8 papers
Robustness and Resilience Evaluation of Eco-Driving Strategies at Signalized Intersections
Zhaohui Liang, Chengyuan Ma, Keke Long +1
Eco-driving strategies have demonstrated substantial potential for improving energy efficiency and reducing emissions, especially at signalized intersections. However, evaluations…
Real-Time Lane-Level Crash Detection on Freeways Using Sparse Telematics Data
Shixiao Liang, Chengyuan Ma, Pei Li +7
Real-time traffic crash detection is critical in intelligent transportation systems because traditional crash notifications often suffer delays and lack specific, lane-level locati…
CATS-V2V: A Real-World Vehicle-to-Vehicle Cooperative Perception Dataset with Complex Adverse Traffic Scenarios
Hangyu Li, Bofeng Cao, Zhaohui Liang +16
Vehicle-to-Vehicle (V2V) cooperative perception has great potential to enhance autonomous driving performance by overcoming perception limitations in complex adverse traffic scenar…
A Low-Rank Method for Vision Language Model Hallucination Mitigation in Autonomous Driving
Keke Long, Jiacheng Guo, Tianyun Zhang +2
Vision Language Models (VLMs) are increasingly used in autonomous driving to help understand traffic scenes, but they sometimes produce hallucinations, which are false details not…
Theory Foundation of Physics-Enhanced Residual Learning
Shixiao Liang, Wang Chen, Keke Long +3
Intensive studies have been conducted in recent years to integrate neural networks with physics models to balance model accuracy and interpretability. One recently proposed approac…
Simulating the Unseen: Crash Prediction Must Learn from What Did Not Happen
Zihao Li, Xinyuan Cao, Xiangbo Gao +12
Traffic safety science has long been hindered by a fundamental data paradox: the crashes we most wish to prevent are precisely those events we rarely observe. Existing crash-freque…