3 citations · 4 across the 6 of their papers we have counts for
6 papers
NTR: Neural Token Reconstruction for Scene Token Bottleneck in End-to-End Driving
Jiahui Li, Jiawei Sun, Zixiang Ren +7
Recent perception-free end-to-end (E2E) autonomous driving methods bypass explicit perception outputs by compressing dense image patch tokens into compact scene tokens for downstre…
Virtual Traffic Police: Large Language Model-Augmented Traffic Signal Control for Unforeseen Incidents
Shiqi Wei, Qiqing Wang, Kaidi Yang
Adaptive traffic signal control (TSC) has demonstrated strong effectiveness in managing dynamic traffic flows. However, conventional methods often struggle when unforeseen traffic…
Interaction-Aware Trajectory Prediction for Safe Motion Planning in Autonomous Driving: A Transformer-Transfer Learning Approach
Jinhao Liang, Chaopeng Tan, Longhao Yan +3
A critical aspect of safe and efficient motion planning for autonomous vehicles (AVs) is to handle the complex and uncertain behavior of surrounding human-driven vehicles (HDVs). D…
Connected Vehicle Data-driven Robust Optimization for Traffic Signal Timing: Modeling Traffic Flow Variability and Errors
Chaopeng Tan, Yue Ding, Kaidi Yang +2
Recent advancements in Connected Vehicle (CV) technology have prompted research on leveraging CV data for more effective traffic management. Despite the low penetration rate, such…
Enhancing High-Speed Cruising Performance of Autonomous Vehicles through Integrated Deep Reinforcement Learning Framework
Jinhao Liang, Kaidi Yang, Chaopeng Tan +2
High-speed cruising scenarios with mixed traffic greatly challenge the road safety of autonomous vehicles (AVs). Unlike existing works that only look at fundamental modules in isol…
Privacy-Preserving Data Fusion for Traffic State Estimation: A Vertical Federated Learning Approach
Qiqing Wang, Kaidi Yang
This paper proposes a privacy-preserving data fusion method for traffic state estimation (TSE). Unlike existing works that assume all data sources to be accessible by a single trus…