Clustering the Stations of Bicycle Sharing System

Bicycle sharing system has emerged as a new mode of transportation in many big cities over the past decade.Since the large number of bicycle stations distribute widely in the city,it is difficult to identify their unique attributes and characteristics directly.Oriented to the real bicycle hire dataset in Hangzhou,China,the clustering analysis for the bicycle stations based on the temporal flow data was carried out firstly.Then,based on the spatial distribution and temporal attributes of calculated clusters,visual diagram and map were used to vividly analyze the bicycle hire behavior related to station category and study the travel rules of citizens.The experimental results demonstrate the relation between human mobility,the time of day,day of week and the station location.

How do Users Evaluate Service Quality of the Dockless Bicycle Sharing System?

In order to improve the public transit’s accessibility and promote service quality of the public transit,it is necessary to alleviate the“last⁃mile”problem.The combination of the public transit and bicycle⁃sharing system is competitive compared with the private car.In 2016,the dockless bicycle⁃sharing system has been undergoing tremendous development.Because the dockless bicycle⁃sharing system is different from previous bicycle⁃sharing systems,components of service quality of the dockless bicycle⁃sharing system differ.However,there are few articles about the service quality of the dockless bicycle⁃sharing system.This paper examined the evaluation of service quality of the dockless bicycle⁃sharing system along with a measurement of users’satisfaction.A questionnaire about service quality was designed,which includes 15 factors.Through the analysis of travelers’evaluation of factors of the dockless bicycle⁃sharing system with Rasch Model,these original ordinal data(Likert data)was transformed to the interval data:the person parameter(ability)and the item parameter(difficulty).Through the analysis of interviewees’abilities,it was found that only education and monthly consumption have significant influence on interviewees’evaluation of service quality of the dockless bicycle⁃sharing system,while there is no significant influence of gender,weekly use of dockless shared⁃bicycle,private car ownership,or monthly income on the evaluation.Furthermore,it was found that users were dissatisfied with cycling under the adverse weather,disturbance from pedestrians and cars,continuity of the bicycle lane,complaint channel,and staff service the most.

Student Bicycle Sharing System in Zagreb-Studocikl

The system of public bicycles in the world known as"Bicycle sharing",is a service in which bicycles are made available for shared use to individuals with or without a certain fee.Users can take and return the bike at numerous locations in the urban parts of the city.As part of the CIVITAS ELAN project(2008-2012),which was aimed at improving the quality of life of citizens by establishing high-quality solutions in city traffic and to promote and encourage sustainable,clean and energy-efficient modes of traffic,a pilot project of student public bicycle(Studocikl)was implemented at the University of Zagreb.In the first phase the pilot project included the Faculty of Transport and Traffic Sciences(FTTS)where is currently implemented.In the second phase the project is planned to include the remaining faculties located at the Borongaj Campus.The idea behind the Studocikl project is to connect two remote locations of FTTS,between headquarters in Vukelićeva Street and Borongaj Campus.Registration(login,logout)of users and the entire administration is done through a web portal.Time of using bicycles is in the period from 8 am to 8 pm(working hours of FTTS).Studocikl was officially put into operation on the 17 September 2012 and in this paper will analyse its one-year operation.The paper will also make proposals for further Studocikl development in terms of:installing GPS trackers for satellite bicycle tracking,the application for smartphones,full automation of the registration,and explore the possibility of extending such service and modes of transportation at all faculties in the University of Zagreb.

Travel Behaviours of Sharing Bicycles in the Central Urban Area Based on Geographically Weighted Regression: The Case of Guangzhou, China

Mobile information and communication technologies(MICTs) have fully penetrated everyday life in smart societies;this has greatly compressed time, space, and distance, and consequently, reshaped residents’ travel behaviour patterns. As a new mode of shared mobility, the sharing bicycle offers a variety of options for the daily travel of urban residents. Extant studies have mainly examined the travel characteristics and influencing factors of public bicycles with piles, while the travel patterns for sharing bicycles and their driving mechanisms have been largely ignored. Using one week’s travel data for Mobike, this study investigated the spatial and temporal distribution patterns of sharing bicycle travel behaviours in the central urban area of Guangzhou, China;furthermore, it identified the influences of built environment density factors on sharing bicycle travel behaviours based on the geographically weighted regression method. Obvious morning and evening peaks were observed in the sharing bicycle travel patterns for both weekdays and weekends. The old urban area, which had a high degree of mixed function, dense road networks, and cycling-friendly built environments, was the main travel area that attracted sharing bicycles on both weekdays and weekends. Furthermore, factors including the point of interest(POI) for the density of public transport stations, the functional mixing degree, and the density of residential POIs significantly affected residents’ travel behaviours. These findings could enrich discourse regarding shared mobility with a Chinese case characterised by rapidly developing MICTs and also provide references to local authorities for improving slow traffic environments.

Simultaneous optimization of transit network and public bicycle station network

The traditional manner to design public transportation system is to sequentially design the transit network and public bicycle network. A new public transportation system design problem that simultaneously considers both bus network design and public bicycle network design is proposed. The chemical reaction optimization(CRO) is designed to solve the problem. A shortcoming of CRO is that, when the two-molecule collisions take place, the molecules are randomly picked from the container.Hence, we improve CRO by employing different mating strategies. The computational results confirm the benefits of the mating strategies. Numerical experiments are conducted on the Sioux-Falls network. A comparison with the traditional sequential modeling framework indicates that the proposed approach has a better performance and is more robust. The practical applicability of the approach is proved by employing a real size network.

Location Privacy in Device-Dependent Location-Based Services:Challenges and Solution

With the evolution of location-based services(LBS),a new type of LBS has already gain a lot of attention and implementation,we name this kind of LBS as the Device-Dependent LBS(DLBS).In DLBS,the service provider(SP)will not only send the information according to the user’s location,more significant,he also provides a service device which will be carried by the user.DLBS has been successfully practised in some of the large cities around the world,for example,the shared bicycle in Beijing and London.In this paper,we,for the first time,blow the whistle of the new location privacy challenges caused by DLBS,since the service device is enabled to perform the localization without the permission of the user.To conquer these threats,we design a service architecture along with a credit system between DLBS provider and the user.The credit system tie together the DLBS device usability with the curious behaviour upon user’s location privacy,DLBS provider has to sacrifice their revenue in order to gain extra location information of their device.We make the simulation of our proposed scheme and the result convince its effectiveness.

A spatiotemporal analysis of the impact of lockdown and coronavirus on London’s bicycle hire scheme:from response to recovery to a new normal

The coronavirus pandemic that started in 2019 has had wide-ranging impacts on many aspects of people’s daily lives.At the peak of the outbreak,lockdown measures and social distancing changed the ways in which cities function.In particular,they had profound impacts on urban transportation systems,with public transport being shut down in many cities.Bike share systems(BSS)were widely reported as having experienced an increase in demand during the early stages of the pandemic before returning to pre-pandemic levels.However,the studies published to date focus mainly on the first year of the pandemic,when various waves saw continual relaxing and reintroductions of restrictions.Therefore,they fall short of exploring the role of BSS as we move to the post-pandemic period.To address this gap,this study uses origin-destination(O-D)flow data from London’s Santander Cycle Hire Scheme from 2019-2021 to analyze the changing use of BSS throughout the first two years of the pandemic,from lockdown to recovery.A Gaussian mixture model(GMM)is used to cluster 2019 BSS trips into three distinct clusters based on their duration and distance.The clusters are used as a reference from which to measure spatial and temporal change in 2020 and 2021.In agreement with previous research,BSS usage was found to have declined by nearly 30%during the first lockdown.Usage then saw a sharp increase as restrictions were lifted,characterized by longer,less direct trips throughout the afternoon rather than typical peak commuting trips.Although the aggregate number of BSS trips appeared to return to normal by October 2020,this was against the backdrop of continuing restrictions on international travel and work from home orders.The period between July and December 2021 was the first period that all government restrictions were lifted.During this time,BSS trips reached higher levels than in 2019.Spatio-temporal analysis indicates a shift away from the traditional morning and evening peak to a more diffuse pattern of working hours.The results indicate that the pandemic may have had sustained impacts on travel behavior,leading to a“new normal”that reflects different ways of working.