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基于AVL数据的单程时间参数设置方法 被引量:5

Setting Scheduled Trip Time Based on AVL Data
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摘要 单程时间(ST)是编制公交运营计划的重要参数,而国内公交企业对此普遍重视不足,多采用公司统一而非针对不同线路的时段标准,由调度人员凭借经验设置参数值,致使其无法反映现实状况,运营服务准点率低下.为此,本文提出一个基于车辆定位(AVL)数据的ST设置方法.其基本思路是:首先通过分析大量AVL数据中的实际单程时间样本,划分'同运营时间(HRT)时段',并建立'单程分布知识库';然后采用候车时间优化模型,计算各HRT时段中的ST参数取值;最后,对ST参数进行仿真验证和调整.对海口4路现实数据的实验显示,采用该方法设置ST参数有助于编制出高执行率和准点率的行车方案. The trip time (ST), as an essential parameter, greatly affects the compilation and on-time probability of a vehicle schedule in public transit services. Unfortunately, the significance of ST has not been generally recognized in China. The values of STs are usually set manually based on experiences, which are normally hard to reilect the real-world situation. To set proper trip times, a novel automatic approach based on the AVL data is proposed. The basic process is as follows. First, running time samples are abstracted from a large set of AVL data, based on which the homogeneous running time ( HRT ) bands are then decided. Meanwhile, the knowledge base of running time distribution is established. Then, the ST parameters corresponding to each HRT band are generated based on a waiting time model. Finally, a simulation system is developed to test the schedules compiled based on a given set of STs, which may be revised further according to the simulation results. Experiments on the bus line 4 of Haikou of China show that setting the STs by the proposed approach brings high on-time probability to vehicle schedules.
作者 徐甲 沈吟东
出处 《交通运输系统工程与信息》 EI CSCD 北大核心 2012年第5期39-45,共7页 Journal of Transportation Systems Engineering and Information Technology
基金 国家自然科学基金(70971044 71171087)
关键词 智能交通 单程时间 AVL数据分析 启发式方法 运营服务分析 intelligent transportation trip time AVL data analysis heuristics service reliability measurement
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参考文献9

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同被引文献25

  • 1杨立才,贾磊,孔庆杰,朱文兴.基于人工免疫算法的交通时段自动划分方法[J].控制理论与应用,2006,23(2):193-198. 被引量:21
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  • 9杜长海,黄席樾,杨祖元,邓天民,詹建平.改进的FCM聚类在交通时段自动划分中的应用[J].计算机工程与应用,2009,45(24):190-193. 被引量:21
  • 10申桂香,张英芝,薛玉霞,陈炳锟,何宇.基于熵权法的数控机床可靠性综合评价[J].吉林大学学报(工学版),2009,39(5):1208-1211. 被引量:36

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