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A cellular automata model for mixed traffic flow considering the driving behavior of connected automated vehicle platoons
Physica A: Statistical Mechanics and its Applications ( IF 2.8 ) Pub Date : 2021-07-13 , DOI: 10.1016/j.physa.2021.126262
Yangsheng Jiang 1, 2, 3 , Sichen Wang 1 , Zhihong Yao 1, 2, 3, 4 , Bin Zhao 1, 2 , Yi Wang 1, 2
Affiliation  

With the development of automated driving technology and communication technology, the emergence of connected automated vehicles (CAVs) will significantly improve traffic efficiency and safety. To study the influence of connected automated vehicles (CAVs) on mixed traffic flow, this study proposes a cellular automata (CA) model of mixed traffic flow considering the driving behavior of the platoon of CAVs. Firstly, three car-following modes, Human-driven vehicle (HDV), Adaptive Cruise Control (ACC), and Cooperative Adaptive Cruise Control (CACC), in mixed traffic flow are analyzed. Secondly, on the bias of the safety distance model and platoon behavior analysis, the acceleration, deceleration, and randomization rules of the cellular automata model of mixed traffic flow are developed. The time step is introduced into the model in the rule design, and the reaction time of the vehicle is considered in the randomization rule. Finally, a numerical simulation is conducted to analyze the fundamental diagram of mixed traffic flow, traffic congestion, and speed volatility under different penetration rates of CAVs. The result shows that (1) the road capacity under the pure CAV environment has increased by 3.24 times compared with the pure HDVs; (2) the maximum congestion reduction percentage can reach 63.36%; and (3) when the penetration rate reaches 80%, the velocity fluctuation decreases significantly. Sensitivity analysis shows that when the penetration rate of CAVs is 100%, the maximum platoon size increase can improve the road capacity. Furthermore, the maximum platoon size has an optimal value in a specific density range.



中文翻译:

考虑联网自动驾驶车辆队列驾驶行为的混合交通流元胞自动机模型

随着自动驾驶技术和通信技术的发展,联网自动驾驶汽车(CAV)的出现将显着提高交通效率和安全性。为了研究联网自动驾驶汽车 (CAV) 对混合交通流的影响,本研究提出了一种考虑 CAV 队列驾驶行为的混合交通流元胞自动机 (CA) 模型。首先,分析了混合交通流中的三种跟驰模式,人类驾驶车辆(HDV)、自适应巡航控制(ACC)和协同自适应巡航控制(CACC)。其次,基于安全距离模型和队列行为分析的偏差,建立了混合交通流元胞自动机模型的加速、减速和随机化规则。在规则设计中将时间步引入模型中,并且在随机化规则中考虑了车辆的反应时间。最后,通过数值模拟分析了不同CAV渗透率下混合交通流、交通拥堵和速度波动的基本图。结果表明:(1)纯CAV环境下的道路通行能力比纯HDV提高了3.24倍;(2)最大拥塞减少率可达63.36%;(3)当穿透率达到80%时,速度波动显着减小。敏感性分析表明,当CAVs的渗透率为100%时,最大排量增加可以提高道路通行能力。此外,最大排大小在特定密度范围内具有最佳值。

更新日期:2021-07-23
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