Cooperative Vehicle Identification for Safe Connected Autonomous Driving

Abstract

5G connected autonomous vehicles (CAVs) is a key to address the challenges faced by autonomous driving with enhanced perception and cooperation on driving. To achieve reliable cooperation for safety critical CAV driving applications, an important but rarely studied issue is identifying communication vehicles of interests from sensed vehicles (ICSV). Wrong vehicle identification may cause unsafe driving decisions and lead to potential accidents. In this paper we study the ICSV problem for safe cooperative autonomous driving. We present a location based baseline method for ICSV and discuss its potential problems. Then we propose a cooperative method to improve reliability and accuracy. In the proposed method vehicle registration number (VRN) is used for vehicle identification. And multiple CAVs can cooperate on both sensing and identifying communication vehicles from their detected ones. VRNs can be hashed before sharing to protect privacy, and are compared to the shared ones for vehicle identification. Experiment results show that the approach is feasible and can have a very low false positive rate.