A Micro Simulator Analysis of Mixed Traffic Flow of Autonomous and Manually Driven Vehicles

Abstract

Although autonomous vehicles (AVs) are expected to improve the safety and speed of traffic flow, traffic speed may decrease because of the mixture of AVs, manually driven vehicles, and public transportation. In this study, we analyze the impact of the mixture on traffic flow through a multimodal micro traffic simulator. We conducted a traffic survey on vehicles, buses, and trams in downtown Kumamoto, Japan. Subsequently, the survey results were used to develop a multimodal traffic simulator used to analyze the effect of the mixture of vehicles and the settings of parameters in the driving-behavior model on multimodal traffic flow. Simulation results revealed that the increased share of AVs improved the average speed of traffic flow. However, the average speed of trams decreased owing to increased AVs. Therefore, we also conducted a simulation to verify that a change in the intersection structure and signal control can prevent the decrease in the speed of trams.