3 papers
cs.AI2025
Spatiotemporal Prediction of Secondary Crashes by Rebalancing Dynamic and Static Data with Generative Adversarial Networks
Junlan Chen, Yiqun Li, Chenyu Ling +2
Data imbalance is a common issue in analyzing and predicting sudden traffic events. Secondary crashes constitute only a small proportion of all crashes. These secondary crashes, tr…
cs.LG2024
A Generative Deep Learning Approach for Crash Severity Modeling with Imbalanced Data
Junlan Chen, Ziyuan Pu, Nan Zheng +3
Crash data is often greatly imbalanced, with the majority of crashes being non-fatal crashes, and only a small number being fatal crashes due to their rarity. Such data imbalance i…
cs.LG2024
Inferring Heterogeneous Treatment Effects of Crashes on Highway Traffic: A Doubly Robust Causal Machine Learning Approach
Shuang Li, Ziyuan Pu, Zhiyong Cui +3
Highway traffic crashes exert a considerable impact on both transportation systems and the economy. In this context, accurate and dependable emergency responses are crucial for eff…