基于泊松过程的 寻找空驶 出租车的算法

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,也带来了比如打车难问题.为了解决这个问题,首先采用对大规模的出租车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进行预测和推荐工作.用此方法与其它相关先进方法进行对比,实验结果表明,此方法在准确率和运行效率方面更具优势.

A Poisson Process-based Algorithm for Searching Vacant Taxi

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.