Title:

Advancing Autonomous Driving: Scalable Testbeds and Seamless Simulation Frameworks

Abstract:

Autonomous driving research often struggles with the high costs and risks of real-world testing. ICAT and BlueICE provide practical solutions to these challenges by creating environments that make testing safer, more efficient, and accessible. ICAT offers a scalable indoor testbed for studying decentralized autonomy and vehicle communication, while BlueICE integrates diverse simulation tools into a unified framework, ensuring seamless data exchange and synchronization. Together, these platforms significantly enhance the ability to test and refine autonomous systems, contributing to the steady progress of intelligent transportation technologies.

Bio:

William He is currently a 4th year Ph.D student working with Prof. Weisong Shi in the Connected and Autonomous Research (CAR) Lab in the Computer Science Department at the University of Delaware. His research is primarily at the intersection of Autonomous Driving and CyberPhysical Systems, focusing on building safe and reliable machine learning and simulation environments for autonomous vehicles and autonomous mobile robots. He has collaborated/worked with researchers from Autoware, Ford, Western Digital, Blue Halo, Leidos, Federal Highway Administration, and  Oak Ridge National Laboratory.