Abstract: Due to the advanced Internet of vehicles and autonomous driving technology, connected autonomous vehicles (CAVs) can adopt a new mode of traffic organization (i.e., smart intersections) to significantly improve the efficiency of intersections. To reduce the total travel cost of urban traffic systems under mixed CAVs and human-driven vehicles (HVs), the layout optimization problem of smart intersections in the urban traffic network is proposed. A mathematical optimization model is established and used to solve the problem. First, based on the analysis of the driving characteristics of the two types of vehicles, a mixed user equilibrium model is established to formulate the path choice behavior of CAVs and HVs. Second, from the perspective of traffic planners, with the integration of a mixed user equilibrium model, a spatial layout optimization model of smart intersections is established for the urban traffic network under the novel mixed traffic flow. It takes system optimization as the optimization objective and is solved by an improved genetic algorithm. Finally, a set of numerical experiments based on the Sioux-Falls network is conducted to verify the validity of the model and algorithm. Besides, the influence of the penetration rate of CAVs on the optimization results is also analyzed. The results show that the rational planning of smart intersections in the urban traffic network can significantly improve the travel efficiency in the novel mixed traffic scenario. Moreover, it greatly reduces the gaps in travel efficiency between CAVs and conventional HVs due to CAVs' unilaterally technological advantages, which further improves traffic fairness.

Key words: urban traffic, layout planning of smart intersections, mathematical programming with equilibrium constraints, connected autonomous vehicle, novel mixed traffic flow, mixed user equilibrium

摘要： 考虑网联自动驾驶车辆(Connected Autonomous Vehicle, CAV)应用先进的车联网与自动驾驶技术，可以采用智能交叉口的组织形式，大幅提升交叉口的通行效率，为降低CAV与人工驾驶车辆(Human-driven Vehicle, HV)混行条件下城市交通系统的整体出行成本，提出智能交叉口在城 市交通网络中的布局优化问题，建立数学优化模型并求解。首先，基于对两类车辆行驶特性的分析，建立混合用户均衡模型，描述CAV与HV的路径选择行为；其次，从交通规划者的角度，以系统最优为目标，整合混合用户均衡模型，建立面向新型混合交通流的智能交叉口网络布局优化模型，并利用改进的遗传算法求解；最后，选取Sioux-Falls交通网络作为案例分析，验证模型与算法的有效性，并研究CAV渗透率变化对优化结果的影响。研究表明，智能交叉口在城市路网中的合理规划极大地提高了新型混行场景下城市交通系统的出行效率，同时，大幅降低了由于网联自动 驾驶单方面技术优势带来的CAV与HV的出行效率差距，增进了出行公平性。

关键词: 城市交通, 智能交叉口网络布局规划, 含均衡约束的数学规划, 网联自动驾驶, 新型混合交通流, 混合用户均衡