Analysis of temporal and spatial usage patterns of dockless bike sharing system around rail transit station area

In order to study the spatiotemporal characteristics of the dockless bike sharing system(BSS)around urban rail transit stations,new normalized calculation methods are proposed to explore the temporal and spatial usage patterns of the dockless BSS around rail transit stations by using 5-weekday dockless bike sharing trip data in Nanjing,China.First,the rail transit station area(RTSA)is defined by extracting shared bike trips with trip ends falling into the area.Then,the temporal and spatial decomposition methods are developed and two criterions are calculated,namely,normalized dynamic variation of bikes(NDVB)and normalized spatial distribution of trips(NSDT).Furthermore,the temporal and spatial usage patterns are clustered and the corresponding geographical distributions of shared bikes are determined.The results show that four temporal usage patterns and two spatial patterns of dockless BSS are finally identified.Area type(urban center and suburb)has a great influence on temporal usage patterns.Spatial usage patterns are irregular and affected by limited directions,adjacent rail transit stations and street networks.The findings can help form a better understanding of dockless shared bike users behavior around rail transit stations,which will contribute to improving the service and efficiency of both rail transit and BSS.

Investigating User Ridership Sentiments for Bike Sharing Programs

Bike sharing is considered a state-of-the-art transportation program. It is ideal for short or medium trips providing riders the ability to pick up a bike at any self-serve bike station and return it to any bike station located within the system’s coverage area. The bike sharing programs in the United States are still very young compared to those in European countries. Washington DC was the first jurisdiction to devise a third generation bike sharing system in the US in 2008. To evaluate the popularity of a bike sharing program, a sentiment analysis of the riders’ feedback can be performed. Twitter is a great platform to understand people’s views instantly. Social media mining is, thus, gaining popularity in many research areas including transportation. Social media mining has two major advantages over conventional attitudinal survey methods—it can easily reach a large audience and it can reflect the true behavior of participants because of the anonymity social media provides. It is known that self-imposed censor is common in responding to conversational attitudinal surveys. This study performed text mining on the tweets related to a case study (Capital Bike share of Washington DC) to perform sentiment analysis or opinion mining. The results of the text mining mostly revealed higher positive sentiments towards the current system.

Inspiration of “Internet + Shared bike” for Healthy Exercise of University Students

As the economy and technology keep growing,the mode of shared bikes gains popularity under these circumstances.At the current period,university students become fond of using shared bikes,which changes body health and life style of university students.When this mode combines the characteristics and functions of shared bikes,it has a great impact on the awareness and motivation of work-out of university students.Supported by Internet technology,shared bikes meet the need of people that they can use them at any time,which is new and innovative to the university students.This article provides university students with shared bike service in campus by analyzing the influence of“Internet+shared bike”on health and sports of university students.It will promote the effective application of shared bikes.

Research on the Traveling Characteristics and Comparison of Bike Sharing in College Campus-A Case Study in Hangzhou

Bike sharing emerging from college campus in China's Mainland has become a major part in the daily traveling of Chinese urban residents.It changes the traveling behavior of urban residents,and simultaneously,raises higher requirements on urban transportation facility construction and management.However,the return of bike sharing to college campus causes more troubles to schools.The fundamental cause is the closed peculiarity of campus traveling comparing with city traveling,and also the discrepancy between college campuses of different types.This paper investigates the traveling characteristics of bike sharing in college campus in three different locations in Hangzhou City,Zhejiang Province of China in the questionnaire,and compares the discrepancy with urban bike sharing traveling characteristics and the discrepancy in bike sharing use between college campuses of different types.From the perspective of parking,maintenance and operation,and hardware design,the paper eventually raises suggestions to optimize independent college campus bike sharing service facility and management consistent with urban system.The research may also offer beneficial reference to the release of bike sharing facilities consistent with urban system in all sorts of independent parks,especially college campus.

Analysis of Financial Accounting Problems Based on Sharing Economy——Taking Bike Sharing as an Example

Bike sharing is a new type of"Internet+"model.At present,China has not yet introduced relevant Internet operating systems and accounting standards.There is still a big problem in the financial accounting and processing of the bike sharing platform.This paper firstly summarizes the development status of bike sharing,then analyzes the related financial accounting problems of bike sharing with the example of Mobike,and points out the main problems faced by the financial accounting of bike sharing short-time rental model,and finally proposes countermeasures for the financial accounting of bike sharing short-time rental model.

Determination of the Size of a Proposed Bike-Sharing Program in Las Vegas, Nevada

Bike-share systems have been installed in cities worldwide as a way to attract travelers to use transit rather than the automobile. This has been proved to be an effective way of mitigating congestion on the road. The objective of this study is to develop a method to determine the size of the bike-share program in terms of the number of bicycles, the number and location of the stations, the number of docks at each station. To achieve the objectives of this study, a literature review was conducted on university bike-sharing systems in the U.S. and abroad. Various cases of bike-share programs were analyzed, in which each case consisted of a different number and location of bike-share stations. The demand corresponding to these stations was used as the input to a simulation model developed in this study to determine the number of docks in stations and bicycles in the system on and around campus at UNLV. These sizing parameters of the bike-share system then were used in a cost and benefit analysis to determine which cases could achieve maximum benefit, given a limitation of the initial costs. It was found that provision of one peripheral station and three internal stations at strategic locations provide relatively higher benefit cost ratio at lower initial cost.

Analysis and O-D Demand Estimation of a Public Bike-Sharing Program in Las Vegas

Bike-share systems are an effective way of mitigating congestion on the road. In addition, bike-share systems have been built in universities to serve for trips to work/commuting as well as the trips on campus. In Las Vegas, a bike-share system was proposed at the University of Nevada, Las Vegas. This study analyzed factors that influence the usage of bike-share program and estimated the origin-destination demand. To achieve these objectives, first, a literature review was conducted on university bike-sharing systems in the U.S. and abroad. Then, a survey with a questionnaire was distributed to UNLV to obtain the users’ preferences to the locations of the proposed bike-share stations and their likelihood and frequency to use the bike-share program. In total, 241 faculty, staff, and students responded to the survey. About 50% of those participating in the survey expressed willingness to use the bike-share system for commuting and 60% said they are willing to use bike share for on-campus travel. Commuting and on-campus travel are two different types of travel, and the factors to determine whether an individual would use the bike-share system are quite different for each. It was estimated that there would be 3450 members for a bike-share program at UNLV, each making bicycle trips with varying frequencies, producing 1966 trips per day.

基于贝叶斯模型的共享单车可用性分析

共享单车的运营管理对于减少碳排放、实现城市交通的可持续发展具有重要意义。在共享单车系统中,每天都有一小部分的单车无法使用。目前共享单车维护管理的可用性信息收集复杂。尽管GPS、物联网、云计算等现代技术为共享单车系统提供了丰富的信息环境,但共享单车自身的故障和维护信息仍然缺乏,没有可靠的在线信息表明共享单车的可用性。本文在对用户出行数据进行分析时,发现存在短时间内用户频繁退租共享单车的现象,这种现象可能隐含着共享单车可用性的信息。因此,本文提出了一个贝叶斯模型,根据用户出行的租赁交易数据,提取退租数据,引入站点属性和用户退租共享单车的时间信息,构建带有协变量的贝叶斯扩展模型。利用在线交易数据估计站点中共享单车的不可用概率以及不可用自行车的数量。本文基于呼和浩特市共享单车系统数据库的真实数据验证该方法的有效性。

共享单车减量回收路径优化模型及求解研究

为解决共享单车的过量投放回收清理工作任务量大问题,本文从交通运输执法者角度出发,对超配额的共享单车进行减量回收。考虑到共享单车站点在空间分布具有零散性会影响单车回收工作的效率,以车辆回收距离最小化为目标,建立多中心的共享单车减量回收路径优化模型。基于遗传算法,设计符合模型的求解算法。以包头市共享单车系统为例进行实证分析,结果表明,该模型及求解算法能缩短车辆回收距离,有效提高共享单车减量回收效率,节约了交通运输管理部门的人力物力。

基于广义加性模型的共享电单车与常规公交竞争强度与影响因素

为分析不同城市共享电单车与多种交通方式的竞争强度及其与常规公交竞争强度的影响因素,开展了哈啰电单车全国用户调查,并建立了广义加性模型。结果表明,共享电单车对常规公交替代作用明显,平均替代比例约20%,不同城市间有15%~28%的变化。南北方城市共享电单车与常规公交竞争强度受不同因素影响:北方城市共享电单车与出租车3 km计价正相关,与常规公交站点密度呈非线性关系;南方城市共享电单车与城区人口数正相关,与全市人均小汽车保有量负相关,与PM2.5浓度呈非线性关系。

电子围栏背景下共享单车停车行为影响特征分析

单车规范停放问题影响着共享单车系统的可持续发展,而设置电子围栏是促进单车停放规范化的重要手段。用户在电子围栏背景下规范停车行为的影响机理是制定停放管理政策的基础。基于用户停车选择行为问卷调查的结果,在二项Logit模型的基础上,结合调查数据特征建立固定效应选择模型、非对称选择模型等多个停车行为选择模型,探究各类特征对用户停车行为的影响。结果显示,用户的年龄、职业、收入等社会经济特征,用户在平常使用共享单车的时段、时长、频率及停放困难频率等共享单车出行特征,具体在停车场景下合规停放的绕行距离和违规停放的罚款金额等场景特征,均会显著影响用户合规停放的概率。模型结果可为电子围栏背景下的精细化管理提供用户行为定量分析基础。

基于大数据的厦门岛建成环境对共享单车起讫点分布的影响

不同城市肌理上的共享单车出行活动迥然相异.基于共享单车和兴趣点(POI)等多源数据,运用核密度和基于最优参数的地理探测器方法,分析厦门岛共享单车起讫点分布格局及建成环境对其影响作用.研究发现:(1)厦门岛共享单车的平均骑行距离为1.08 km,平均骑行时间为7.19 min.(2)起讫点在空间上总体呈现“一带多核”的分布特征.(3)建筑密度和人口密度是共享单车起讫点分布的核心驱动因子,中心可达性和道路交叉口密度则是主要驱动因子.(4)不同建成环境因子围绕2个核心因子形成协同增强效应,不同要素优化组合是共享单车发展的有效路径.

厦门岛轨道交通站点共享单车接驳影响因素研究

共享单车凭借其高效便利的优势在全国各大城市快速普及,已成为轨道交通站点重要的接驳方式,但其供需失衡、乱停乱放等问题也给城市交通与环境带来挑战。利用厦门市共享单车及城市空间等多源大数据,通过Python、GIS解析共享单车出行的时空特征,探究轨道站域骑行特征及其来自土地利用、城市建成环境等方面的影响效应,结果表明:共享单车具有短时空距离利用的特征,为城市地铁站点的接驳交通提供了重要支撑;站点周边共享单车的接驳利用受城市多种因素影响,同时也反映了站点开发的阶段性和差异性;根据共享单车出行特征,轨道交通站点可归纳为四类,应根据站点的不同类型因站施策,完善城市慢行系统,促进共享单车骑行,加强轨道交通站域开发。

基于云端数据分析的共享电单车起火原因分析技术研究

共享电单车具有运行数据采集和云端记录功能,揭示云端数据随起火部位及引燃模式的变化规律,可为起火原因认定和产品质量管理提供新依据。本文通过明火引燃、动力电池热失控整车燃烧试验和电气线路短路故障试验,研究共享电单车起火燃烧过程中云端数据的V-t曲线特征和变化规律。结果表明:明火及短路会导致数据传输线路断开,整车电压数据出现骤降后快速降至0,电压下降速度可超过500.56 mV/s;动力电池热失控后,整车电压数据出现骤降后缓慢下降,电压下降速度为20.02 mV/s,并在下降过程中出现短期的电压回升现象。开展共享电单车的火灾调查时,可通过调取云端数据分析V-t曲线特征的方法,为起火原因认定工作提供线索。

建成环境对共享单车分时骑行量的非线性作用研究:以上海市为例

为解析建成环境对共享单车不同时段借还车量的非线性作用,本文以2016年上海摩拜共享单车和网络公开数据为基础,利用梯度提升决策树,建立共享单车工作日,非工作日及工作日早、晚高峰借还车量模型。研究结果显示:变量影响程度方面,街道至市中心距离对4个时段共享单车借还车量具有稳定且突出的作用,相对重要度超过17%;路网密度、非机动车道占比、人口密度影响次之,但在4个时段作用波动较大。非线性关系方面,街道至市中心距离、非机动车道占比、人口密度、就业POI(Point of Interest)密度与各时段共享单车借还车量呈复杂非线性关系,阈值效应显著;路网密度、住宅POI密度则与之总体负相关和正相关。同时段下,建成环境对早晚高峰时期的共享单车借还车量非线性作用差异明显,与高峰时期单车骑行的潮汐性特征相一致,非机动占比与街道中心邻近度、就业POI密度对高峰时段单车骑行作用有明显的协作性作用。

面向共享单车调配的带约束游牧算法研究

共享单车调配是优化城市交通资源配置的重要手段,但目前的最优路径调配方法往往对单车系统规模敏感。为此,研究一种分时段、区域间调配的共享单车投放方法,提出了带约束的游牧算法(nomad algorithm with constraints,NCA)求解调配模型的最优解。将单车调配问题建模为以单车流量为约束、以最小化运营损耗为目标的优化问题;提出求解上述模型的NCA算法,预测投放区域单车存量和区域间转移量,相比无约束的原游牧算法,改进了局部搜索和全局寻优策略,优化了部落初定位方法;基于预测的存量和转移量得出分时段区域间单车的调配方案。在上海和纽约相关数据集上的对比实验结果表明,运行时长约为其他方法的15%,租赁需求响应率高于分支定界算法0.15%,单车总数和运营损耗比遗传算法降低了约10%,验证了该方法具有更高的优化效率和用户需求响应率。

基于TOD模式及语义功能的共享单车潮汐流与建成环境非线性关联研究

公共交通导向发展(TOD)是实现城市紧凑、人居可持续发展的重要途径,共享单车与轨道交通的接驳出行极大提升了公共交通的服务范围,促进了TOD规划策略的落实。该文基于TOD规划理念,识别共享单车的接驳流动模式,在考虑地铁站语义功能基础上,使用可解释机器学习模型挖掘武汉市主城区共享单车潮汐流模式及与建成环境的非线性关联关系,结论如下:①根据共享单车早晚高峰时段的潮汐均衡性指数,发现武汉市主城区存在“早入晚出”和“早出晚入”两类潮汐流模式,前者出现在距城市中心距离中等的居住区和汉口中央活动区边缘的就业区,后者出现在二环线附近的就业密集区;②通过POI语义信息建模和层次聚类识别出4类地铁站语义功能主题及两种混合功能聚类簇,地铁站语义功能类型与共享单车流动模式呈强相关;③建成环境因子的非线性效应明显,当配套生活设施和道路密度适中、居住规模较大时,能有效促进共享单车高流量稳定接驳模式发生。研究结果可从共享单车优化调度、城市建成环境调整等方面为缓解共享单车潮汐流问题提供依据。

基于公开数据的共享单车出行时空特征分析

近年来,共享单车作为一种低碳环保的新兴出行方式得到广泛使用,能够有效解决居民出行“最后一公里”问题。由于其使用环境开放、有利于保持社交距离等特点,突发公共卫生事件背景下使用共享单车出行的特征成为研究热点。文章以芝加哥市共享单车系统Divvy Bikes为研究对象,基于公开数据集,对2021年和2022年芝加哥共享单车出行时空特征进行分析,结果发现:第一,2022年共享单车骑行量相比2021年有明显下降,但其下降程度低于同时期的地面公交和轨道交通客流量;第二,在时间特征上,尽管受到突发公共卫生事件的影响,共享单车骑行仍然呈现明显的早晚高峰现象,骑行时长以5~10分钟为主;第三,在空间特征上,骑行距离以短中距离为主,骑行热点区域主要集中在芝加哥市中心区域并呈现由市中心向郊区扩散的趋势。

基于Markov过程天气预测的共享单车调度优化研究

针对某大学城共享单车资源分配不平衡问题,建立了与调度成本和用户满意度相关的单目标数学规划模型,对现有共享单车调度策略进行分析,并制定改善方案.通过调查问卷分析单车调度过程中存在的问题,利用Python获取单车的相关数据.在此基础上,基于齐次Markov过程对天气状况进行预测,采用LSTM时间序列对区域内未来单车数量的变化情况进行预测,利用遗传算法求解最优调度路径和调度数量,提出优化方案.通过敏感性分析验证本文所提方案的可行性.结果表明,优化后的调度方案缩短了单次调度时间并提高了用户的满意度,对共享单车管理部门具有指导意义.

考虑共享单车接驳的共享汽车站点选址模型构建及应用研究

共享汽车是共享经济背景下的一种绿色出行模式,它不但能满足人们出行用车需求,还能实现城市低碳绿色发展。但是,很多城市也出现了共享汽车站点布局不合理、站点汽车数量和用户需求不匹配、停车取车难等一系列问题。在组合出行的背景下,基于停车场、城市POI及出租车(包括快车)订单等多源数据,以最大化用户需求满足和最小化取车还车成本为目标,构建考虑共享单车接驳的共享汽车站点选址模型,并实证分析得到最优的站点布局。研究结果表明,从用户需求情况来看,在共享汽车站点最大服务范围一定的前提下,可以通过增加站点数量和共享单车可用率来提高用户需求,让共享汽车用户在出行时做到有车可用。从用户取还车便捷性来看,在共享汽车站点最大服务范围较大时,随着共享单车可用率的增加,用户使用取还共享汽车花费的时间明显减少。这在一定程度上说明共享单车可用率增加可有效提高共享汽车用户取还车的便捷性,缩短用户的取还车时间,提高其用车意愿。