特大城市共享单车出行特征变化分析
Analysis of Changes in Characteristics of Shared Bicycle Trips in Megacities

基于python结合纽约市共享单车订单数据定量分析共享单车在2018~2023年的出行特征变化，通过出行总量、出行时段、出行用户、出行次数、出行时长、出行空间变化来分析共享单车出行特征。研究发现，2018~2023年骑行总量在总体上呈上升趋势；2018~2023年的共享单车出行具有明显的早晚高峰特征；纽约的共享单车用户多为本地常住居民；从第一季度到第三季度骑行次数在增加，而第三季度到第四季度骑行次数在减少；骑行时长主要集中在10~20分钟，随着骑行时长的延长，出行次数在下降；用户出行热门地点是医院、银行、公园、广场、商场以及餐厅。并通过对2021年1月30日~8月31日深圳共享单车数据以及2020年12月21日~12月25日厦门共享单车数据的分析发现有桩和无桩共享单车之间存在着相通的规律。研究共享单车出行特征的变化，可以揭示城市公共交通变化的规律，从而推动公共交通系统的发展。
Based on python combined with New York City’s shared bicycle order data, the paper quantitatively analyzes the change of shared bicycle travel characteristics in 2018~2023, through the total number of trips, travel time, travel users, the number of trips, travel duration, and travel spatial changes to analyze the shared bicycle travel characteristics. It is found that the total number of rides in 2018~2023 shows an upward trend in general; the bike-sharing trips in 2018~2023 have obvious morning and evening peak characteristics; most of the bike-sharing users in New York are local permanent residents; the number of rides is increasing from the first quarter to the third quarter, while the number of rides is decreasing from the third quarter to the fourth quarter; and the length of rides is mainly concentrated in the range of 10~20 minutes. The number of trips is decreasing as the length of the ride increases; users travel to hospitals, banks, parks, squares, shopping malls, and restaurants. And through the analysis of Shenzhen’s shared bike data from 30 January~31 August 2021 and Xiamen’s shared bike data from 21 December~25 December 2020, it is found that there is a common pattern between the staked and stakeless shared bikes. Studying the changes in the travelling characteristics of shared bicycles can reveal the laws of changes in urban public transport and thus promote the development of public transport systems.