Demonstrations of Cooperative Perception: Safety and Robustness in Connected and Automated Vehicle Operations

• Main Authors: Mao Shan, Karan Narula, Yung Fei Wong, Stewart Worrall, Malik Khan, Paul Alexander, Eduardo Nebot
• Format: Article
• Language: English
• Published: MDPI AG 2021-12-01
• Series: Sensors
• Subjects: collective perception; cooperative perception; collective perception service; V2X communication; intelligent roadside unit; connected and automated vehicle
• Online Access: https://www.mdpi.com/1424-8220/21/1/200

Cooperative perception, or collective perception (CP), is an emerging and promising technology for intelligent transportation systems (ITS). It enables an ITS station (ITS-S) to share its local perception information with others by means of vehicle-to-X (V2X) communication, thereby achieving improved efficiency and safety in road transportation. In this paper, we present our recent progress on the development of a connected and automated vehicle (CAV) and intelligent roadside unit (IRSU). The main contribution of the work lies in investigating and demonstrating the use of CP service within intelligent infrastructure to improve awareness of vulnerable road users (VRU) and thus safety for CAVs in various traffic scenarios. We demonstrate in experiments that a connected vehicle (CV) can “see” a pedestrian around the corners. More importantly, we demonstrate how CAVs can autonomously and safely interact with walking and running pedestrians, relying only on the CP information from the IRSU through vehicle-to-infrastructure (V2I) communication. This is one of the first demonstrations of urban vehicle automation using only CP information. We also address in the paper the handling of collective perception messages (CPMs) received from the IRSU, and passing them through a pipeline of CP information coordinate transformation with uncertainty, multiple road user tracking, and eventually path planning/decision-making within the CAV. The experimental results were obtained with manually driven CV, fully autonomous CAV, and an IRSU retrofitted with vision and laser sensors and a road user tracking system.