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Modeling the heterogeneous traffic flow considering the effect of self-stabilizing and autonomous vehicles |
Yuan Gong(公元) and Wen-Xing Zhu(朱文兴)† |
School of Control Science and Engineering, Shandong University, Jinan 250061, China |
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Abstract With the increasing maturity of automatic driving technology, the homogeneous traffic flow will gradually evolve into the heterogeneous traffic flow, which consists of human-driving and autonomous vehicles. To better study the characteristics of the heterogeneous traffic system, this paper proposes a new car-following model for autonomous vehicles and heterogeneous traffic flow, which considers the self-stabilizing effect of vehicles. Through linear and nonlinear methods, this paper deduces and analyzes the stability of such a car-following model with the self-stabilizing effect. Finally, the model is verified by numerical simulation. Numerical results show that the self-stabilizing effect can make the heterogeneous traffic flow more stable, and that increasing the self-stabilizing coefficient or historical time length can strengthen the stability of heterogeneous traffic flow and alleviate traffic congestion effectively. In addition, the heterogeneous traffic flow can also be stabilized with a higher proportion of autonomous vehicles.
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Received: 16 August 2021
Revised: 24 September 2021
Accepted manuscript online: 29 September 2021
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PACS:
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45.70.Vn
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(Granular models of complex systems; traffic flow)
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05.70.Fh
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(Phase transitions: general studies)
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05.70.Jk
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(Critical point phenomena)
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89.40.-a
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(Transportation)
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Fund: Project supported by the National Natural Science Foundation of China (Grant No. 61773243), the Major Technology Innovation Project of Shandong Province, China (Grant No. 2019TSLH0203), and the National Key Research and Development Program of China (Grant No. 2020YFB1600501). |
Corresponding Authors:
Wen-Xing Zhu
E-mail: zhuwenxing@sdu.edu.cn
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Cite this article:
Yuan Gong(公元) and Wen-Xing Zhu(朱文兴) Modeling the heterogeneous traffic flow considering the effect of self-stabilizing and autonomous vehicles 2022 Chin. Phys. B 31 024502
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