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基于AVL数据的公交到站时间实时预测模型

DOI: 10.3969/j.issn.1674-0696.2012.05.23, PP. 1014-1017

Keywords: 公交到站时间,实时预测,自动车辆定位数据,BP神经网络算法,自适应指数平滑法,busarrivaltime,real-timeprediction,automaticvehiclelocationdata(AVL),back-propagationnetworkalgorithm,self-adaptivethriceexponentialsmoothingalgorithm

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Abstract:

:?公交车辆到站时间预测是公交信息服务、公交动态调度的关键参数。基于实时和历史的公交车辆自动定位数据(AVL)需求分析,将公交车辆到站时间划分为站点停靠时间、区段全程运行时间和区段部分运行时间,分别采用点估计法、BP神经网络法和自适应指数平滑法对其进行动态预测。最后结合实验线路公交车辆的AVL运行数据,对预测模型进行了验证和评价分析。研究结果表明:本预测模型由于将历史数据规律和实时交通状况进行了有效融合,从而提高了公交到站时间预测的鲁棒性和预测精度。

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