Equipped with high driving automation and advanced communication technologies, connected and autonomous vehicles (CAV) areexpected to possess a shorter reaction time and a wider vision,which are promising to improve t...Equipped with high driving automation and advanced communication technologies, connected and autonomous vehicles (CAV) areexpected 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. Inthis paper, we attempt to investigate the impact of CAV on traffic safety considering these factors. To this end, a car-following modelfor CAV is proposed first. Then, the cooperative driving strategy for CAVs is designed. Precisely, the feedback gains of the informationare adjusted in real-time and are designed based on the derived stability criterion of the mixed traffic flow. Microscopic simulations ofmixed traffic flow in traffic oscillation are designed and conducted to explore how the distribution and connectivity of CAV affect thesafety performance ofmixed traffic flow. Simulation results show that increasing the penetration rate of CAV is promising to shift thesafety performance ofmixed traffic flow. In addition, the safety performance of mixed traffic flow is related to the spatial distributionand communication range of CAV. Besides, increasing communication range does not inevitably improve the safety performance ofmixed traffic flow when the penetration rate of CAV is low. Moreover, it is also found from the spatial–temporal trajectory of themixedtraffic flow that introducing CAV can mitigate the propagation of the stop-and-go wave and increase the throughput.展开更多
基金National Natural Science Foundation of China(Grant No.61973028).
文摘Equipped with high driving automation and advanced communication technologies, connected and autonomous vehicles (CAV) areexpected 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. Inthis paper, we attempt to investigate the impact of CAV on traffic safety considering these factors. To this end, a car-following modelfor CAV is proposed first. Then, the cooperative driving strategy for CAVs is designed. Precisely, the feedback gains of the informationare adjusted in real-time and are designed based on the derived stability criterion of the mixed traffic flow. Microscopic simulations ofmixed traffic flow in traffic oscillation are designed and conducted to explore how the distribution and connectivity of CAV affect thesafety performance ofmixed traffic flow. Simulation results show that increasing the penetration rate of CAV is promising to shift thesafety performance ofmixed traffic flow. In addition, the safety performance of mixed traffic flow is related to the spatial distributionand communication range of CAV. Besides, increasing communication range does not inevitably improve the safety performance ofmixed traffic flow when the penetration rate of CAV is low. Moreover, it is also found from the spatial–temporal trajectory of themixedtraffic flow that introducing CAV can mitigate the propagation of the stop-and-go wave and increase the throughput.
