Analytical studies on an optimized adaptive cruise control model of traffic flow based on self-stabilizing strategy

Zhipeng Li, Yingying Liu, Shangzhi Xu and Yeqing Qian
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Zhipeng Li: Information Processing and Intelligent, Transportation System Laboratory, P. R. China2Department of Information and Communication Engineering, Tongji University, Shanghai 200092, P. R. China3The Center of National Railway Intelligent Transportation, System Engineering and Technology, Beijing 100081, P. R. China
Yingying Liu: Information Processing and Intelligent, Transportation System Laboratory, P. R. China2Department of Information and Communication Engineering, Tongji University, Shanghai 200092, P. R. China3The Center of National Railway Intelligent Transportation, System Engineering and Technology, Beijing 100081, P. R. China
Shangzhi Xu: Information Processing and Intelligent, Transportation System Laboratory, P. R. China2Department of Information and Communication Engineering, Tongji University, Shanghai 200092, P. R. China3The Center of National Railway Intelligent Transportation, System Engineering and Technology, Beijing 100081, P. R. China
Yeqing Qian: Information Processing and Intelligent, Transportation System Laboratory, P. R. China2Department of Information and Communication Engineering, Tongji University, Shanghai 200092, P. R. China3The Center of National Railway Intelligent Transportation, System Engineering and Technology, Beijing 100081, P. R. China

International Journal of Modern Physics C (IJMPC), 2020, vol. 31, issue 04, 1-18

Abstract: Cooperative adaptive cruise control (CACC) system possesses more remarkable ability to suppress disturbance and enhance the traffic capacity than adaptive cruise control (ACC). However, CACC asks for strict requirement on wireless communication and precise equipment, which remains a big difficulty to implement. This paper extends a new ACC model by introducing the self-stabilizing control with historical data, aimed at achieving the close performance of CACC and make it practicable. Substituting real-time information with pre-stored data substantially reduces the technical demand and offers high reliability to withstand the network delay. Linear stability analysis for this model points out enhancing the value of the gain or time delay of self-stabilizing control benefits to stabilize the traffic. The theories are corroborated via the simulation and further numerical simulations explicate the impact on fuel consumption and emissions and traffic capacity.

Keywords: Adaptive cruise control; homogeneous traffic flow model; self-stabilizing control (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S0129183120500540

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