCONJ
app01-10633	153	30	objects	object	NOUN
app01-10633	153	31	appear	appear	VERB
app01-10633	153	32	to	to	PART
app01-10633	153	33	move	move	VERB
app01-10633	153	34	faster	fast	ADV
app01-10633	153	35	.	.	PUNCT
app01-10633	154	1	on	on	ADP
app01-10633	154	2	the	the	DET
app01-10633	154	3	other	other	ADJ
app01-10633	154	4	hand	hand	NOUN
app01-10633	154	5	,	,	PUNCT
app01-10633	154	6	trees	tree	NOUN
app01-10633	154	7	consistently	consistently	ADV
app01-10633	154	8	show	show	VERB
app01-10633	154	9	a	a	DET
app01-10633	154	10	stabilizing	stabilize	VERB
app01-10633	154	11	effect	effect	NOUN
app01-10633	154	12	on	on	ADP
app01-10633	154	13	speed	speed	NOUN
app01-10633	154	14	perception	perception	NOUN
app01-10633	154	15	.	.	PUNCT
app01-10633	155	1	in	in	ADP
app01-10633	155	2	areas	area	NOUN
app01-10633	155	3	with	with	ADP
app01-10633	155	4	trees	tree	NOUN
app01-10633	155	5	,	,	PUNCT
app01-10633	155	6	people	people	NOUN
app01-10633	155	7	tend	tend	VERB
app01-10633	155	8	to	to	PART
app01-10633	155	9	estimate	estimate	VERB
app01-10633	155	10	speed	speed	NOUN
app01-10633	155	11	more	more	ADV
app01-10633	155	12	accurately	accurately	ADV
app01-10633	155	13	,	,	PUNCT
app01-10633	155	14	possibly	possibly	ADV
app01-10633	155	15	due	due	ADP
app01-10633	155	16	to	to	ADP
app01-10633	155	17	the	the	DET
app01-10633	155	18	visual	visual	ADJ
app01-10633	155	19	references	reference	NOUN
app01-10633	155	20	trees	tree	NOUN
app01-10633	155	21	provide	provide	VERB
app01-10633	155	22	or	or	CCONJ
app01-10633	155	23	the	the	DET
app01-10633	155	24	environmental	environmental	ADJ
app01-10633	155	25	factors	factor	NOUN
app01-10633	155	26	like	like	ADP
app01-10633	155	27	shading	shading	NOUN
app01-10633	155	28	and	and	CCONJ
app01-10633	155	29	wind	wind	NOUN
app01-10633	155	30	buffering	buffering	NOUN
app01-10633	155	31	that	that	PRON
app01-10633	155	32	help	help	AUX
app01-10633	155	33	moderate	moderate	VERB
app01-10633	155	34	their	their	PRON
app01-10633	155	35	perceptions	perception	NOUN
app01-10633	155	36	.	.	PUNCT
app01-10633	156	1	this	this	PRON
app01-10633	156	2	suggests	suggest	VERB
app01-10633	156	3	that	that	SCONJ
app01-10633	156	4	in	in	ADP
app01-10633	156	5	more	more	ADJ
app01-10633	156	6	structured	structured	ADJ
app01-10633	156	7	environments	environment	NOUN
app01-10633	156	8	where	where	SCONJ
app01-10633	156	9	natural	natural	ADJ
app01-10633	156	10	elements	element	NOUN
app01-10633	156	11	are	be	AUX
app01-10633	156	12	present	present	ADJ
app01-10633	156	13	,	,	PUNCT
app01-10633	156	14	people	people	NOUN
app01-10633	156	15	have	have	VERB
app01-10633	156	16	a	a	DET
app01-10633	156	17	better	well	ADJ
app01-10633	156	18	sense	sense	NOUN
app01-10633	156	19	of	of	ADP
app01-10633	156	20	the	the	DET
app01-10633	156	21	actual	actual	ADJ
app01-10633	156	22	speed	speed	NOUN
app01-10633	156	23	.	.	PUNCT
app01-10633	157	1	in	in	ADP
app01-10633	157	2	contrast	contrast	NOUN
app01-10633	157	3	,	,	PUNCT
app01-10633	157	4	built	build	VERB
app01-10633	157	5	environments	environment	NOUN
app01-10633	157	6	like	like	ADP
app01-10633	157	7	buildings	building	NOUN
app01-10633	157	8	and	and	CCONJ
app01-10633	157	9	particularly	particularly	ADV
app01-10633	157	10	industrial	industrial	ADJ
app01-10633	157	11	zones	zone	NOUN
app01-10633	157	12	significantly	significantly	ADV
app01-10633	157	13	increase	increase	VERB
app01-10633	157	14	the	the	DET
app01-10633	157	15	overestimation	overestimation	NOUN
app01-10633	157	16	of	of	ADP
app01-10633	157	17	speed	speed	NOUN
app01-10633	157	18	.	.	PUNCT
app01-10633	158	1	these	these	DET
app01-10633	158	2	areas	area	NOUN
app01-10633	158	3	are	be	AUX
app01-10633	158	4	likely	likely	ADV
app01-10633	158	5	more	more	ADV
app01-10633	158	6	complex	complex	ADJ
app01-10633	158	7	visually	visually	ADV
app01-10633	158	8	,	,	PUNCT
app01-10633	158	9	with	with	ADP
app01-10633	158	10	large	large	ADJ
app01-10633	158	11	structures	structure	NOUN
app01-10633	158	12	and	and	CCONJ
app01-10633	158	13	potential	potential	ADJ
app01-10633	158	14	obstacles	obstacle	NOUN
app01-10633	158	15	that	that	PRON
app01-10633	158	16	distort	distort	VERB
app01-10633	158	17	people	people	NOUN
app01-10633	158	18	’s	’s	PART
app01-10633	158	19	ability	ability	NOUN
app01-10633	158	20	to	to	PART
app01-10633	158	21	accurately	accurately	ADV
app01-10633	158	22	gauge	gauge	VERB
app01-10633	158	23	how	how	SCONJ
app01-10633	158	24	fast	fast	ADJ
app01-10633	158	25	vehicles	vehicle	NOUN
app01-10633	158	26	are	be	AUX
app01-10633	158	27	moving	move	VERB
app01-10633	158	28	.	.	PUNCT
app01-10633	159	1	the	the	DET
app01-10633	159	2	confined	confine	VERB
app01-10633	159	3	spaces	space	NOUN
app01-10633	159	4	and	and	CCONJ
app01-10633	159	5	obstructions	obstruction	NOUN
app01-10633	159	6	in	in	ADP
app01-10633	159	7	these	these	DET
app01-10633	159	8	areas	area	NOUN
app01-10633	159	9	could	could	AUX
app01-10633	159	10	create	create	VERB
app01-10633	159	11	a	a	DET
app01-10633	159	12	false	false	ADJ
app01-10633	159	13	sense	sense	NOUN
app01-10633	159	14	of	of	ADP
app01-10633	159	15	speed	speed	NOUN
app01-10633	159	16	,	,	PUNCT
app01-10633	159	17	making	make	VERB
app01-10633	159	18	vehicles	vehicle	NOUN
app01-10633	159	19	seem	seem	VERB
app01-10633	159	20	faster	fast	ADV
app01-10633	159	21	than	than	SCONJ
app01-10633	159	22	they	they	PRON
app01-10633	159	23	are	be	AUX
app01-10633	159	24	.	.	PUNCT
app01-10633	160	1	moreover	moreover	ADV
app01-10633	160	2	,	,	PUNCT
app01-10633	160	3	forests	forest	NOUN
app01-10633	160	4	and	and	CCONJ
app01-10633	160	5	urban	urban	ADJ
app01-10633	160	6	areas	area	NOUN
app01-10633	160	7	generally	generally	ADV
app01-10633	160	8	reduce	reduce	VERB
app01-10633	160	9	the	the	DET
app01-10633	160	10	deviation	deviation	NOUN
app01-10633	160	11	between	between	ADP
app01-10633	160	12	perceived	perceive	VERB
app01-10633	160	13	and	and	CCONJ
app01-10633	160	14	actual	actual	ADJ
app01-10633	160	15	speeds	speed	NOUN
app01-10633	160	16	,	,	PUNCT
app01-10633	160	17	with	with	ADP
app01-10633	160	18	forests	forest	NOUN
app01-10633	160	19	showing	show	VERB
app01-10633	160	20	the	the	DET
app01-10633	160	21	most	most	ADV
app01-10633	160	22	substantial	substantial	ADJ
app01-10633	160	23	stabilizing	stabilizing	NOUN
app01-10633	160	24	effect	effect	NOUN
app01-10633	160	25	.	.	PUNCT
app01-10633	161	1	this	this	DET
app01-10633	161	2	finding	finding	NOUN
app01-10633	161	3	indicates	indicate	VERB
app01-10633	161	4	that	that	SCONJ
app01-10633	161	5	natural	natural	ADJ
app01-10633	161	6	settings	setting	NOUN
app01-10633	161	7	with	with	ADP
app01-10633	161	8	consistent	consistent	ADJ
app01-10633	161	9	environmental	environmental	ADJ
app01-10633	161	10	features	feature	NOUN
app01-10633	161	11	allow	allow	VERB
app01-10633	161	12	for	for	ADP
app01-10633	161	13	more	more	ADV
app01-10633	161	14	accurate	accurate	ADJ
app01-10633	161	15	speed	speed	NOUN
app01-10633	161	16	assessments	assessment	NOUN
app01-10633	161	17	,	,	PUNCT
app01-10633	161	18	perhaps	perhaps	ADV
app01-10633	161	19	because	because	SCONJ
app01-10633	161	20	the	the	DET
app01-10633	161	21	surroundings	surrounding	NOUN
app01-10633	161	22	provide	provide	VERB
app01-10633	161	23	regular	regular	ADJ
app01-10633	161	24	,	,	PUNCT
app01-10633	161	25	predictable	predictable	ADJ
app01-10633	161	26	visual	visual	ADJ
app01-10633	161	27	cues	cue	NOUN
app01-10633	161	28	that	that	PRON
app01-10633	161	29	help	help	VERB
app01-10633	161	30	people	people	NOUN
app01-10633	161	31	judge	judge	VERB
app01-10633	161	32	motion	motion	NOUN
app01-10633	161	33	.	.	PUNCT
app01-10633	162	1	there	there	PRON
app01-10633	162	2	were	be	VERB
app01-10633	162	3	also	also	ADV
app01-10633	162	4	instances	instance	NOUN
app01-10633	162	5	where	where	SCONJ
app01-10633	162	6	the	the	DET
app01-10633	162	7	differences	difference	NOUN
app01-10633	162	8	between	between	ADP
app01-10633	162	9	certain	certain	ADJ
app01-10633	162	10	categories	category	NOUN
app01-10633	162	11	,	,	PUNCT
app01-10633	162	12	such	such	ADJ
app01-10633	162	13	as	as	ADP
app01-10633	162	14	flat	flat	ADJ
app01-10633	162	15	area	area	NOUN
app01-10633	162	16	vs	vs	ADP
app01-10633	162	17	downhill	downhill	ADV
app01-10633	162	18	slope	slope	NOUN
app01-10633	162	19	or	or	CCONJ
app01-10633	162	20	flat	flat	ADJ
app01-10633	162	21	area	area	NOUN
app01-10633	162	22	vs	vs	ADP
app01-10633	162	23	buildings	building	NOUN
app01-10633	162	24	,	,	PUNCT
app01-10633	162	25	were	be	AUX
app01-10633	162	26	not	not	PART
app01-10633	162	27	statistically	statistically	ADV
app01-10633	162	28	significant	significant	ADJ
app01-10633	162	29	.	.	PUNCT
app01-10633	163	1	this	this	PRON
app01-10633	163	2	indicates	indicate	VERB
app01-10633	163	3	that	that	SCONJ
app01-10633	163	4	while	while	SCONJ
app01-10633	163	5	the	the	DET
app01-10633	163	6	environment	environment	NOUN
app01-10633	163	7	often	often	ADV
app01-10633	163	8	affects	affect	VERB
app01-10633	163	9	speed	speed	NOUN
app01-10633	163	10	perception	perception	NOUN
app01-10633	163	11	,	,	PUNCT
app01-10633	163	12	it	it	PRON
app01-10633	163	13	does	do	AUX
app01-10633	163	14	not	not	PART
app01-10633	163	15	do	do	VERB
app01-10633	163	16	so	so	ADV
app01-10633	163	17	uniformly	uniformly	ADV
app01-10633	163	18	across	across	ADP
app01-10633	163	19	all	all	DET
app01-10633	163	20	situations	situation	NOUN
app01-10633	163	21	and	and	CCONJ
app01-10633	163	22	settings	setting	NOUN
app01-10633	163	23	.	.	PUNCT
app01-10633	164	1	5	5	X
app01-10633	164	2	.	.	X
app01-10633	164	3	conclusions	conclusion	NOUN
app01-10633	164	4	this	this	DET
app01-10633	164	5	study	study	NOUN
app01-10633	164	6	shows	show	VERB
app01-10633	164	7	that	that	SCONJ
app01-10633	164	8	the	the	DET
app01-10633	164	9	roadside	roadside	NOUN
app01-10633	164	10	strongly	strongly	ADV
app01-10633	164	11	influences	influence	VERB
app01-10633	164	12	human	human	ADJ
app01-10633	164	13	perception	perception	NOUN
app01-10633	164	14	of	of	ADP
app01-10633	164	15	speed	speed	NOUN
app01-10633	164	16	.	.	PUNCT
app01-10633	165	1	natural	natural	ADJ
app01-10633	165	2	settings	setting	NOUN
app01-10633	165	3	,	,	PUNCT
app01-10633	165	4	such	such	ADJ
app01-10633	165	5	as	as	ADP
app01-10633	165	6	trees	tree	NOUN
app01-10633	165	7	and	and	CCONJ
app01-10633	165	8	forests	forest	NOUN
app01-10633	165	9	,	,	PUNCT
app01-10633	165	10	help	help	VERB
app01-10633	165	11	people	people	NOUN
app01-10633	165	12	estimate	estimate	VERB
app01-10633	165	13	speed	speed	NOUN
app01-10633	165	14	more	more	ADV
app01-10633	165	15	accurately	accurately	ADV
app01-10633	165	16	,	,	PUNCT
app01-10633	165	17	while	while	SCONJ
app01-10633	165	18	flat	flat	ADJ
app01-10633	165	19	areas	area	NOUN
app01-10633	165	20	and	and	CCONJ
app01-10633	165	21	built	build	VERB
app01-10633	165	22	environments	environment	NOUN
app01-10633	165	23	,	,	PUNCT
app01-10633	165	24	like	like	ADP
app01-10633	165	25	industrial	industrial	ADJ
app01-10633	165	26	zones	zone	NOUN
app01-10633	165	27	and	and	CCONJ
app01-10633	165	28	buildings	building	NOUN
app01-10633	165	29	,	,	PUNCT
app01-10633	165	30	often	often	ADV
app01-10633	165	31	lead	lead	VERB
app01-10633	165	32	to	to	ADP
app01-10633	165	33	overestimations	overestimation	NOUN
app01-10633	165	34	.	.	PUNCT
app01-10633	166	1	the	the	DET
app01-10633	166	2	lack	lack	NOUN
app01-10633	166	3	of	of	ADP
app01-10633	166	4	visual	visual	ADJ
app01-10633	166	5	cues	cue	NOUN
app01-10633	166	6	or	or	CCONJ
app01-10633	166	7	the	the	DET
app01-10633	166	8	complexity	complexity	NOUN
app01-10633	166	9	of	of	ADP
app01-10633	166	10	these	these	DET
app01-10633	166	11	environments	environment	NOUN
app01-10633	166	12	distorts	distort	VERB
app01-10633	166	13	how	how	SCONJ
app01-10633	166	14	fast	fast	ADJ
app01-10633	166	15	vehicles	vehicle	NOUN
app01-10633	166	16	are	be	AUX
app01-10633	166	17	perceived	perceive	VERB
app01-10633	166	18	.	.	PUNCT
app01-10633	167	1	future	future	ADJ
app01-10633	167	2	research	research	NOUN
app01-10633	167	3	should	should	AUX
app01-10633	167	4	explore	explore	VERB
app01-10633	167	5	why	why	SCONJ
app01-10633	167	6	people	people	NOUN
app01-10633	167	7	overestimate	overestimate	VERB
app01-10633	167	8	speed	speed	NOUN
app01-10633	167	9	in	in	ADP
app01-10633	167	10	these	these	DET
app01-10633	167	11	environments	environment	NOUN
app01-10633	167	12	,	,	PUNCT
app01-10633	167	13	considering	consider	VERB
app01-10633	167	14	visual	visual	ADJ
app01-10633	167	15	complexity	complexity	NOUN
app01-10633	167	16	,	,	PUNCT
app01-10633	167	17	environmental	environmental	ADJ
app01-10633	167	18	familiarity	familiarity	NOUN
app01-10633	167	19	,	,	PUNCT
app01-10633	167	20	and	and	CCONJ
app01-10633	167	21	weather	weather	NOUN
app01-10633	167	22	conditions	condition	NOUN
app01-10633	167	23	.	.	PUNCT
app01-10633	168	1	all	all	DET
app01-10633	168	2	these	these	DET
app01-10633	168	3	factors	factor	NOUN
app01-10633	168	4	–	–	PUNCT
app01-10633	168	5	demographics	demographic	NOUN
app01-10633	168	6	of	of	ADP
app01-10633	168	7	the	the	DET
app01-10633	168	8	observers	observer	NOUN
app01-10633	168	9	,	,	PUNCT
app01-10633	168	10	traffic	traffic	NOUN
app01-10633	168	11	intensity	intensity	NOUN
app01-10633	168	12	,	,	PUNCT
app01-10633	168	13	road	road	NOUN
app01-10633	168	14	surface	surface	NOUN
app01-10633	168	15	,	,	PUNCT
app01-10633	168	16	lighting	lighting	NOUN
app01-10633	168	17	conditions	condition	NOUN
app01-10633	168	18	,	,	PUNCT
app01-10633	168	19	and	and	CCONJ
app01-10633	168	20	types	type	NOUN
app01-10633	168	21	of	of	ADP
app01-10633	168	22	intersections	intersection	NOUN
app01-10633	168	23	–	–	PUNCT
app01-10633	168	24	must	must	AUX
app01-10633	168	25	be	be	AUX
app01-10633	168	26	measured	measure	VERB
app01-10633	168	27	simultaneously	simultaneously	ADV
app01-10633	168	28	to	to	PART
app01-10633	168	29	capture	capture	VERB
app01-10633	168	30	their	their	PRON
app01-10633	168	31	combined	combine	VERB
app01-10633	168	32	effect	effect	NOUN
app01-10633	168	33	on	on	ADP
app01-10633	168	34	speed	speed	NOUN
app01-10633	168	35	perception	perception	NOUN
app01-10633	168	36	.	.	PUNCT
app01-10633	169	1	we	we	PRON
app01-10633	169	2	can	can	AUX
app01-10633	169	3	only	only	ADV
app01-10633	169	4	fully	fully	ADV
app01-10633	169	5	understand	understand	VERB
app01-10633	169	6	how	how	SCONJ
app01-10633	169	7	they	they	PRON
app01-10633	169	8	interact	interact	VERB
app01-10633	169	9	and	and	CCONJ
app01-10633	169	10	shape	shape	VERB
app01-10633	169	11	perception	perception	NOUN
app01-10633	169	12	by	by	ADP
app01-10633	169	13	studying	study	VERB
app01-10633	169	14	them	they	PRON
app01-10633	169	15	together	together	ADV
app01-10633	169	16	.	.	PUNCT
app01-10633	170	1	understanding	understand	VERB
app01-10633	170	2	these	these	DET
app01-10633	170	3	factors	factor	NOUN
app01-10633	170	4	could	could	AUX
app01-10633	170	5	lead	lead	VERB
app01-10633	170	6	to	to	ADP
app01-10633	170	7	better	well	ADJ
app01-10633	170	8	insights	insight	NOUN
app01-10633	170	9	into	into	ADP
app01-10633	170	10	how	how	SCONJ
app01-10633	170	11	humans	human	NOUN
app01-10633	170	12	perceive	perceive	VERB
app01-10633	170	13	speed	speed	NOUN
app01-10633	170	14	,	,	PUNCT
app01-10633	170	15	with	with	ADP
app01-10633	170	16	practical	practical	ADJ
app01-10633	170	17	applications	application	NOUN
app01-10633	170	18	in	in	ADP
app01-10633	170	19	urban	urban	ADJ
app01-10633	170	20	planning	planning	NOUN
app01-10633	170	21	and	and	CCONJ
app01-10633	170	22	road	road	NOUN
app01-10633	170	23	safety	safety	NOUN
app01-10633	170	24	.	.	PUNCT
app01-10633	171	1	acknowledgements	acknowledgement	NOUN
app01-10633	171	2	this	this	DET
app01-10633	171	3	paper	paper	NOUN
app01-10633	171	4	was	be	AUX
app01-10633	171	5	written	write	VERB
app01-10633	171	6	within	within	ADP
app01-10633	171	7	the	the	DET
app01-10633	171	8	project	project	NOUN
app01-10633	171	9	of	of	ADP
app01-10633	171	10	the	the	DET
app01-10633	171	11	specific	specific	ADJ
app01-10633	171	12	university	university	NOUN
app01-10633	171	13	research	research	NOUN
app01-10633	171	14	entitled	entitle	VERB
app01-10633	171	15	“	"	PUNCT
app01-10633	171	16	database	database	NOUN
app01-10633	171	17	of	of	ADP
app01-10633	171	18	vehicle	vehicle	NOUN
app01-10633	171	19	speed	speed	NOUN
app01-10633	171	20	estimates	estimate	NOUN
app01-10633	171	21	in	in	ADP
app01-10633	171	22	urban	urban	ADJ
app01-10633	171	23	areas	area	NOUN
app01-10633	171	24	”	"	PUNCT
app01-10633	171	25	(	(	PUNCT
app01-10633	171	26	no	no	INTJ
app01-10633	171	27	.	.	PUNCT
app01-10633	172	1	úsi	úsi	NOUN
app01-10633	172	2	-	-	PUNCT
app01-10633	172	3	j-23	j-23	NOUN
app01-10633	172	4	-	-	PUNCT
app01-10633	172	5	8652	8652	NUM
app01-10633	172	6	)	)	PUNCT
app01-10633	172	7	and	and	CCONJ
app01-10633	172	8	was	be	AUX
app01-10633	172	9	carried	carry	VERB
app01-10633	172	10	out	out	ADP
app01-10633	172	11	at	at	ADP
app01-10633	172	12	the	the	DET
app01-10633	172	13	institute	institute	NOUN
app01-10633	172	14	of	of	ADP
app01-10633	172	15	forensic	forensic	ADJ
app01-10633	172	16	engineering	engineering	NOUN
app01-10633	172	17	of	of	ADP
app01-10633	172	18	brno	brno	PROPN
app01-10633	172	19	university	university	PROPN
app01-10633	172	20	of	of	ADP
app01-10633	172	21	technology	technology	NOUN
app01-10633	172	22	.	.	PUNCT
app01-10633	173	1	references	reference	NOUN
app01-10633	173	2	[	[	X
app01-10633	173	3	1	1	X
app01-10633	173	4	]	]	X
app01-10633	173	5	y.	y.	PROPN
app01-10633	173	6	qin	qin	PROPN
app01-10633	173	7	,	,	PUNCT
app01-10633	173	8	y.	y.	PROPN
app01-10633	173	9	chen	chen	PROPN
app01-10633	173	10	,	,	PUNCT
app01-10633	173	11	k.	k.	PROPN
app01-10633	173	12	lin	lin	PROPN
app01-10633	173	13	.	.	PUNCT
app01-10633	174	1	quantifying	quantify	VERB
app01-10633	174	2	the	the	DET
app01-10633	174	3	effects	effect	NOUN
app01-10633	174	4	of	of	ADP
app01-10633	174	5	visual	visual	ADJ
app01-10633	174	6	road	road	NOUN
app01-10633	174	7	information	information	NOUN
app01-10633	174	8	on	on	ADP
app01-10633	174	9	drivers	driver	NOUN
app01-10633	174	10	’	’	PART
app01-10633	174	11	speed	speed	NOUN
app01-10633	174	12	choices	choice	NOUN
app01-10633	174	13	to	to	PART
app01-10633	174	14	promote	promote	VERB
app01-10633	174	15	self	self	NOUN
app01-10633	174	16	-	-	PUNCT
app01-10633	174	17	explaining	explain	VERB
app01-10633	174	18	roads	road	NOUN
app01-10633	174	19	.	.	PUNCT
app01-10633	175	1	international	international	ADJ
app01-10633	175	2	journal	journal	PROPN
app01-10633	175	3	of	of	ADP
app01-10633	175	4	environmental	environmental	ADJ
app01-10633	175	5	research	research	NOUN
app01-10633	175	6	and	and	CCONJ
app01-10633	175	7	public	public	ADJ
app01-10633	175	8	health	health	NOUN
app01-10633	175	9	17(7):2437	17(7):2437	NUM
app01-10633	175	10	,	,	PUNCT
app01-10633	175	11	2020	2020	NUM
app01-10633	175	12	.	.	PUNCT
app01-10633	176	1	https://doi.org/10.3390/ijerph17072437	https://doi.org/10.3390/ijerph17072437	PROPN
app01-10633	176	2	120	120	NUM
app01-10633	176	3	https://doi.org/10.3390/ijerph17072437	https://doi.org/10.3390/ijerph17072437	ADJ
app01-10633	176	4	vol	vol	NOUN
app01-10633	176	5	.	.	PUNCT
app01-10633	177	1	52/2025	52/2025	NUM
app01-10633	177	2	the	the	DET
app01-10633	177	3	effect	effect	NOUN
app01-10633	177	4	of	of	ADP
app01-10633	177	5	roadside	roadside	NOUN
app01-10633	177	6	on	on	ADP
app01-10633	177	7	speed	speed	NOUN
app01-10633	177	8	perception	perception	NOUN
app01-10633	177	9	[	[	X
app01-10633	177	10	2	2	NUM
app01-10633	177	11	]	]	PUNCT
app01-10633	177	12	c.	c.	PROPN
app01-10633	177	13	wu	wu	PROPN
app01-10633	177	14	,	,	PUNCT
app01-10633	177	15	d.	d.	PROPN
app01-10633	177	16	yu	yu	PROPN
app01-10633	177	17	,	,	PUNCT
app01-10633	177	18	a.	a.	PROPN
app01-10633	177	19	doherty	doherty	PROPN
app01-10633	177	20	,	,	PUNCT
app01-10633	177	21	et	et	PROPN
app01-10633	177	22	al	al	PROPN
app01-10633	177	23	.	.	PUNCT
app01-10633	178	1	an	an	DET
app01-10633	178	2	investigation	investigation	NOUN
app01-10633	178	3	of	of	ADP
app01-10633	178	4	perceived	perceive	VERB
app01-10633	178	5	vehicle	vehicle	NOUN
app01-10633	178	6	speed	speed	NOUN
app01-10633	178	7	from	from	ADP
app01-10633	178	8	a	a	DET
app01-10633	178	9	driver	driver	NOUN
app01-10633	178	10	’s	’s	PART
app01-10633	178	11	perspective	perspective	NOUN
app01-10633	178	12	.	.	PUNCT
app01-10633	179	1	plos	plos	PROPN
app01-10633	179	2	one	one	NUM
app01-10633	179	3	12(10):e0185347	12(10):e0185347	NUM
app01-10633	179	4	,	,	PUNCT
app01-10633	179	5	2017	2017	NUM
app01-10633	179	6	.	.	PUNCT
app01-10633	180	1	https://doi.org/10.1371/journal.pone.0185347	https://doi.org/10.1371/journal.pone.0185347	ADJ
app01-10633	181	1	[	[	X
app01-10633	181	2	3	3	X
app01-10633	181	3	]	]	X
app01-10633	181	4	d.	d.	PROPN
app01-10633	181	5	schaffner	schaffner	PROPN
app01-10633	181	6	,	,	PUNCT
app01-10633	181	7	m.	m.	NOUN
app01-10633	181	8	van	van	PROPN
app01-10633	181	9	eggermond	eggermond	PROPN
app01-10633	181	10	,	,	PUNCT
app01-10633	181	11	n.	n.	NOUN
app01-10633	181	12	studer	studer	NOUN
app01-10633	181	13	.	.	PUNCT
app01-10633	182	1	selfexplaining	selfexplaine	VERB
app01-10633	182	2	roads	road	NOUN
app01-10633	182	3	:	:	PUNCT
app01-10633	182	4	effects	effect	NOUN
app01-10633	182	5	of	of	ADP
app01-10633	182	6	road	road	NOUN
app01-10633	182	7	design	design	NOUN
app01-10633	182	8	on	on	ADP
app01-10633	182	9	perception	perception	NOUN
app01-10633	182	10	and	and	CCONJ
app01-10633	182	11	speed	speed	NOUN
app01-10633	182	12	choice	choice	NOUN
app01-10633	182	13	.	.	PUNCT
app01-10633	183	1	in	in	ADP
app01-10633	183	2	international	international	ADJ
app01-10633	183	3	conference	conference	NOUN
app01-10633	183	4	on	on	ADP
app01-10633	183	5	traffic	traffic	NOUN
app01-10633	183	6	and	and	CCONJ
app01-10633	183	7	transport	transport	NOUN
app01-10633	183	8	psychology	psychology	NOUN
app01-10633	183	9	icttp	icttp	ADV
app01-10633	183	10	.	.	PUNCT
app01-10633	183	11	2022	2022	NUM
app01-10633	183	12	.	.	PUNCT
app01-10633	184	1	[	[	X
app01-10633	184	2	2024	2024	NUM
app01-10633	184	3	-	-	SYM
app01-10633	184	4	10	10	NUM
app01-10633	184	5	-	-	SYM
app01-10633	184	6	20	20	NUM
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app01-10633	184	8	.	.	PUNCT
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app01-10633	185	2	[	[	X
app01-10633	185	3	4	4	NUM
app01-10633	185	4	]	]	PUNCT
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app01-10633	185	6	s.	s.	PROPN
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app01-10633	185	10	a.	a.	NOUN
app01-10633	185	11	knodler	knodler	NOUN
app01-10633	185	12	,	,	PUNCT
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app01-10633	185	14	m.	m.	PROPN
app01-10633	185	15	dulaski	dulaski	PROPN
app01-10633	185	16	.	.	PUNCT
app01-10633	186	1	speed	speed	NOUN
app01-10633	186	2	perception	perception	NOUN
app01-10633	186	3	fidelity	fidelity	NOUN
app01-10633	186	4	in	in	ADP
app01-10633	186	5	a	a	DET
app01-10633	186	6	driving	drive	VERB
app01-10633	186	7	simulator	simulator	NOUN
app01-10633	186	8	environment	environment	NOUN
app01-10633	186	9	.	.	PUNCT
app01-10633	187	1	in	in	ADP
app01-10633	187	2	proceedings	proceeding	NOUN
app01-10633	187	3	of	of	ADP
app01-10633	187	4	the	the	DET
app01-10633	187	5	driving	drive	VERB
app01-10633	187	6	simulator	simulator	NOUN
app01-10633	187	7	conference	conference	PROPN
app01-10633	187	8	north	north	PROPN
app01-10633	187	9	america	america	PROPN
app01-10633	187	10	,	,	PUNCT
app01-10633	187	11	pp	pp	X
app01-10633	187	12	.	.	PUNCT
app01-10633	188	1	343–352	343–352	NUM
app01-10633	188	2	.	.	PUNCT
app01-10633	188	3	2005	2005	NUM
app01-10633	188	4	.	.	PUNCT
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app01-10633	189	2	5	5	X
app01-10633	189	3	]	]	PUNCT
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app01-10633	189	5	xu	xu	PROPN
app01-10633	189	6	,	,	PUNCT
app01-10633	189	7	h.	h.	PROPN
app01-10633	189	8	li	li	PROPN
app01-10633	189	9	,	,	PUNCT
app01-10633	189	10	x.	x.	PROPN
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app01-10633	189	12	,	,	PUNCT
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app01-10633	189	15	.	.	PUNCT
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app01-10633	190	2	influence	influence	NOUN
app01-10633	190	3	of	of	ADP
app01-10633	190	4	freeway	freeway	NOUN
app01-10633	190	5	curve	curve	NOUN
app01-10633	190	6	characteristics	characteristic	NOUN
app01-10633	190	7	on	on	ADP
app01-10633	190	8	drivers	driver	NOUN
app01-10633	190	9	’	'	PUNCT
app01-10633	190	10	speed	speed	NOUN
app01-10633	190	11	perception	perception	NOUN
app01-10633	190	12	accuracy	accuracy	NOUN
app01-10633	190	13	.	.	PUNCT
app01-10633	191	1	plos	plos	PROPN
app01-10633	191	2	one	one	NUM
app01-10633	191	3	17(5):e0267250	17(5):e0267250	NUM
app01-10633	191	4	,	,	PUNCT
app01-10633	191	5	2022	2022	NUM
app01-10633	191	6	.	.	PUNCT
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app01-10633	192	2	[	[	PUNCT
app01-10633	192	3	6	6	NUM
app01-10633	192	4	]	]	PUNCT
app01-10633	192	5	l.	l.	PROPN
app01-10633	192	6	kamasová	kamasová	PROPN
app01-10633	192	7	.	.	PUNCT
app01-10633	193	1	vnímání	vnímání	PROPN
app01-10633	193	2	rychlosti	rychlosti	NOUN
app01-10633	193	3	vozidla	vozidla	NOUN
app01-10633	193	4	[	[	X
app01-10633	193	5	in	in	ADP
app01-10633	193	6	czech	czech	PROPN
app01-10633	193	7	;	;	PUNCT
app01-10633	193	8	perception	perception	NOUN
app01-10633	193	9	of	of	ADP
app01-10633	193	10	vehicle	vehicle	NOUN
app01-10633	193	11	speed	speed	NOUN
app01-10633	193	12	]	]	PUNCT
app01-10633	193	13	.	.	PUNCT
app01-10633	194	1	master	master	PROPN
app01-10633	194	2	’s	’s	PART
app01-10633	194	3	thesis	thesis	NOUN
app01-10633	194	4	,	,	PUNCT
app01-10633	194	5	vysoké	vysoké	VERB
app01-10633	194	6	učení	učení	PROPN
app01-10633	194	7	technické	technické	PROPN
app01-10633	194	8	v	v	X
app01-10633	194	9	brně	brně	PROPN
app01-10633	194	10	,	,	PUNCT
app01-10633	194	11	ústav	ústav	VERB
app01-10633	194	12	soudního	soudního	ADJ
app01-10633	194	13	inženýrství	inženýrství	NOUN
app01-10633	194	14	,	,	PUNCT
app01-10633	194	15	2018	2018	NUM
app01-10633	194	16	.	.	PUNCT
app01-10633	195	1	[	[	X
app01-10633	195	2	2024	2024	NUM
app01-10633	195	3	-	-	SYM
app01-10633	195	4	10	10	NUM
app01-10633	195	5	-	-	SYM
app01-10633	195	6	20	20	NUM
app01-10633	195	7	]	]	PUNCT
app01-10633	195	8	.	.	PUNCT
app01-10633	196	1	https	https	PROPN
app01-10633	196	2	:	:	PUNCT
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app01-10633	196	4	/	/	SYM
app01-10633	196	5	studenti	studenti	PROPN
app01-10633	196	6	/	/	SYM
app01-10633	196	7	zav	zav	PROPN
app01-10633	196	8	-	-	PUNCT
app01-10633	196	9	prace	prace	PROPN
app01-10633	196	10	/	/	SYM
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app01-10633	197	2	7	7	NUM
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app01-10633	197	5	hlavinková	hlavinková	PROPN
app01-10633	197	6	.	.	PUNCT
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app01-10633	198	4	[	[	X
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app01-10633	198	6	czech	czech	PROPN
app01-10633	198	7	;	;	PUNCT
app01-10633	198	8	perception	perception	NOUN
app01-10633	198	9	of	of	ADP
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app01-10633	198	11	speed	speed	NOUN
app01-10633	198	12	]	]	PUNCT
app01-10633	198	13	.	.	PUNCT
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app01-10633	199	4	,	,	PUNCT
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app01-10633	199	6	učení	učení	PROPN
app01-10633	199	7	technické	technické	PROPN
app01-10633	199	8	v	v	X
app01-10633	199	9	brně	brně	PROPN
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app01-10633	199	11	ústav	ústav	VERB
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app01-10633	199	14	,	,	PUNCT
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app01-10633	199	16	.	.	PUNCT
app01-10633	200	1	[	[	X
app01-10633	200	2	2024	2024	NUM
app01-10633	200	3	-	-	SYM
app01-10633	200	4	10	10	NUM
app01-10633	200	5	-	-	SYM
app01-10633	200	6	20	20	NUM
app01-10633	200	7	]	]	PUNCT
app01-10633	200	8	.	.	PUNCT
app01-10633	201	1	https	https	NOUN
app01-10633	201	2	:	:	PUNCT
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app01-10633	201	6	/	/	SYM
app01-10633	201	7	zav	zav	PROPN
app01-10633	201	8	-	-	PUNCT
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app01-10633	202	2	8	8	NUM
app01-10633	202	3	]	]	PUNCT
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app01-10633	202	5	rak	rak	PROPN
app01-10633	202	6	.	.	PUNCT
app01-10633	203	1	vnímání	vnímání	PROPN
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app01-10633	203	3	vozidla	vozidla	VERB
app01-10633	203	4	chodcem	chodcem	NOUN
app01-10633	204	1	[	[	X
app01-10633	204	2	in	in	ADP
app01-10633	204	3	czech	czech	PROPN
app01-10633	204	4	;	;	PUNCT
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app01-10633	204	8	speed	speed	NOUN
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app01-10633	205	1	master	master	PROPN
app01-10633	205	2	’s	’s	PART
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app01-10633	205	11	ústav	ústav	VERB
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app01-10633	205	14	,	,	PUNCT
app01-10633	205	15	2020	2020	NUM
app01-10633	205	16	.	.	PUNCT
app01-10633	206	1	[	[	X
app01-10633	206	2	2024	2024	NUM
app01-10633	206	3	-	-	SYM
app01-10633	206	4	10	10	NUM
app01-10633	206	5	-	-	SYM
app01-10633	206	6	20	20	NUM
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app01-10633	206	8	.	.	PUNCT
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app01-10633	207	4	/	/	SYM
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app01-10633	207	10	/	/	SYM
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app01-10633	210	1	[	[	X
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app01-10633	210	3	czech	czech	PROPN
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app01-10633	212	5	-	-	SYM
app01-10633	212	6	20	20	NUM
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app01-10633	212	8	.	.	PUNCT
app01-10633	213	1	https	https	PROPN
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app01-10633	217	5	-	-	SYM
app01-10633	217	6	20	20	NUM
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app01-10633	217	8	.	.	PUNCT
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app01-10633	220	1	vnímání	vnímání	PROPN
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app01-10633	220	3	vozidla	vozidla	NOUN
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app01-10633	220	7	řidičských	řidičských	PROPN
app01-10633	220	8	zkušeností	zkušeností	PROPN
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app01-10633	221	2	in	in	ADP
app01-10633	221	3	czech	czech	PROPN
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app01-10633	221	17	.	.	PUNCT
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app01-10633	222	14	,	,	PUNCT
app01-10633	222	15	2021	2021	NUM
app01-10633	222	16	.	.	PUNCT
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app01-10633	223	4	10	10	NUM
app01-10633	223	5	-	-	SYM
app01-10633	223	6	20	20	NUM
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app01-10633	223	8	.	.	PUNCT
app01-10633	224	1	https	https	PROPN
app01-10633	224	2	:	:	PUNCT
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app01-10633	224	8	-	-	PUNCT
app01-10633	224	9	prace	prace	NOUN
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app01-10633	225	2	nočních	nočních	PROPN
app01-10633	225	3	odhadů	odhadů	PROPN
app01-10633	225	4	rychlostí	rychlostí	PROPN
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app01-10633	226	8	speed	speed	NOUN
app01-10633	226	9	estimates	estimate	NOUN
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app01-10633	227	3	příspěvků	příspěvků	NOUN
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app01-10633	227	6	forensic	forensic	ADJ
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app01-10633	227	9	2023	2023	NUM
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app01-10633	228	1	32–38	32–38	NUM
app01-10633	228	2	.	.	PUNCT
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app01-10633	229	2	učení	učení	PROPN
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app01-10633	229	12	,	,	PUNCT
app01-10633	229	13	2023	2023	NUM
app01-10633	229	14	.	.	PUNCT
app01-10633	230	1	isbn	isbn	ADJ
app01-10633	230	2	978	978	NUM
app01-10633	230	3	-	-	SYM
app01-10633	230	4	80	80	NUM
app01-10633	230	5	-	-	PUNCT
app01-10633	230	6	214	214	NUM
app01-10633	230	7	-	-	PUNCT
app01-10633	230	8	6165	6165	NUM
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app01-10633	230	10	9	9	NUM
app01-10633	230	11	.	.	NUM
app01-10633	230	12	121	121	NUM
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app01-10633	230	14	https://irf.fhnw.ch/handle/11654/34086	https://irf.fhnw.ch/handle/11654/34086	NOUN
app01-10633	230	15	https://doi.org/10.1371/journal.pone.0267250	https://doi.org/10.1371/journal.pone.0267250	VERB
app01-10633	230	16	https://www.vutbr.cz/studenti/zav-prace/detail/112286	https://www.vutbr.cz/studenti/zav-prace/detail/112286	ADJ
app01-10633	230	17	https://www.vutbr.cz/studenti/zav-prace/detail/112286	https://www.vutbr.cz/studenti/zav-prace/detail/112286	PROPN
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app01-10633	230	20	https://www.vutbr.cz/studenti/zav-prace/detail/120323	https://www.vutbr.cz/studenti/zav-prace/detail/120323	PROPN
app01-10633	230	21	https://www.vutbr.cz/studenti/zav-prace/detail/120323	https://www.vutbr.cz/studenti/zav-prace/detail/120323	PROPN
app01-10633	230	22	https://www.vutbr.cz/studenti/zav-prace/detail/132016	https://www.vutbr.cz/studenti/zav-prace/detail/132016	X
app01-10633	230	23	https://www.vutbr.cz/studenti/zav-prace/detail/132016	https://www.vutbr.cz/studenti/zav-prace/detail/132016	PROPN
app01-10633	230	24	https://www.vutbr.cz/studenti/zav-prace/detail/135642	https://www.vutbr.cz/studenti/zav-prace/detail/135642	NUM
app01-10633	230	25	https://www.vutbr.cz/studenti/zav-prace/detail/135642	https://www.vutbr.cz/studenti/zav-prace/detail/135642	PROPN
app01-10633	230	26	https://www.vutbr.cz/studenti/zav-prace/detail/127915	https://www.vutbr.cz/studenti/zav-prace/detail/127915	PROPN
app01-10633	230	27	https://www.vutbr.cz/studenti/zav-prace/detail/127915	https://www.vutbr.cz/studenti/zav-prace/detail/127915	PROPN
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app01-10633	230	29	polytechnica	polytechnica	PROPN
app01-10633	230	30	ctu	ctu	NOUN
app01-10633	230	31	proceedings	proceeding	NOUN
app01-10633	230	32	52:116–121	52:116–121	NUM
app01-10633	230	33	,	,	PUNCT
app01-10633	230	34	2025	2025	NUM
app01-10633	230	35	1	1	NUM
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app01-10633	230	37	2	2	NUM
app01-10633	230	38	dataset	dataset	NOUN
app01-10633	230	39	and	and	CCONJ
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app01-10633	230	41	2.1	2.1	NUM
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app01-10633	230	44	2.2	2.2	NUM
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app01-10633	230	46	criteria	criterion	NOUN
app01-10633	230	47	3	3	NUM
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app01-10633	230	49	4	4	NUM
app01-10633	230	50	discussion	discussion	NOUN
app01-10633	230	51	5	5	NUM
app01-10633	230	52	conclusions	conclusion	NOUN
app01-10633	230	53	acknowledgements	acknowledgement	NOUN
app01-10633	230	54	references	reference	NOUN