Mixed traffic flow characteristics analysis under different proportion of autonomous vehicles

Lin Wang; Yuqi Guo; Yanyue Liu; Jierui Zhu

doi:10.1117/12.3015696

20 February 2024 Mixed traffic flow characteristics analysis under different proportion of autonomous vehicles

Lin Wang, Yuqi Guo, Yanyue Liu, Jierui Zhu

Proceedings Volume 13064, Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023); 1306439 (2024) https://doi.org/10.1117/12.3015696
Event: 7th International Conference on Traffic Engineering and Transportation System (ICTETS 2023), 2023, Dalian, China

Abstract

In the paper, the simulation approach is proposed to analyze traffic flow characteristics under different mixed traffic scenarios. Firstly, the Intelligent Driver Model and Krauss models are chosen as the autonomous vehicle car-following model and manual vehicle one, and the models are described in detail. What’s more, the simulation of urban mobility (SUMO) software is applied to build three different types of highway scenarios, the two models are distinguished by setting different parameters. Finally, simulation program is run for each scenario, and the autonomous vehicles proportion increases gradually from 10% to 90% at the rate of 10%. The analysis results show that the average speed on the road increased as the proportion of autonomous vehicles increased, the conclusion proves that autonomous vehicles can improve road efficiency.

Citation Download Citation

Lin Wang, Yuqi Guo, Yanyue Liu, and Jierui Zhu "Mixed traffic flow characteristics analysis under different proportion of autonomous vehicles", Proc. SPIE 13064, Seventh International Conference on Traffic Engineering and Transportation System (ICTETS 2023), 1306439 (20 February 2024); https://doi.org/10.1117/12.3015696

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