Autonomous Mobility Research / Applications Autonomous Mobility — where we apply it Autonomous vehicles are reshaping how people and goods move. INSPIRE Lab studies how to understand autonomous vehicle behavior in real traffic, coordinate connected and autonomous vehicles to improve mobility and safety, and prepare for the rise of autonomous trucking. Problems We Tackle — three core challenges Problem 01 AV Behavior Understanding Identifying and classifying autonomous vehicle behaviors in real-world traffic to support safety analysis and policy. Problem 03 Autonomous Trucking Preparing for the next generation of self-driving heavy-duty vehicles in long-haul freight operations. Featured Publications — recent highlights Preprint · 2025 SVBRD-LLM: Self-Verifying Behavioral Rule Discovery for Autonomous Vehicle Identification Li, Wang, Jiao, Claudel & Guo Preprint · 2026 LLM-MLFFN: Multi-Level Autonomous Driving Behavior Feature Fusion via Large Language Model Li, Wang, Cheng, Machineni, Guo, Chen, Jiao & Claudel Transportmetrica B · 2025 Optimal Speed Limit Control for Network Mobility and Safety: A Twin-Delayed Deep Deterministic Policy Gradient Approach Afifah & Guo Full Publication List →
