DSETA: a dual-stage continual learning framework for travel time prediction in dynamic traffic environments
Read the original at arxiv.org→arXiv:2608.00402v1 Announce Type: new Abstract: Estimated Time of Arrival (ETA) prediction is a core component of intelligent transportation systems. As traffic congestion patterns become increasingly dynamic in...
Original headline: "DSETA: A Dual-Stage Continual Learning Framework for Travel Time Prediction in Dynamic Traffic Environments"
Coverage timeline
- Aug 4, 04:00 UTC arXiv cs.LG lead source DSETA: A Dual-Stage Continual Learning Framework for Travel Time Prediction in Dynamic Traffic Environments