基于感兴趣点和滴滴数据的打车需求分析

Requirement Analysis on Taxi Demands from Point of Interest and Didi Data

大数据具有多数据形式、大数据量、传输快捷等优势,大数据分析已逐渐影响和改变人们解决问题的思维方式。本文利用滴滴打车数据和感兴趣点分析人们的打车需求,识别出打车活跃区域。对打车需求数据进行时间划分,核密度分析得到打车聚集区域。统计了打车点附近各类型POI的个数,分析了各区域内打车需求与时间段、地理位置、工作日和周末的关系。发现早高峰(7点到9点)打车与住宅区POI相关,晚高峰(17点到19点)与商铺POI相关,夜晚(21点到2点)打车与公司POI相关,且同一地区在周末与工作日的打车活跃时间不同。

Big Data have the features of variety forms,high-volume,convenient and immediate transmission,with the increasing influence on our daily life and ways in solving issues.We analyze the taxi demand quantity base on didi data and point of interest to recognize the active district with high taxi demand.We divided taxi demand data into several portions by the periods of time,identified the district with high frequency of taxi demand,followed by a statistics of the POI amount around the neighborhood.We also analyzed relationship of taxi demand quantity and time slot,location,weekday or weekend in different district.The paper shows morning peak(from 7 o’clock to 9 o’clock)is related to residential POIs,the evening peak(from 17 o’clock to 9 o’clock)with the commercial POIS,and the night time(from 21 o’clock to23 o’clock)with company POIs,but showing different time slot between weekdays and weekends,even in the identical district.