Spatiotemporal expert GPT network for traffic flow prediction
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Published online on May 07, 2026
Abstract
Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Ahead of Print.
Urban traffic displays pronounced temporal periodicity, spatial dependencies, and heterogeneous behavioral patterns. These characteristics hinder traditional approaches from capturing multi-scale dynamics and complex topologies within a unified prediction ...
Urban traffic displays pronounced temporal periodicity, spatial dependencies, and heterogeneous behavioral patterns. These characteristics hinder traditional approaches from capturing multi-scale dynamics and complex topologies within a unified prediction ...