面向新型混合交通流的快速路合流区通行能力建模

面向人类驾驶和具备协同自适应巡航功能的网联自动驾驶组成的新型混合交通流，考虑道路交通特性、道路结构以及匝道汇入前主线交通状态等因素的交互作用机理，基于概率统计理论解析网联自动驾驶渗透率和编队长度间的耦合关系，进一步基于间隙接受理论分析匝道汇入交通对合流区通行能力的折减效应，建立快速路合流区通行能力模型，定量描述不同道路条件下合流区通行能力如何随网联自动驾驶渗透率和编队长度变化。模型中的道路交通特性、道路结构及匝道汇入前部分交通状态参数根据实际道路交通环境标定，提升了模型的通用性与可迁移性。搭建内嵌车辆动力学模块的Vissim仿真平台进行模型评估，结果表明，模型精度在80%以上，且在不同网联自动驾驶渗透率和编队长度条件下皆表现良好。 

A Capacity Model of Freeway Merging Areas with Partially Connected Automated Traffic

A capacity model is developed to study freeway merging areas of a novel mixed traffic with human-driven vehicles and connected automated vehicles equipped with cooperative adaptive cruise control. The interaction mechanism of factors, such as road traffic characteristics, road structure, and mainline traffic state before the merge, is considered. The probability and statistics theory is used to analyze coupling relationships between penetration rate and platoon length. Furthermore, based on the gap acceptance theory, reduction effects of ramp merging traffic on the capacity of the merging area is analyzed. The capacity model of freeway merging areas with partially connected automated traffic is established to quantitatively describe how the capacity changes with the penetration rate and platoon length of connected automated vehicles under various road conditions. The parameters of road traffic characteristics, road structure, and part of the traffic state before the ramp merge are calibrated according to the actual traffic condition, which improves versatility and transferability of the model. A Vissim simulation platform with an embedded vehicle dynamics module is developed to evaluate the model. The results show that the accuracy of the model is generally over 80%. The model performed well under various penetration rates and platoon lengths of connected automated vehicles.