Intelligent connected vehicles (ICVs) are recognized as a new sustainable transportation mode, which could be promising for reducing crashes. However, the mixed traffic consisting of manually driven vehicles and ICVs may negatively affect road safety due to individual heterogeneity. This study investigated heterogeneity effects on freeway safety-based simulation experiments. Two types of vehicle dynamic models were employed to depict dynamic behaviors of manually driven vehicles and adaptive cruise control (ACC) vehicles (a simplified version of ICVs), respectively. Real vehicle trajectories were utilized to calibrate model parameters based on genetic algorithms. Surrogate safety measures were applied to establish the relationship between vehicle behaviors and longitudinal collision risks. Simulation results indicate that the heterogeneity has negative effects on longitudinal safety. With the higher degree of heterogeneity, longitudinal collision risks are increased. Compared to traffic flow consisting of human drivers only, mixed traffic flow may be more dangerous when the market penetration rate of ACC is low, since the ACC system can be recognized as a new source of individual heterogeneity. Findings of this study show that necessary countermeasures should be developed to improve safety for mixed traffic flow from the perspective of transportation safety planning in the near future.

Variable speed limit (VSL) control is an effective technology to improve safety near freeway bottlenecks. This study aims to develop a control strategy for mixed traffic flow consisting of both human-driven vehicles (HDVs) and connected and automated vehicles (CAVs) based on collision avoidance theory. A microscopic simulation platform is first established, and four vehicle longitudinal dynamic models including Cruising model, Intelligent Driver Model (IDM), Adaptive Cruise Control model (ACC), Cooperative Cruise Control model (CACC) and one vehicle lateral dynamic model Minimizing Overall Braking Induced by Lane Changes model (MOBIL) are incorporated into the simulation platform. Then, a new VSL control strategy derived from collision avoidance theory is proposed for mixed traffic flow at the initial stage of CAVs’ popularization. Extensive simulation experiments are conducted, and surrogate safety measures and total travel time indicators are utilized to evaluate the safety and efficiency performances of the proposed VSL control. Results indicate that the proposed VSL control strategy can effectively improve the safety performance near freeway bottlenecks with an acceptable efficiency level.