协同自适应巡航车辆混合交通流的lighhill - whitham - richards模型

Yanyan Qin, Hao Wang, Daiheng Ni
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引用次数: 30

摘要

未来,道路交通将包括手动车辆和协作式自适应巡航控制(CACC)车辆的随机组合,当车辆之间的通信不可用时,CACC车辆将降级为自适应巡航控制(ACC)车辆。本文提出了不同CACC渗透率下的混合车流lighhill - whitham - richards (LWR)模型的广义框架。该方法从理论上证明了通过混合排的运动波速为混合基本图的斜率。此外,从CACC到ACC的随机退化被捕获在交通场景的数学期望中,其中CACC只监视前面的一辆车。以智能驾驶员模型(IDM)和先进交通和公路合作伙伴(PATH)项目验证的CACC/ACC模型为例,研究了小扰动和冲击波的传播。并对选定的车辆跟随模型进行了数值模拟。并将所导出的混合LWR模型应用于求解一些交通流问题。结果表明,所提出的低波比模型能够很好地描述小扰动和激波的传播特性。混合LWR模型还可以用于解决一些实际问题,如交通事故引起的排队和移动瓶颈的影响。更重要的是,本文提出的广义框架允许其他CACC/ACC/常规汽车跟随模型,包括那些从进一步的实验中发展出来的模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lighthill-Whitham-Richards Model for Traffic Flow Mixed with Cooperative Adaptive Cruise Control Vehicles
In the future, road traffic will incorporate a random mix of manual vehicles and cooperative adaptive cruise control (CACC) vehicles, where a CACC vehicle will degrade to an adaptive cruise control (ACC) vehicle when vehicle-to-vehicle communications are not available. This paper proposes a generalized framework of the Lighthill-Whitham-Richards (LWR) model for such mixed vehicular flow under different CACC penetration rates. In this approach, the kinematic wave speed propagating through the mixed platoon was theoretically proven to be the slope of mixed fundamental diagram. In addition, the random degradation from CACC to ACC was captured in mathematical expectation for traffic scenarios where the CACC only monitors one vehicle ahead. Three concrete car-following models, the intelligent driver model (IDM) and CACC/ACC models validated by Partners for Advanced Transit and Highways (PATH) program, were selected as examples to investigate the propagation of small perturbations and shock waves. Numerical simulations were also performed based on the selected car-following models. Moreover, the derived mixed LWR model was applied to solve some traffic flow problems. It indicates that the proposed LWR model is able to describe the propagation properties of both small perturbations and shock waves. The mixed LWR model can also be used to solve some practical problems, such as the queue caused by a traffic accident and the impact of a moving bottleneck. More importantly, the proposed generalized framework admits other CACC/ACC/regular car-following models, including those developed from further experiments.
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