Simulation of mixed traffic with cooperative lane changes

Abstract

AbstractThis study proposes a mixed traffic simulation framework that integrates vehicle car‐following (CF) and lane‐changing (LC) with connected and automated vehicles (CAVs) of different cooperation behaviors. This framework is centered at a CAV LC model incorporated with CF dynamics in mixed traffic. The model was calibrated and validated using data collected from small‐scale field experiments in a previous study. To demonstrate a large‐scale application of this framework, PTV Vissim was used to implement the framework on a segment of Interstate 75 highway. Sensitivity analyses were conducted to investigate the impacts of key parameters on traffic mobility and stability performance. The results show that traffic performance degraded as the traffic demand and vehicle diverging rate increased. As the CAV penetration rate increased, traffic performance fluctuated when CAVs were more conservative. As the CAV cooperation rate, incentive criterion threshold, and incentive criterion bias increased, mobility and stability performance first improved and then degraded. When CAV platooning was considered, traffic performance was enhanced. These findings shed light on mixed traffic management from the perspectives of both transportation operators (e.g., facilities and policies to promote vehicle cooperation) and automakers (e.g., tuning parameters in their LC models) to achieve the best traffic performance.