智能公交无人场站场景构建及调度策略研究

Research on scene construction and scheduling strategy of intelligent bus unmanned station

针对无人公交场站通行效率低、调度不规律等问题,提出无人场站虚拟场景的构建方法,建立车-路-云一体化环境下的无人公交调度仿真平台。根据高精卫星地图和场站内部场景要素尺寸、位置等信息,利用PreScan软件构建无人场站场景模型,利用Trucksim软件构建车辆整车模型和横纵向动力学模型;考虑无人公交电池荷电状态(state of charge,SOC)、场站内部充电位和停车位的分布情况,设计了无人公交场站全局调度策略,确定无人公交停车、充电方案和充电标准,基于改进的Dijkstra算法规划无人公交行驶路径。为验证该场景模型及调度规划策略的有效性,基于PreScan、Trucksim和Matlab/Simulink构建无人场站综合仿真平台,结合实车传感器采集的行驶信息,验证了该平台的可靠性。通过综合仿真平台数据和实车测试数据对比可得,无人场站整体通行效率提高了14.30%。

Aiming at the problems of low traffic efficiency and irregular scheduling of unmanned bus stations,a method of constructing virtual scenes of unmanned bus stations is proposed,and an unmanned bus scheduling simulation platform under the integrated environment of vehicle-road-cloud is established.According to the highprecision satellite map and the information of the size and location of the scene elements inside the station,the PreScan software is used to construct the scene model of the unmanned station,and the Trucksim software is used to construct the vehicle model and the lateral and longitudinal dynamics model.Considering the state of charge(SOC)of the unmanned bus battery and the distribution of charging and parking places in the station,the global scheduling strategy of the unmanned bus station is designed.The parking and charging schemes and charging standard of the unmanned bus are determined,and the driving path of the unmanned bus is planned based on the improved Dijkstra algorithm.In order to verify the effectiveness of the scene model and the scheduling planning strategy,the comprehensive simulation platform of the unmanned station is constructed based on Prescan,Trucksim and Matlab/Simulink,and the reliability of the platform is verified by combining the driving information collected by the real vehicle sensors.By comparing the comprehensive simulation platform data with the real vehicle test data,the overall traffic efficiency of the unmanned station is improved by 14.30%.