Research Review with Sikai (Sky) Chen, Ph.D.
Speaker(s): Sikai (Sky) Chen, Ph.D., Post-Doctoral Researcher, Center for Connected and Automated Transportation (CCAT)
Presentation Title: Using AI to Improve CAV Operations in Mixed Traffic
Date/Time: Tuesday, November 9th, 2021 | 12:00 PM ET
Abstract: Rapid advances in artificial intelligence and machine learning (AI/ML) offer unprecedented opportunities for improving the operations of connected and autonomous vehicles (CAVs) in a traffic stream that also includes human-driven vehicles. Dr. Sikai (Sky) Chen will discuss recent developments in vehicle automation with mixed traffic streams, including the challenges and opportunities associated with AI/ML algorithm development and application for CAV operations. These include leveraging real-time data using AI/ML to improve safety, mobility, and efficiency, and rapidness of response to changing traffic environments. Dr. Chen will also discuss AI/ML cooperative control algorithms for multi-agent systems that consider dynamic interactions between heterogeneous system users (e.g., human drivers, connected and/or automated vehicles). Results from extensive simulation experiments will be presented to demonstrate the effectiveness of such cooperative control innovations. Insights from this research can provide guidance to CAV manufacturers and transport agencies regarding infrastructure investments specifically for CAV operations.
Dr. Chen is a member of two ASCE committees: Connected and Autonomous Vehicle Impacts, and Economics and Finance. His recently published award-winning thesis addressed the safety implications of roadway design and management, specifically examining new evidence and insights in the traditional and emerging (autonomous vehicle) operating environments. His research interests include transportation infrastructure systems evaluation, roadway safety, and policy analysis, and applications of machine learning and data mining in transportation and infrastructure systems. His current research at CCAT and the Robotics Institute focuses on deep learning, intelligent transportation systems, vehicle automation, simulation, and control.