id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
ajst-32395	Chu, Tianqi	Redundancy-Aware Multi-Sensor Fusion for Resilient Perception in Intelligent Vehicles	2025	9	.pdf	application/pdf	5084	226	34	Uncertainty from learned fusion is often miscalibrated and therefore over‑confident; distribution shift across weather, lens contamination, and rare targets remains under‑represented in training and evaluation; black‑box fusion complicates safety cases and public trust; and embedded compute budgets make some accurate raw‑level approaches impractical at ASIL‑D deadlines. Redundancy and data fusion counter this fragility by arranging for alternate coverage, by cross‑checking disagreeing measurements, and by enabling graceful degradation when one channel becomes unreliable.	cache/ajst-32395.pdf	txt/ajst-32395.txt