| 摘要: |
| 随着城市化进程的推进，城市车辆数量呈现激增的趋势。城市交通为居民的出行提供便利的同时，也带来了其它挑战，比如打车难问题。本文的主要工作分为两部分：1）预测乘客在某个位置某个时间点的打车概率和等待空车时间；2）在某个位置某个时间点，为乘客推荐打车位置。为了完成上述主要工作，本文首先对大规模的出租车GPS轨迹数据进行预处理，并生成道路特征索引。然后利用非齐次泊松过程NPP(Nonhomogeneous Poisson Process)进行预测和推荐工作。在实验部分，我们基于真实的北京市出租车轨迹数据（由12000辆出租车在30天内产生）和路网数据，将本文方法与其它相关先进方法进行对比，实验结果表明，本文方法在准确率和运行效率方面更具优势。 |
| 关键词: GPS轨迹 出租车 路段索引 预测 推荐 |
| DOI： |
| 分类号:TP3-0 |
| 基金项目: |
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| A Poisson Process-based Algorithm for Searching Vacant Taxi |
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fanlilue
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Zunyi Normal College
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| Abstract: |
| With the development of urbanization, the number of cars has been proliferating fast. Urban transportation provides convenience for city resident, meanwhile, it also brings many challenges, such as causing a difficulty for taking a taxi. In this paper, main work is composed of two parts: first, we propose a method to estimate the probability and waiting time for a vacant taxi at a given time and place, second, we provide an recommendations for passengers of where to wait for a taxi. In order to complete the main work, we firstly preprocess the Large-scale Taxi GPS Traces and generate the road characteristic index. Then we use NPP (Nonhomogeneous Poisson Process) to predict and recommend. In the experimental part of the paper, based on the large-scale real-world GPS traces dataset, we compare our method and other related advanced methods and the results show that our method has more advantages in accuracy and efficiency. |
| Key words: GPS traces taxi road segment index prediction recommendation |
