| 摘要: |
| 随着城市人口的增长与交通问题的加剧，出行也变得越来越困难.出租车是重要的公共交通工具;对于乘客来说，了解等候出租车需要花费的时间有助于他们安排行程与选择最优的等候地点.针对这个问题，使用出租车轨迹的历史数据，预测乘客在某时某地等候出租车需要的时间.算法使用参数与非参数模型，通过对空车到达过程的建模，预测单个乘客等候出租车需要的时间.使用大规模的杭州出租车数据，结合仿真来验证预测算法.实验评估结果显示，参数模型对等候时间预测的平均误差约为4.5分钟，并且参数模型预测误差小于5 分钟的概率约为83%. |
| 关键词: 乘客候车时间预测 空车到达时间间隔 出租车轨迹 |
| DOI： |
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| 基金项目:国家重点基础研究发展计划（973）（2013CB329504）；国家科技支撑计划（2012BAH94F01）；浙江省钱江人才计划（2011R10078） |
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| Predicting Passengers’ Waiting Time by Mining Taxi Traces |
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QI Guan-De, PAN Yao, LI Shi-Jian, PAN Gang
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Department of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
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| Abstract: |
| Travelling in metropolis is becoming increasingly difficult for people due to the growing population and busier traffic. Since taxi is important public traffic tools in cities, knowing how long it will take to find a taxi can be helpful for customers to plan their schedule and choose the best place to wait. This paper presents a method to predict the waiting time for a customer at a given time and location from historical taxi trajectories. With a parametric and a non-parametric model for arriving flow of vacant taxis, it predicts the time a single passenger needs to wait for a taxi service. Emulation experiment with large-scale taxi dataset in Hangzhou was conducted to verify the new method. The evaluation results validate that the mean prediction errors for both the parametric and non-parametric model are about 4.5 minutes. Moreover, the probability of that the prediction error is below 5 minutes for parametric model is about 83 percent. |
| Key words: prediction of passenger waiting time arriving interval of vacant taxis taxi traces |
