【摘要】 基于卡口数据,设计道路交通分析任务和数据挖掘算法,探索分析结果在宏观、中观、微观层面对城市交通规划、建设和管理的工程应用。基于所有车辆一日经过的卡口序列,提出毗邻区域交通量、车流轨迹和道路运行状况三大分析任务和技术方案。提出毗邻区域交通量概念,计算有道路连接的毗邻区域间的车流量,得到宏观路网交通量分布特征。采用频繁子序列挖掘算法得到满足特定条件的车辆群频繁经过的卡口集合和顺序,得到车辆群的活动范围和重要路径。基于车辆到达路段起点和终点的时间间隔,得到随着时间变化的路段车辆行程时间分布。以湖北省宜昌市为例阐述工程应用,总结提出卡口数据挖掘与道路交通分析系统框架。更多还原

【Abstract】 Based on traffic data collected by cameras, this paper introduces the traffic analysis method for roadway design and data mining algorithms, and explores their applications in urban transportation planning, infrastructure construction, and traffic management at macro, mesa, and micro levels. Based on the spatial and temporal sequences of vehicles, three analysis tasks and solution methods are proposed to obtain three important indexes, namely the traffic flow distribution among adjacent areas, vehicle trajectories,and the time-dependent traffic operations. The concept of traffic flow distribution among adjacent areas is proposed. It refers to the traffic volumes between two adjacent areas connected by roads, and it reveals the macroscopic distribution feature of traffic flows. The application of frequent sequence mining algorithms can identify the sequences of vehicle clusters passing by the data collection cameras, which reveals vehicle clusters travel areas and paths. Based on the vehicles entering and egressing time, the travel time by hour of the day can be calculated. Finally, taking Yichang city in Hubei province as a case study, the paper illustrates the data mining and road traffic analysis framework based on traffic camera data.更多还原