Exploring Shared Perception and Control in Cooperative Vehicle-Intersection Systems: A Review
Elham Yazdani Bejarbaneh, Haiping Du, Fazel Naghdy
Abstract
Road intersections will soon be congested with countless connected autonomous vehicles (CAVs) to meet a variety of transportation needs. In such an environment, CAVs will need to work together and coordinate with one another. Smart infrastructure should also be in place to enable CAVs to efficiently utilize shared intersection resources and carry out their mobility duties. The interaction among CAVs and between CAVs and infrastructure for efficient intersection management is facilitated by a key technology of intelligent transportation system (ITS), known as cooperative vehicle-intersection system (CVIS). Towards developing a better insight into this fast-developing technology, this study presents a thorough review of the state of the art in CVIS research in the context of three hierarchal layers of shared perception, intersection control, and vehicle control. To describe the workflow of cooperative perception systems, a systematic architecture of infrastructure-based perception supported by edge computing and multi-node multi-sensor fusion techniques is explored. Different shared perception methodologies, aiming at the perceptual fusion of CAVs and infrastructure to achieve comprehensive environmental perception are critically analyzed to identify the landscape of cooperative detection and tracking. With an emphasis on essential interaction between CAVs and infrastructure, various cooperative control strategies are then investigated for the co-design of crossing scheduling and motion control of multiple CAVs at intersections. The applications of CVIS in cooperative driving automation in terms of efficiency, safety, and sustainability are qualitatively analyzed. This paper concludes by identifying gaps and challenges in vehicle-intersection cooperation along with recommendations on future research directions.