摘要
为了探究城市路网中混有智能网联车辆(CAV)的交通流特性,研究CAV不同渗透率分布下对路网通行能力的影响。应用智能驾驶模型(IDM)和协同自适应巡航控制模型(CACC)分别作为人工驾驶车辆(HDV)和智能网联车辆的纵向速度更新规则,并建立考虑车辆到信号交叉口距离影响的横向换道规则。推导基于各渗透率等级路段占路网长度比例下的混合交通宏观基本图模型(MFD),通过SUMO仿真验证模型有效性。最后针对模型中的比例参数进行敏感性分析。结果表明:混合交通MFD可以用于异质交通流组成的城市路网宏观交通状态的有效估计与通行能力分析。当CAV渗透率均匀时,在路段渗透率高于30%时,路网通行能力提升显著;当CAV渗透率非均匀时,异质路网的通行能力随着渗透率等级较高路段比例的增加而逐渐提高,100%CAV路段比例的影响尤为显著。混合交通MFD为混有CAV的城市交通调控和CAV在路网中的路径规划提供理论参考。
In order to explore traffic flow characteristics of urban networks mixed with connected automated vehicles(CAV),the impacts of different penetration distribution of CAV on traffic capacity is studied.The intelligent driver model(IDM)and cooperative adaptive cruise control(CACC)model are used as longitudinal speed update rules for Human Driven Vehicles(HDV)and CAV respectively,and lateral lane-changing rules additionally considering the distance between vehicles and signalized intersections,are established.A mixed traffic MFD is derived based on the length proportion of road segments with different penetration rates to the total road network,and its validity is verified via SUMO simulation.Finally,sensitivity analyses on scale parameters are carried out.The experiment results show that the proposed mixed traffic MFD is suitable for the estimation of macroscopic traffic state and analysis on traffic capacity of heterogeneous urban network.If the CAV penetration rate is uniform,the traffic flow capacity is significantly improved when the rate is higher than 30%;if the rate is non-uniform,the capacity gradually increases when the segment proportion with higher penetration grade tends to be greater,especially for 100%CAV segments.The proposed mixed traffic MFD can provide a theoretical reference for both urban traffic control mixed with CAV and route planning of CAV.
作者
王伊欣
张希
刘冶
WANG Yi-xin;ZHANG Xi;LIU Ye(School of Mechanical Engineering,Shanghai Jiaotong University,Shanghai 200240,China)
出处
《公路》
北大核心
2022年第3期225-231,共7页
Highway
基金
国家重点研发计划,项目编号2019YFE0100200。
关键词
交通工程
智能网联车辆
通行能力
宏观基本图模型
渗透率
SUMO仿真
traffic engineering
CAV
traffic capacity
macroscopic fundamental diagram model
penetration rate
SUMO simulation
