Modeling and Simulation of Heterogeneous Traffic Flows Considering the Influence of Multiple Vehicles

To explore the operational characteristics of heterogeneous traffic flows composed of Human-Driven Vehicles (HDVs) and Connected and Autonomous Vehicles (CAVs), a simulation model considering the influence of multiple vehicles was established. This study employed the traditional Intelligent Driver Model (IDM) and the Minimizing Overall Braking Induced by Lane-changing Model (MOBIL) to depict the car-following and lane-changing behaviors of HDVs. Additionally, it integrated the variations in safety headway caused by CAVs and the communication among multiple vehicles to enhance the IDM and MOBIL models, thus describing the car-following and lane-changing behaviors of CAVs. As a result, a heterogeneous traffic flow model considering the influence of multiple vehicles was developed. Utilizing Matlab, numerical simulation experiments were conducted to investigate the operational characteristics of heterogeneous traffic flow. The findings reveal that an escalation in CAV penetration rate facilitates the enhancement of the maximum traffic capacity in heterogeneous traffic flow. Furthermore, the increase in traffic capacity becomes even more pronounced when the CAV penetration rate exceeds 0.4. Compared to the traditional IDM + MOBIL model, the improved model, which incorporates the influence of multiple vehicles, demonstrates superior homogeneity and stability in traffic flow. CAVs significantly enhance the stability of heterogeneous traffic flows, and as the CAV penetration rate further increases, they can effectively suppress the propagation and diffusion of disturbances. With an increase in CAV penetration rate, the peak lane-changing frequency of HDVs shows a declining trend, while the peak lane-changing frequency of CAVs exhibits an ascending trend. The research findings provide a theoretical basis for analyzing road capacity and contribute to traffic management and control. Moreover, they enrich the field of traffic flow theory.