Simulation Research of Automated Vehicles on Urban Expressway Capacity Under Traffic Accidents

Urban expressway is the artery of urban traffic, and traffic accidents on it will cause traffic congestion in sections and even in the road network. At present, automated vehicles (AV) is gradually adopted, which has great potential in optimizing road capacity. This paper focuses on how the utilization of autonomous vehicle affects the road capacity after traffic accidents. Firstly, in order to make VISSIM simulation closer to the reality, the actual speed of vehicles at the intersection of lane change in Singapore is collected to obtain the real data of driving behavior. Next, the expected speed, deceleration area and traffic flow of each section are obtained to establish the simulation model of the accident, and then the driving behavior model is set as the human-driver model and three AV models (cautious, normal, aggressive) created by CoEXist in VISSIM. At the same time, the project inputs aggressive vehicles with penetration rates of 20%, 40%, 60% and 80% to study the impact of penetration rate of autonomous vehicle on road capacity.