Framework for Autonomous Driving Trajectory Prediction via Physics-Constrained Data Fusion and Spatiotemporal Encoding

dc.contributor.author	Yuan, Yi
dc.contributor.author	Li, Peng
dc.date.accessioned	2026-08-20T20:57:23Z
dc.date.available	2026-08-20T20:57:23Z
dc.date.copyright	2026/02/25
dc.date.issued	2026
dc.identifier.other	JTEPBS.TEENG-9445.pdf
dc.identifier.uri	http://yetl.yabesh.ir/yetl1/handle/yetl/4313728
dc.description.abstract	AbstractWith the rapid development of artificial intelligence, autonomous driving has advanced significantly. Vehicle trajectory prediction, a key component of autonomous driving, directly affects the quality of planning and decision-making in dynamic ...
dc.publisher	American Society of Civil Engineers
dc.title	Framework for Autonomous Driving Trajectory Prediction via Physics-Constrained Data Fusion and Spatiotemporal Encoding
dc.type	Journal Article
dc.journal.volume	152
dc.journal.issue	5
dc.journal.title	Journal of Transportation Engineering, Part A: Systems
dc.identifier.doi	10.1061/JTEPBS.TEENG-9445
dc.journal.fristpage	04026023-1
dc.journal.lastpage	04026023-15
dc.page	15
dc.tree	Journal of Transportation Engineering, Part A: Systems:;2026:;Volume ( 152 ):;issue: 005
dc.contenttype	Fulltext