智能网联卡车车队混合流通行能力分析方法

智能网联卡车车队有望成为网联自动驾驶率先应用的场景之一，本文针对智能网联卡车车队混合交通流通行能力开展研究。首先，以智能网联卡车车队、人工驾驶卡车及人工驾驶小汽车构成的随机混合交通流为研究对象，考虑智能网联卡车车队规模空间分布特征，分析混合交通流中10种跟驰行为类型，理论推导其概率表达式，进而构建智能网联卡车车队混合交通流通行能力的通用性分析方法。然后，考虑实际交通流运行中卡车分布的随机性，将智能网联卡车车队混合交通流分为优势流、随机流和劣势流3种态势，以此提升混合交通流通行能力分析方法的普适性。最后，选择实测数据标定的跟驰模型进行案例分析，验证理论分析方法的有效性。研究结果表明：智能网联卡车比例提高或其车队规模增大均有利于3种态势混合交通流中车辆转换系数及相对熵的减小，从而可有效提升混合交通流通行能力。不同智能网联卡车比例条件下，智能网联卡车车队随机分布最优车队规模为2~4辆，同时，优势流、随机流和劣势流3种混合交通流通行能力依次递减。研究结果揭示了智能网联卡车车队混合交通流通行能力提升的内在机理，为未来智能网联卡车车队的运营管理提供方法支撑。

Capacity Analysis Method of Mixed Flow with Connected and Automated Truck Platooning

Connected and automated truck platooning is expected to be one of the first scenarios for the application of connected and automated driving. This paper studies the traffic capacity of mixed traffic flow of connected and automated truck platooning, where the random mixed traffic flow is composed of connected and automated trucks, manual trucks, and cars. Firstly, this paper analyzes 10 types of car- following behavior in the mixed traffic flow considering the spatial distribution characteristics of the scale of connected and automated truck platooning, develops its probability expression, and then constructs a general capacity analysis method of the mixed traffic flow. Then, considering the randomness of truck distribution in the actual traffic flow operation, the mixed traffic flow of connected and automated truck platooning is divided into three situations: dominant flow, random flow, and inferior flow to improve the universality of the mixed traffic flow capacity analysis method. Finally, the connected and automated truckfollowing model calibrated by the measured data is selected for case analysis to verify the effectiveness of the theoretical analysis method. The results show that the increase of the proportion of connected and automated trucks, or the increase of its platooning size, are conducive to the reduction of vehicle conversion coefficient and relative entropy in the mixed traffic flow of the three situations, which can effectively improve the traffic capacity of the mixed traffic flow. Under different conditions such as the proportion of connected and automated trucks, the optimal platooning size of connected and automated truck platooning randomly distributed is 2~4 vehicles. At the same time, the trafficcapacity of three mixed traffic flows, i.e., dominant flow, random flow, and inferior flow, decreases in turn. The research results reveal the internal mechanism of improving the capacity of mixed traffic flow of connected and automated truck platooning and provide methodological support for the operation and management of intelligent network truck platooning in the future.