MRI: Acquisition of Connected Autonomous Vehicles (CAV) Infrastructure to Support Cooperative Human-Robot Driving and Pedestrian Safety

University Of Nevada Las Vegas, Las Vegas NV

Investigators

Abstract

This project funds the creation of the University of Nevada, Las Vegas (UNLV) Mixed Driving (MixeD) “living laboratory” through the purchase and deployment of advanced environmental sensors and vehicle-to-everything (V2X) communication equipment. The equipment will augment UNLV’s basic automated vehicle demonstration platform and equip at least three intersections adjacent to campus with high-resolution cameras, radars, and lidars and V2X communication for collaborative vehicle-infrastructure sensing and safety. The equipment will enable new research in connected and autonomous vehicles (CAVs), with emphasis on artificial intelligence (AI) that can support the transition from human drivers to fully self-driving cars, and provides a real-world testbed for the research. While significant advances have been made in environmental sensing from a vehicle or infrastructure, much less work has focused on their cooperation and collaboration. This project will consider how V2X connectivity can enable sharing of information between vehicles and infrastructure and how to develop AI algorithms that take advantage of the strengths of each – e.g., high resolution measurements from a vehicle with the high availability and behavior diversity observable from infrastructure. The research will consider i) collaborative vehicle-infrastructure sensing and control, ii) on-road behavior modeling for better understanding of human actions for less conservative and more natural CAV operation in mixed traffic situations, iii) computer vision-based AI algorithm development for continual adaption, and iv) real-time, continuous characterization of safety at intersections through trajectory analysis. The MixeD project will promote collaboration between future automated vehicles and humans and enable safer and more natural interactions. The research will explicitly consider human behavior and intentions rather than rules-of-the-road to ensure safety to improve the safety of CAVs around pedestrians and other vulnerable road users. As a Minority- and Hispanic-Serving Institution, project will provide UNLV’s diverse student population with technical skills and unique learning and training experience in the growing areas of self-driving cars, AI, and computer vision. Full project details, including publications, datasets, and code, are available at https://MixeD.sites.unlv.edu. The website will be maintained for at least five years. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.