Liu, Haoji (University of Virginia), Mu, Zeyu (University of Virginia), WANG, Zejiang (Oak Ridge National Laboratory), Park, B. Brian (University of Virginia)

Mixed Traffic Flow Performance Evaluation Considering Spatial Distribution of Mixed-Automated Vehicles

Scheduled for presentation during the Regular Session "Multi-autonomous Vehicle Studies, Models, Techniques and Simulations II" (FrAT10), Friday, September 27, 2024, 10:30−10:50, Salon 18

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC), September 24- 27, 2024, Edmonton, Canada

This information is tentative and subject to change. Compiled on October 3, 2024

Abstract

Adaptive cruise control (ACC) and cooperative ACC (CACC) systems for connected automated vehicles (CAVs) have been extensively developed over decades. However, the impact of the mixed-automated vehicle spatial distribution on mixed traffic flow performance considering different cruise controllers, particularly with the introduction of new CACC systems involving unconnected vehicles between two CAVs (CACCu), remains unclear. In this study, we modeled and evaluated the impact of different spatial distributions on mixed traffic flow. First, we developed car-following models for traditional human-driven vehicles (THVs) incorporating human reaction time, and for CAVs utilizing various cruise controllers including ACC, CACC, and CACCu, accounting for delayed vehicle dynamics. Then, numerical simulations were conducted to analyze the influence of mixed-automated vehicle spatial distribution, CAV penetration rate, and CAVs’ desired time gap on traffic flow performance. Evaluation measures for driving comfort, energy consumption, and travel efficiency were employed to assess the outcomes. Our findings indicate that solely pursuing the clustered distribution to form CACC platoons may not always be optimal due to potential traffic disturbances amplified by clustered THVs, contrasting with most existing research. Furthermore, implementing CACCu is proved to improve CAV connectivity utilization, resulting in enhanced traffic performance in terms of safety, comfort, energy efficiency, and travel efficiency.