Predicting traffic incident risks at granular spatiotemporal levels is
c...
Urban road-based risk prediction is a crucial yet challenging aspect of
...
crucial for transportation management. However, traditional spatial-temp...
Traffic data serves as a fundamental component in both research and
appl...
Short-term demand forecasting for on-demand ride-hailing services is one...
Recent studies have significantly improved the prediction accuracy of tr...
Origin-Destination (O-D) travel demand prediction is a fundamental chall...
The Braess's Paradox (BP) is the observation that adding one or more roa...
Spatiotemporal kriging is an important application in spatiotemporal dat...
This paper studies the traffic state estimation (TSE) problem using spar...
Time series forecasting and spatiotemporal kriging are the two most impo...