考虑不同出口转向的城市道路行程时间估计  

Estimation of Urban Road Travel Time Considering Different Exit Turning Movements

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作  者:陈秀锋[1] 曲腾姣 田家斌[1] CHEN Xiu-feng QU Teng-jiao TIAN Jia-bin(School of Automobile and Transport, Qingdao University of Technology, Qingdao Shandong 266520, Chin)

机构地区:[1]青岛理工大学汽车与交通学院,山东青岛266520

出  处:《公路交通科技》2017年第2期93-99,共7页Journal of Highway and Transportation Research and Development

基  金:国家自然科学基金项目(51178231);山东省自然科学基金项目(ZR2012EEL28)

摘  要:为了有效利用城市道路行程时间数据,提高道路交通状态预测精度,提出了一种考虑交叉口不同出口转向的行程时间估算方法。针对现有行程时间计算模型存在忽略交叉口不同出口转向交通运行状况不均衡性的现象,提出了交叉口上下游出口转向的概念,通过融合定点检测器和探测车数据,在原有累积直方图模型的基础上建立了交叉口不同出口转向的行程时间累积直方图模型。最后以香江路为例进行数据分析,验证了模型的有效性和准确性。研究结果表明:新模型得到的行程时间计算值与视频检测设备获取的实测值相比误差在10%左右,且相对纯探测车方法预测精度更高,说明考虑不同出口转向的城市道路行程时间估计模型可行。In order to effectively utilize the urban road travel time data and improve the prediction accuracy of traffic state of urban road,an estimation method of travel time considering different exit turning movements is proposed. Aiming at the phenomenon of current travel time calculation model ignores the difference of traffic operation condition at each exit turning direction of intersection,the concept of upstream and downstream exits turning is put forward. With the fusion data collected by fixed detectors and the probes,a new cumulative histogram model for estimation of deferent exit turning movement travel time on urban road intersections established on the basis of the original one. Finally,by analyzing the experimental data in the case of Xiangjiang road,the effectiveness and the accuracy of the new model is verified. The result shows that the new model' s error of exit turning movement travel time between the actual value collected by the video detection device and the computation value is about 10%,and the prediction accuracy of the new method is higher than that of the probe-only method,which indicates that the estimation model of urban road travel time considering different exit turning movements is feasible.

关 键 词:交通工程 行程时间 累积直方图模型 数据融合 纯探测车方法 百分率误差 

分 类 号:U491[交通运输工程—交通运输规划与管理]

 

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