Impact of connected and autonomous vehicles on traffic safety of mixed traffic flow: from the perspective of connectivity and spatial distribution

Abstract

Abstract Equipped with high driving automation and advanced communication technologies, connected and autonomous vehicles (CAV) are expected to possess a shorter reaction time and a wider vision, which are promising to improve traffic safety and efficiency. However, little attention has been paid to the effect of connectivity and spatial distribution on the safety performance of mixed traffic flow. In this paper, we attempt to investigate the impact of CAV on traffic safety considering these factors. To this end, a car-following model for CAV is proposed first. Then, the cooperative driving strategy for CAVs is designed. Precisely, the feedback gains of the information are adjusted in real-time and are designed based on the derived stability criterion of the mixed traffic flow. Microscopic simulations of mixed traffic flow in traffic oscillation are designed and conducted to explore how the distribution and connectivity of CAV affect the safety performance of mixed traffic flow. Simulation results show that increasing the penetration rate of CAV is promising to shift the safety performance of mixed traffic flow. In addition, the safety performance of mixed traffic flow is related to the spatial distribution and communication range of CAV. Besides, increasing communication range does not inevitably improve the safety performance of mixed traffic flow when the penetration rate of CAV is low. Moreover, it is also found from the spatial–temporal trajectory of the mixed traffic flow that introducing CAV can mitigate the propagation of the stop-and-go wave and increase the throughput.