A Safety-Driven Interpretable Model for Vehicle Control With Impact on Traffic

Xia Wang is a Ph.D. student in Computer Science at Vanderbilt University, where her research focuses on autonomous driving, cyber-physical systems, machine learning, formal methods, and intelligent transportation systems. Her work develops interpretable, safety-aware, and human-centered AI frameworks for autonomous vehicles, including knowledge-integrated end-to-end planning, adaptive cruise control classification, runtime monitoring, and logic-based safety verification. She has contributed to the CIRCLES 100-car open-road experiment and has published research at venues including ICCPS, ITSC, IV, RV, AAMAS, CVPR autopilot workshop and IEEE Control Systems Magazine. Her recent work on NeoAD explores how large-model reasoning, BEV representations, and formal safety robustness can improve autonomous driving planning under diverse and challenging scenarios.

Dr. Matthew Bunting is a Research Scientist at the Institute for Software Integrated Systems at Vanderbilt University. He joined Vanderbilt in 2022 having previously been a postdoctoral scholar at the University of Arizona from 2020-2022. His research is in embedded control software and visualization for cyber-physical systems.

Dan Work is a Chancellor Faculty Fellow and professor in civil and environmental engineering, computer science, and the Institute for Software Integrated Systems at Vanderbilt University.

Professor of Computer Science at Vanderbilt University. Research in cyber-physical systems, autonomous vehicles, and domain-specific modeling.