Driver style plays a key role in influencing stability in heterogeneous traffic flow. This study aims to explore the impact of different driver styles on heterogeneous traffic flow stability on the basis of a microscopic car-following model, namely, desired safety margin (DSM) model. The DSM model is used to portray the psychological behavior, operation behavior, and performance of the driver in terms of response time by using five driving behavior parameters, namely, the upper and lower limits of the DSM, sensitivity coefficient of acceleration and deceleration, and response time. Driving behavior characteristics would cause a dynamic phase transition for single-lane traffic flow. Five driving behavior characteristics constitute driver style in this paper. Analytical results indicate that driver 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 numerical simulation experiments. Therefore, increasing the proportions of responsive, sensitive, and risk-averse driver 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 driver styles when all the drivers are stable. However, if a platoon has stable and unstable drivers, then the proportion of drivers with different driver 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 driver styles and their proportions.

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