SYNOPSIS
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. This presentation first discusses recent developments in vehicle automation with mixed traffic streams. The challenges and opportunities associated with AI/ML algorithm development and application for CAV operations will be identified. These include leveraging real-time data using AI/ML to improve safety, mobility, and efficiency, and to offer the capability to respond rapidly to changing traffic environments. In addition, the presentation will 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.
ABOUT THE SPEAKER
Dr. Samuel Labi is a professor at Purdue University’s Lyles School of Civil Engineering, and associate director of the USDOT Region 5 Center for Connected and Automated Transportation (CCAT). Dr. Labi’s research is guided by current and evolving trends on the civil infrastructure development landscape. His research clients include FHWA/Indiana DOT, USDOT, TRB (NCHRP), Rhode Island’s state attorney general, and Illinois’s Auditor General. He serves as assistant editor, editorial board member, or guest editor for journals including Computer-Aided Civil & Infrastructure Engineering, Safety Science, Infrastructure Systems, Risk & Uncertainty. He is the chair of ASCE’s Economics & Finance committee, secretary of TRB’s asset management committee. Dr. Labi’s major research awards include American Society of Tests and Materials (ASTM)’s Mather Award (2007) for outstanding paper in concrete materials, TRB’s K.B. Woods (2008) for outstanding journal paper in design & construction, ASCE’s Frank Masters Award (2014) for outstanding and innovative work in advancing the area of transportation systems, and TRB’s Grant Mickel (2018) award for outstanding journal paper in operations & maintenance.
Dr. Sikai (Sky) Chen is a Visiting Assistant Professor at the Center School of Civil Engineering at Purdue University, and Visiting Research Fellow at the Robotics Institute, School of Computer Science at Carnegie Mellon University. He received his Ph.D. in Civil Engineering with a focus on Computational Science & Engineering from Purdue University in August 2019 under the supervision of Dr. Samuel Labi. Dr. Chen’s research interests span both theoretical and applied aspects of artificial intelligence, data science, robotics, and optimization. His research application areas include connected and autonomous vehicles, transportation and infrastructure systems, human factors, smart cities, and cloud/fog/edge computing for large-scale network modeling and simulation. His Ph.D. dissertation, “Safety Implications of Roadway Design and Management: New Evidence and Insights in The Traditional and Emerging (Autonomous Vehicle) Operating Environments”, received the 2019 Best Civil Engineering Dissertation Award from Purdue University and Council of University Transportation Centers’ 2019 Milton Pikarsky Memorial Award (a national prize for best Ph.D. dissertation). Dr. Chen serves as co-PI for USDOT-funded research projects at CCAT. In addition, he is a member of two ASCE national committees: Connected & Autonomous Vehicle Impacts, and Economics & Finance.