Desired Safety Margin Model-Based Exploration of Driver Style Effect on Heterogeneous Traffic Flow

摘要

Driving style plays a key role in influencing stability of traffic in heterogeneous traffic flow. This study aims to explore the impact of different driving styles on heterogeneous traffic flow stability on the basis of a microscopic car-following model, namely, the desired safety margin (DSM) model. The DSM model is used to portray the psychological behavior, operational behavior, and performance of the driver in terms of response time. This is calculated by using five driving behavior parameters, the upper and lower limits of the DSM, sensitivity coefficient of acceleration and deceleration, and the response time. Characteristics of driving behavior would cause a dynamic phase transition for single-lane traffic flow. Five characteristics of driving behavior are mapped out in this paper. Analytical results indicate that driving styles and their proportions play a key role on the stability of heterogeneous traffic flow. In this study, we found that a driver who is responsive, sensitive, and risk-averse is stable, and a driver who is unresponsive, insensitive, and risk-prone is unstable based on the results of numerous simulation experiments. Therefore, increasing the proportions of responsive, sensitive, and risk-averse driving styles and decreasing the proportions of unresponsive, insensitive, and risk-prone driver styles can help improve heterogeneous traffic flow stability. Moreover, the traffic flow is always stable regardless of the proportions of the driving styles when all the drivers are stable. However, if a platoon has stable and unstable drivers, then the proportion of drivers with different driving styles plays a key role in traffic flow stability. These results are useful in developing a traffic control strategy to stabilize traffic flow by adjusting driving styles and their proportions.