基于大数据的南京市共享单车时空特征研究

共享单车的兴起极大地便利了人们的短距离出行,利用单车大数据来挖掘和分析短距离的出行规律已成为智慧城市和智慧交通的重要热点.利用南京市的摩拜单车时空数据,研究了单车的时空分布规律与差异,并重点挖掘了早晚高峰时刻以及区域间单车流动规律等,研究表明:(1)南京市整体早、晚高峰时间分别为7:10-8:37和17:15-18:25;副中心早高峰比主城区早35min开始,且晚高峰持续时间长;(2)早、晚高峰高强度骑行主要分布在以新街口、百家湖等为中心的区域;主城区和副中心区有着骑行差异,短距离骑行主城区相对副中心具有更高的比例,副中心则具有更多的长距离骑行;(3)单车骑行围绕地铁站而显现聚集趋势,并且集中于地铁1,2,3号线区域.

On Space-Time Characteristics of Shared Bikes in Nanjing Based on Big Data

The rise of the current shared bikes greatly facilitates people''s travel of short distances, and with the big data of shared bikes, studies have been done to mine and analyze the traveling pattern of people in the field of Smart City and Smart Transportation which has become a important focus. With the space-time data of the MOBIKE located in Nanjing studies the space-time pattern regularity and differences of the shared bikes and focus on mining the rush hour and regional flow of the shared bikes, etc.. The results show that, firstly, the overall morning rush time of Nanjing is about 7:10-8:37, and the evening rush time is nearly 17:15-18:25; the morning rush hours of sub-center of Jiangning District began 35 minutes earlier than the main urban area, and the evening rush last for a longer time. Secondly, the high intensity riding in the morning and evening rush is mainly distributed in the main urban area centered around Xinjiekou and the sub-center of Baijia Lake. Thirdly, there are some riding difference laying between the main urban area and the Baijia Lake, the deputy central district. The main urban area has a greater proportion in short distance riding, while the deputy central district has more long-distance riding. Eventually, cycling shows a tendency to gather around subway stations, and is concentrated in metro line 1, 2, and 3.