13 citations · 15 across the 6 of their papers we have counts for
6 papers
Plug-and-Play Traffic Element Awareness for End-to-End Autonomous Driving
Zongzheng Zhang, Jijun Wang, Saining Zhang +8
Traffic elements such as traffic lights and road signs play a fundamental role in human driving decisions and should naturally influence end-to-end driving performance. However, ex…
Do Open-Loop Metrics Predict Closed-Loop Driving? A Cross-Benchmark Correlation Study of NAVSIM and Bench2Drive
Yiru Wang, Anqing Jiang, Shuo Wang +4
Open-loop evaluation offers fast, reproducible assessment of autonomous driving planners, but its ability to predict real closed-loop driving performance remains questionable. Prio…
Principal Prototype Analysis on Manifold for Interpretable Reinforcement Learning
Bodla Krishna Vamshi, Haizhao Yang
Recent years have witnessed the widespread adoption of reinforcement learning (RL), from solving real-time games to fine-tuning large language models using human preference data si…
Automating Traffic Model Enhancement with AI Research Agent
Xusen Guo, Xinxi Yang, Mingxing Peng +3
Developing efficient traffic models is crucial for optimizing modern transportation systems. However, current modeling approaches remain labor-intensive and prone to human errors d…
Diffusion Models for Intelligent Transportation Systems: A Survey
Mingxing Peng, Kehua Chen, Xusen Guo +4
Intelligent Transportation Systems (ITS) are vital in modern traffic management and optimization, significantly enhancing traffic efficiency and safety. Recently, diffusion models…
Learning Car-Following Behaviors Using Bayesian Matrix Normal Mixture Regression
Chengyuan Zhang, Kehua Chen, Meixin Zhu +2
Learning and understanding car-following (CF) behaviors are crucial for microscopic traffic simulation. Traditional CF models, though simple, often lack generalization capabilities…