基于人车路协同的智能交通出行信息服务系统

An intelligent traffic travel information service system based on human⁃vehicle⁃road coordination

近年来,智能交通信息服务受到广泛的关注,针对数据实时性和准确性差、信息交互共享难问题,设计了一种人车路协同的智能交通出行信息服务系统,形成人车路智能协同的工作环境。为解决智能交通结构化多源信息融合,提出了一种由卡尔曼(Kalman)滤波和D⁃S(Dempster/Shafer)证据理论两种信息融合模型——KD⁃SF模型,发现采用KD⁃SF模型信息融合结果与GPS车载采集实际测试数据近似相同,信息融合更精确。通过系统应用验证表明,人车路协同系统与交通服务信息融合后,在高峰时段公交线路平均运行车速明显提升,乘客平均候车时间明显缩短,提高城市公共交通运行效率。

Intelligent traffic information services have received extensive attention recently,but they still hold some problems,like poor real time capability,low accuracy of data,and ineptitude of exchanging and sharing information.This paper proposes an intelligent traffic travel information service system with human⁃vehicle⁃road coordination to establish a framework of intelligent human⁃vehicle⁃road collaboration surroundings.In this system,a KD⁃SF model is designed based on the Kalman filter and the Dempster/Shafer evidence theory to integrate the structural multi⁃source information for the intelligent transportation.Simulation results demonstrate that the KD⁃SF model can output the same results as the actual test data collected by the GPS vehicle,and its information fusion is more accurate.The application tests reveals that integrating the human⁃vehicle⁃road coordination system into the traffic service information system can significantly improve the average operating speed of the bus lines during peak hours and shorten the average waiting time of passengers,thus the efficiency of the urban public transportation is improved.