Cooperative Perception using Cellular V2X in Mixed Traffic Scenario

Abstract

The ultimate goal of connected autonomous vehicles (CAVs) is to provide traffic accident-free, road capacity, and mobility service. The CAVs are supported by vehicle-to-everything (V2X) communication to achieve those goals. The 3rd Generation Partnership Project (3GPP) standardizes the V2X called cellular V2X (C-V2X). In the real application, the CAVs should deal with mixed traffic scenarios during its penetration in the highways. The term mixed traffic refers to the traffic that consisted of human driving and CAVs. This paper considers that human driving is an unconnected vehicle and has a jerky driving behavior. Hence, when the CAVs interacted with human driving vehicles, CAVs required large spacing between vehicles to provide safety and comfortable driving. It will sacrifice the road capacity where the spacing between vehicles is large. This paper proposes the cooperative perception strategy using C-V2X to mitigate the adverse effect of unconnected vehicles without sacrificing safety and comfortable driving. The errors during transmission such as propagation error, half-duplex error, packet sensing ratio error, and message collision are considered. The effectiveness of our cooperative strategy is demonstrated by a joint simulation of Matlab/Simulink and PreScan.