32 citations · 32 across the 7 of their papers we have counts for
9 papers
Physics-Informed Koopman Learning for Data-Efficient System Identification of Automated Vehicle Dynamics
Hangyu Li, Yiming Meng, Zhaohui Liang +8
Understanding how a particular automated vehicle reacts to nearby traffic can improve motion prediction, control development, traffic simulation, and safety evaluation. However, co…
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…
SRA-CP: Spontaneous Risk-Aware Selective Cooperative Perception
Jiaxi Liu, Chengyuan Ma, Hang Zhou +5
Cooperative perception (CP) offers significant potential to overcome the limitations of single-vehicle sensing by enabling information sharing among connected vehicles (CVs). Howev…
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…
Unveiling Uniform Shifted Power Law in Stochastic Human and Autonomous Driving Behavior
Wang Chen, Heye Huang, Ke Ma +4
Accurately simulating rare but safety-critical driving behaviors is essential for the evaluation and certification of autonomous vehicles (AVs). However, current models often fail…
Benchmarking Tesla's Traffic Light and Stop Sign Control: Field Dataset and Behavior Insights
Zheng Li, Peng Zhang, Shixiao Liang +5
Understanding how Advanced Driver-Assistance Systems (ADAS) interact with Traffic Control Devices (TCDs) is critical for assessing their influence on traffic operations, yet this i…
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…
Analytical Optimized Traffic Flow Recovery for Large-scale Urban Transportation Network
Sicheng Fu, Haotian Shi, Shixiao Liang +2
The implementation of intelligent transportation systems (ITS) has enhanced data collection in urban transportation through advanced traffic sensing devices. However, the high cost…
A Unified Longitudinal Trajectory Dataset for Automated Vehicle
Hang Zhou, Ke Ma, Shixiao Liang +2
Automated Vehicles (AVs) promise significant advances in transportation. Critical to these improvements is understanding AVs' longitudinal behavior, relying heavily on real-world t…