Public Bicycle Research Articles

Rating road traffic education

In the context of road safety, improvements in road traffic education have been recognized in several countries as an instrument for reducing road accidents. However, the level of road safety education imparted by different institutions lacks an objective performance measure regarding the level of awareness that different participants in the transport process have concerning road transportation risks. Based on an analytical hierarchy process to weigh the relative importance of different questions, in this paper, the fundamentals of a road safety questionnaire are presented and discussed, including the corresponding references for the contents of each question. This test was designed for six road transport participants: car drivers and passengers; public bus, motorcycle and bicycle riders; and pedestrians. For each of these participants, six areas of knowledge were addressed: applied situations, courtesy and urbanity, infrastructure, safety and human factors, traffic signals and rules/recommendations. The target population for applying the test was the inhabitants of the City of Santiago de Queretaro, Mexico. For a grading scale of 1 to 10, the lowest and highest grades were obtained by motorcycle riders (5.72) and pedestrians (8.84), respectively, which denotes the need for better instructions for motorcyclists regarding road safety.

Research on Factors Influencing the Loyalty of Campus Public Bicycles

Recently, campus public bicycles have been popular, how to improve consumer loyalty is worthful to explore. This study selects ZHBIT as the research region, where campus public bicycles have been popular. 392 valid samples are collected to explore influencing factors of its loyalty. The results show that perceived quality and perceived value of campus public bicycle positively affect brand preference, consumer satisfaction and loyalty. Brand preference and consumer satisfaction have a positive mediation impact on consumer loyalty, while the power of brand preference is stronger than consumer satisfaction.

서비스디자인을 적용한 공공재 디자인 전략에 관한 연구 - 공공자전거서비스 사례를 중심으로

서비스디자인을 적용한 공공재 디자인 전략에 관한 연구 - 공공자전거서비스 사례를 중심으로

Effects of perception on public bike-and-ride: A survey under complex, multifactor mode-choice scenarios

Bicycles are an environmentally-friendly, energy-saving mode of transportation. Public bike-and-ride is a term used to describe the use of public bicycles combined with transit as a means of transportation. A new stated preference (SP) design scheme based on the factors respondents felt were most important was proposed to augment the traditional SP design under complex multi-factor and multi-level situations. iPads were used to automatically administer the survey under each design scheme and collect the choice behavior data for public bike-and-ride. The concept of perceived psychological distance was further proposed and used to estimate Logit models. Comparative analysis of these models shows for the traditional SP design scheme, some factors, including perceived psychological distance, have reduced statistically significant effects on public bike-and-ride choice relative to the new SP design scheme. This indicates that in scenarios with complex decisions, the decision-makers would reduce their consideration of some factors and simplify their decision process making the new SP survey design scheme more suitable to analyze their choice behavior in those cases. Model analysis showed that perceived psychological distance for each traveler is the most critical factor during the decision process for travel behavior analysis. Finally, sensitivity analysis was conducted to determine which factors in the new survey design were important to increase the share of public bike-and-ride users. Practical findings for promoting public bike-and-ride use are presented in addition to theoretical references for improving the traditional survey methods.

Understanding the usage of dockless bike sharing in Singapore

ABSTRACTA new generation of bike-sharing services without docking stations is currently revolutionizing the traditional bike-sharing market as it dramatically expands around the world. This study aims at understanding the usage of new dockless bike-sharing services through the lens of Singapore's prevalent service. We collected the GPS data of all dockless bikes from one of the largest bike sharing operators in Singapore for nine consecutive days, for a total of over 14 million records. We adopted spatial autoregressive models to analyze the spatiotemporal patterns of bike usage during the study period. The models explored the impact of bike fleet size, surrounding built environment, access to public transportation, bicycle infrastructure, and weather conditions on the usage of dockless bikes. Larger bike fleet is associated with higher usage but with diminishing marginal impact. In addition, high land use mixtures, easy access to public transportation, more supportive cycling facilities, and free-ride promotions positively impact the usage of dockless bikes. The negative influence of rainfall and high temperatures on bike utilization is also exhibited. The study also offered some guidance to urban planners, policy makers, and transportation practitioners who wish to promote bike-sharing service while ensuring its sustainability.

Bicycle Lane Condition and Distance: Case Study of Public Bicycle System in Xi’an, China

AbstractUrban road infrastructure has significantly affected the popularity and use of public bike-sharing systems in many cities. Using the bike-sharing system of Xi’an, China, as a case study, th...

Enhancing the utilization of public bike sharing systems using return anxiety information

Public Bike Sharing Systems (PBSSs) have become popular as mass transportation tools. Along with the growth of the population using them, disadvantages of PBSS are emerging, for example, when there are no bikes available for users to rent or no vacant parking lots to which bikes can be returned. To make up for this disadvantage, users are allowed to apply for fee discounts and obtain real-time information in advance from the Internet. The two main problems are full stations or lack of available bikes. But in hot spots or at specific hot times, even when users know the current station information, it is not possible to guarantee whether there will be parking lots or available bikes in the next second.To prevent the decline of the reference value of real-time bike information caused by large numbers of users, we collect the number of bikes near stations and real-time information in bike stations to form return anxiety information. When a station is nearly full or there are many bikes near the station, the return anxiety information value will increase. When users enquire about returning bikes to stations, they can refer to the return anxiety information. The higher the return anxiety information value, the lower the user’s tendency to return the bike. In the implementation, our study develops an android application to collect basic data and uses a Petri Net to simulate the PBSS scenario. Various rates of user trust are used to verify the reference value of return anxiety information.

Commute happiness in Xi’an, China: Effects of commute mode, duration, and frequency

Commuting between home and work is an important aspect of everyday life. Based upon the broaden and build theory of positive emotions, experiencing happiness during commutes generates positive emotions that are beneficial for both individual and societal well-being. The existing literature on commute happiness is dominated by studies from the U.S., Canada, and Europe. Little is known about commute happiness in Chinese cities where electric bikes and employer-provided shuttle buses are common commute modes. This study uses original survey data collected from Xi’an, China to examine how commute happiness may differ across eight commute modes (walk, private bike, public bike, bus, subway, electric bike, shuttle bus, and private car) and by commute duration and frequency, while controlling for personal demographics and overall health and well-being. Results show that commute mode and duration are significantly associated with commute happiness while commute frequency is not. People who use employer shuttle buses reported the highest commute happiness, followed by people who use private bikes and then people who walk. People who use regular city buses reported the lowest commute happiness. People who use subway, public bikes, and electric bikes show no differences in commute happiness from car users. Longer commute duration is associated with lower happiness. Recommendations for Chinese cities to promote commute happiness include improving public bus services, investing in pedestrian and bicycle infrastructure, enhancing bike-transit integration, encouraging employer shuttle bus programs, and fostering jobs-housing balance. The results also indicate a gender gap in commute happiness that merits additional research.

Multi-Agent System for Demand Prediction and Trip Visualization in Bike Sharing Systems

This paper proposes a multi agent system that provides visualization and prediction tools for bike sharing systems (BSS). The presented multi-agent system includes an agent that performs data collection and cleaning processes, it is also capable of creating demand forecasting models for each bicycle station. Moreover, the architecture offers API (Application Programming Interface) services and provides a web application for visualization and forecasting. This work aims to make the system generic enough for it to be able to integrate data from different types of bike sharing systems. Thus, in future studies it will be possible to employ the proposed system in different types of bike sharing systems. This article contains a literature review, a section on the process of developing the system and the built-in prediction models. Moreover, a case study which validates the proposed system by implementing it in a public bicycle sharing system in Salamanca, called SalenBici. It also includes an outline of the results and conclusions, a discussion on the challenges encountered in this domain, as well as possibilities for future work.

Mining bike-sharing travel behavior data: An investigation into trip chains and transition activities

This study aims to explore the travel behavior of bike-sharing users in Zhongshan, China. To this end, we use 5months of trip data, which included origin and destination locations, and pickup and return time of each used bike in the system. To get a complete picture of the behavior, we distinguished between trips, trip chains, and transition activities. We categorized different trip chains and constructed transition matrices between activities. We found that almost all trips have different origin and destination stations. Two thirds of the trips are part of a trip chain consisting of multiple trips. Although users often use another station to start their next trip, a clear picture emerges in which public bikes are used as a single mode to hop from one destination to another, and at the end return more or less to the same location where the trip chain was started. Moreover, based on the trip chain matrices and transition matrices between activities, we conclude that users mainly used public bikes for commuting, and some of users went home during lunch break, while the system was also used or after-work shopping activities.

Are you being shared? Mobility, data and social relations in Shanghai’s Public Bike Sharing 2.0 sector

Starting in early 2016, a new wave of dockless ICT-based Public Bike Sharing Systems (PBSS 2.0) has grown rapidly in many Chinese cities and is now spreading globally. Whilst there is a growing literature on sharing and a substantial technical literature on the earlier breed of docked PBSS 1.0, there is no critical academic study of this new bike sharing phenomenon. This paper seeks to contribute to social scientific debates on sharing and mobilities by exploring the nature of sharing engendered by these disruptive forms of bike sharing. Focused on a case study of Shanghai (China) and based upon a series of stakeholder interviews and media analysis, this paper explores the extent to which these systems represent more economically reproductive “transactional” or disruptive and “transformational” modalities of sharing. By exploring the social, spatial and environmental relations produced by these new “hybrid mobiles”, we conclude that PBSS 2.0 represents a retrenchment and extension of existing exploitative capitalist relations. Whilst we temper this conclusion in the knowledge that it is very early in its evolution, we argue that in its current form PBSS 2.0 is unlikely to achieve the societal transformations often cited as a benefit of the hybridisation of virtual and physical mobility.

Investigation on the effects of weather and calendar events on bike-sharing according to the trip patterns of bike rentals of stations

Public bicycle systems are widely spread across many cities worldwide. ‘Tashu’, a public bicycle sharing system in Daejeon, was installed in 2009 and it is one of the well-established public bike-sharing systems in South Korea. Previous studies in the literature found that in general, bicycling is affected by weather conditions and temporal characteristics. However, the degrees of impacts or the signs of effects may be different depending on the stations. Therefore, this study investigated the different effects of weather conditions and temporal characteristics according to the characteristics of the stations at the station level analysis in addition to the system level analysis. For the cost-effective station level analysis, clustering analysis was utilized to find out the groups of the stations with the similar properties. Moreover, temperature humidity index (THI) and the indicator variable of heatwaves were introduced to consider the interaction between temperature and humidity and measure the influence of high temperature, which has been rarely considered. In the system level analysis, the results showed that the selected factors have the different influence over the different time periods within a day. Especially, scorching heat and non-working days differently affect the demand for public bikes by hours. Also, it was observed that high temperature over 30°C reduces the bicycle usage, which revealed the necessity of taking into account not only severe colds but also heatwaves in the prediction of the demand. By clustering analysis, the stations were partitioned into the three clusters. One cluster shows the strong peak in the morning while two others have peaks in the evening. The effects of weather conditions and non-working days on the demand for public bicycles were different depending on the clusters, which seemed to be related to the main purposes of bike usage in the clusters.

Bike-sharing-boom – rozwój nowych form zrównoważonego transportu w Polsce na przykładzie roweru publicznego

The public bicycle system (bike-sharing system) is becoming an increasingly common element of the transport system in urban space in Poland and in the world. The main reasons for implementing this solution in urban areas include the need to increase the efficiency of urban transport systems and to reduce the problems created by the pressure of traditional means of transport on the environment. Public bike is also successfully becoming an element of multimodal transport by connecting with other public transport. In Poland, bike-sharing has been operating since 2008, expanding its range with each subsequent year for new cities, as well as rural areas. The study analyzed changes in the number of systems in Poland in 2017-2018 – in the period of the greatest development of this form of transport in the studied area. The analysis was based on the indicators of the number of public bicycle stations on a given area and the number of bicycles on the background of the number of inhabitants of the analyzed cities. The work also compared bicycle rental rates for individual systems operating in Poland. On the basis of the analyzed data, the directions of public bicycle development in Poland were also determined.

Design of public bicycle scheduling model based on data mining algorithm

Guangzhou Public Bicycle System has been the largest bike-sharing program in the world. The software of the system was developed by our research team. To meet the fluctuating demand for bicycles and for vacant lockers at each station, employees need to actively shift bicycles between stations by a fleet of vehicles. Hybrid GRA-SP metaheuristic which incorporate a path-relinking procedure have been successfully applied for different combinatorial problems. Data mining is a process that uses a variety of data analysis tools to discover patterns and relationships in data. In this paper, a new hybrid data mining metaheuristic combines GRA-SP which incorporate path-relinking procedure with data mining process is proposed and some improvement are made.

Critical Success Factors and Performance Evaluation Model for the Development of the Urban Public Bicycle System

The public bicycle is a low emission vehicle that provides social, environmental and traffic related benefits. Currently, many cities around the world have integrated a public bicycle system (PBS) into their urban blueprint as a new transport model for mainstream public transport system. Taipei City has also set up a PBS. The main purpose of this study is to create a model and evaluate the service performance of Taipei’s PBS by adopting the Fuzzy Delphi and IPA methods. The study results can provide the operators with the necessary foundation for operational improvements. Moreover, the study architecture, methods and model can serve as important reference to promote PBS in other cities.

Analysis and Calculation of Public Bicycle Site Scale in Hohhot

This article makes a statistic through the full day about lend and return cars of Public bike rental point, Calculate the Poor borrowing of each time period of each site, loan return coefficient and the peak borrow the car coefficient. At the same time, using these data and the public bicycle turnover rate to calculate the peak time lease scale. Layout of public bicycle site according to the results calculated can make resources rational and convenient for citizens to travel.

A GPS-Based Classification of Visitors’ Vehicular Behavior in a Protected Area Setting

As tourism and visitation increases to parks and protected areas worldwide, concerns regarding degradation of natural resources and visitor experiences also increase. As such, understanding visitor use patterns and spatial characteristics is important for better management of social and ecological resources. In many parks and protected areas, transportation systems (including park roads, parking lots, personal vehicles, public transit services, bicycle and/or pedestrian paths, and Intelligent Transportation Systems (ITS) that help deliver visitors to their destinations within parks) are a primary way for tourists and visitors to interact with and experience natural environments. Transportation systems designed with visitor use patterns in mind can both provide a positive experience for tourists as well as minimize impacts to natural resources within parks and protected areas. Our research used Global Positioning System (GPS)-based technology and a statistical classification procedure to examine spatial and temporal patterns of vehicular visitation in the Moose-Wilson corridor of Grand Teton National Park. While GPS-based technology has been used in parks and protected areas to study the spatial behavior of hikers and bikers, it has not been widely utilized to study the spatial behavior patterns of visitors travelling in vehicles to park destinations. Similarly, statistical classifications have been used to understand visitor behavior patterns in parks and protected areas, but are rarely applied to spatial data such as GPS tracks of visitor spatial movements. This classification based on spatial behavior resulted in the categorization of visitors into three types: Opportunistic Commuters, Wildlife/Scenery Viewers, and Hikers. These results expand existing literature suggesting that interpretable patterns of visitor spatial movements can result from classification studies using GPS-based collection of visitor behavior data. Understanding these patterns of visitor behavior is important for the management of social and natural resource conditions at park destinations as well as visitor experiences within the transportation corridor, as different types of visitors often exhibit different spatial behavior patterns. The classification and associated patterns of visitor behavior have important implications for managers of parks and protected area as different types of visitors may require different transportation and information needs in order to achieve their desired experience and minimize ecological impacts.Subscribe to JPRA

Design of public bicycle scheduling model based on data mining algorithm

Design of public bicycle scheduling model based on data mining algorithm

A simulation model for public bike-sharing systems

Urban areas are in need of efficient and sustainable mobility services. Public bicycle sharing systems stand out as a promising alternative and many cities have invested in their deployment. This has led to a continuous and fast implementation of these systems around the world, while at the same time, research works devoted to understand the system dynamics and deriving optimal designs are being developed. In spite of this, many promoting agencies have faced the impossibility of evaluating a system design in advance, increasing the uncertainty on its performance and the risks of failure. This paper describes the development of an agent-based simulation model to emulate a bike-sharing system. The goal is to obtain a tool to evaluate and compare different alternatives for the system design before their implementation. This tool will support the decision-making process in all the stages of implementation, from the strategical planning to the daily operation. The main behavioral patterns and schemes for all agents involved are designed and implemented into a Matlab programming code. The model is validated against real data compiled from the Barcelona's Bicing system showing good accuracy.

Public bicycle system – analysis of selected practices on the example of Poland

Public bicycle system – analysis of selected practices on the example of Poland