A model for the layout of bike stations in public bike‐sharing systems

The problem of designing a layout of bike stations for public bike‐sharing systems entails selecting a number of stations and then constructing them within a planning area having many bike traffic zones and candidate bike stations. In this paper, we proposed a mathematical model to formulate the layout of public bike stations with the objective of minimizing users' total travel time and investment budget constraints. The model can guarantee that the needs for picking up and dropping off bikes amidst all bike travel demands are satisfied. Using this model, the number and locations of bike stations and the number of bikes and parking lockers at each bike station can be simultaneously determined. A typical example solved by lingo solver is created to illustrate the proposed model. Copyright © 2015 John Wiley & Sons, Ltd.     

A simulation tool for bicycle sharing systems in multimodal networks

This paper presents a methodology for modelling an urban transport system, integrating public bicycles in a multi-modal network. A bike cost function that reproduces the effect of slopes on cycling speeds is proposed. Also, the effect of traffic levels on the attractiveness of cycling routes is taken into account. The model applies the modal split and network assignment phases in a multimodal network with different classes of users. It has been verified over a test network and then validated by applying it to a real case in the city of Santander in Spain. The results obtained make this model a useful decision-making tool to encourage the use of the public bicycle from a sustainable development point of view.     

Dockless bike-sharing systems: what are the implications?

ABSTRACT

The emergence of dockless bike-sharing services has revolutionised bike-sharing markets in recent years, and the dramatic growth of shared bike fleets in China, as well as their rapid expansion throughout the world, exceeds prior expectations. An understanding of the impacts of these new dockless bike-sharing systems is of vital importance for system operations, transportation and urban planning research. This paper provides a first overview of the emerging literature on implications of dockless bike-sharing systems for users' travel behaviour, user experience, and relevant social impacts of dockless bike-sharing systems. Our review suggests that the dockless design of bike-sharing systems significantly improves users' experiences at the end of their bike trips. Individuals can instantly switch to a dockless shared bike without the responsibility of returning it back to a designated dock. Additionally, the high flexibility and efficiency of dockless bike-sharing often makes the bike-sharing systems' integration with public transit even tighter than that of traditional public bikes, providing an efficient option for first/last-mile trips. The GPS tracking device embedded in each dockless shared bike enables the unprecedented collection of large-scale riding trajectory data, which allow scholars to analyse people's travel behaviour in new ways. Although many studies have investigated travel satisfaction amongst cyclists, there is a lack of knowledge of the satisfaction with bikeshare trips, including both station-based and dockless bikeshare systems. The availability and usage rates of dockless bike-sharing systems implies that they may seriously impact on individuals' subjective well-being by influencing their satisfaction with their travel experiences, health and social participation, which requires further exploration. The impact of dockless bike-sharing on users' access to services and social activities and the related decreases in social exclusion are also relevant issues about which knowledge is lacking. With the increases in popularity of dockless shared bikes in some cities, issues related to the equity and access and the implications for social exclusion and inequality are also raised.     

Locating rental stations and bikeways in a public bike system

To determine the spatial distribution of rental stations and bikeways in a public bike system, this paper proposes a facility location and network design model. The model is developed as a multi-objective programing problem that considers four objectives (minimizing cyclist risk, maximizing cyclist comfort, minimizing adverse impacts on traffic and maximizing service coverage) and multiple constraints (monetary budget, network connectivity, station spacing, bikeway types, station number and value ranges of decision variables). The ε-constraint method solves the programing problem for the public bike system in Daan District, Taipei City, Taiwan. The nine non-dominated alternatives generated are all markedly better than existing locations of rental stations and bikeways. Scenario analysis results indicate that increasing the construction budget for bikeways significantly improves cyclist safety and comfort whilst increasing the adverse impact on traffic. Planners can use this model to develop public bike systems that spatially integrate rental stations and bikeway networks.     

Promoting public bike-sharing: A lesson from the unsuccessful Pronto system

In 2014, Seattle implemented its own bike-sharing system, Pronto. However, the system ultimately ceased operation three years later on March 17th, 2017. To learn from this failure, this paper seeks to understand factors that encourage, or discourage, bike-sharing trip generation and attraction at the station level. This paper investigates the effects of land use, roadway design, elevation, bus trips, weather, and temporal factors on three-hour long bike pickups and returns at each docking station. To address temporal autocorrelations and the nonlinear seasonality, the paper implements a generalized additive mixed model (GAMM) that incorporates the joint effects of a time metric and time-varying variables. The paper estimates models on total counts of pickups and returns, as well as pickups categorized by user types and by location. The results clarify that effects of hilly terrain and the rainy weather, two commonly perceived contributors to the failure. Additionally, results suggest that users in the University District, presumably mostly university students, tend to use shared bikes in neighborhoods with a higher household density and a higher percentage of residential land use, and make bike-sharing trips regardless workdays or non-workdays. The paper also contributes to the discussion on the relationship between public transportation service and bike-sharing. In general, users tend to use bike-sharing more at stations that have more scheduled bus trips nearby. However, some bike-sharing users may shift to bus services during peak hours and rainy weather. Several strategies are proposed accordingly to increase bike ridership in the future.     

Incentivized vehicle relocation in vehicle sharing systems

The asymmetric demand-offer problem represents a major challenge for one-way vehicle sharing systems (VSS) affecting their economic viability as it necessitates the engagement of considerable human (and financial) resources in relocating vehicles to satisfy customer demand. In this paper, we propose a novel approach which involves user-based vehicle relocations to address supply-and-demand mismatches; in our approach, VSS users are offered price incentives so as to accept picking up their vehicle from an oversupplied station and/or to drop it off to an under-supplied station. The system incentivizes users based on the priorities of vehicle relocations among stations, taking into account the fluctuating demand for vehicles and parking places at different stations over time. A graph-theoretic approach is employed for modeling the problem of allocating vehicles to users in a way that maximizes the profit of the system taking into account the budget the VSS can afford to spend for rewarding users, as well as the users’ strategic behavior. We present two different schemes for incentivizing users to act in favour of the system. Both schemes consider budget constraints and are truthful and budget-feasible. We have extensively evaluated our approach through simulations which demonstrated significant gain with respect to the number of completed trips and system revenue. We have also validated our approach through pilot trials conducted in a free-floating e-motorbike sharing system in the framework of an EU-funded research project.     

The station-free sharing bike demand forecasting with a deep learning approach and large-scale datasets

The station-free sharing bike is a new sharing traffic mode that has been deployed in a large scale in China in the early 2017. Without docking stations, this system allows the sharing bike to be parked in any proper places. This study aimed to develop a dynamic demand forecasting model for station-free bike sharing using the deep learning approach. The spatial and temporal analyses were first conducted to investigate the mobility pattern of the station-free bike sharing. The result indicates the imbalanced spatial and temporal demand of bike sharing trips. The long short-term memory neural networks (LSTM NNs) were then developed to predict the bike sharing trip production and attraction at TAZ for different time intervals, including the 10-min, 15-min, 20-min and 30-min intervals. The validation results suggested that the developed LSTM NNs have reasonable good prediction accuracy in trip productions and attractions for different time intervals. The statistical models and recently developed machine learning methods were also developed to benchmark the LSTM NN. The comparison results suggested that the LSTM NNs provide better prediction accuracy than both conventional statistical models and advanced machine learning methods for different time intervals. The developed LSTM NNs can be used to predict the gap between the inflow and outflow of the sharing bike trips at a TAZ, which provide useful information for rebalancing the sharing bike in the system.     

Applying spatial-temporal analysis and retail location theory to public bikes site selection in Taipei

In order to turn Taipei into a sustainable, green metropolis, in 2009, the Department of Transportation of Taipei City Government launched a public bike rental system (YouBike) to meet people’s daily commute and/or leisure needs. Given that users may return bikes to sites differing from their starting locations, rental stations frequently lack bikes or bike racks. This study sought to identify lacking-bike and/or lacking-bike rack hot spots utilizing spatial-temporal analysis. In addition, it applied retail location theory to determine site selection of further rental stations. Historical data indicated that shortage of bikes was much more severe than shortage of bike racks in the YouBike public bike system and lacking-bike and lacking-bike rack hot spots were clustered significantly. The study demonstrated that spatial-temporal analysis can be used to effectively identify rental stations’ spatial patterns, determine the most suitable locations for further installation of rental stations, help to provide public bike users with a more effective rental system, and greatly assist public bikes’ operational management and decision-making in Taiwan.     

Capturing the conditions that introduce systematic variation in bike-sharing travel behavior using data mining techniques

The potential of smart-card transactions within bike-sharing systems (BSS) is still to be explored. This research proposes an original offline data mining procedure that takes advantage of the quality of these data to analyze the bike usage casuistry within a sharing scheme. A difference is made between usage and travel behavior: the usage is described by the actual trip-chaining gathered with every smart-card transaction and is directly influenced by the limitations of the BSS as a public renting service, while the travel behavior relates to the spatio-temporal distribution, the travel time and trip purpose. The proposed approach is based on the hypothesis that there are systematic usage types which can be described through a set of conditions that permit to classify the rentals and reduce the heterogeneity in travel patterns. Hence, the proposed algorithm is a powerful tool to characterize the actual demand for bike-sharing systems. Furthermore, the results show that its potential goes well beyond that since service deficiencies rapidly arise and their impacts can be measured in terms of demand. Consequently, this research contributes to the state of knowledge on cycling behavior within public systems and it is also a key instrument beneficial to both decision makers and operators assisting the demand analysis, the service redesign and its optimization.     

Promoting bike-and-ride: The Dutch experience

The number of policy initiatives to promote the use of bike-and-ride, or the combined use of bicycle and public transport for one trip, has grown considerably over the past decade as part of the search for more sustainable transport solutions. This paper discusses the experiences with, and impacts of, such initiatives in the Netherlands. The Dutch measures to promote bicycle use in access trips have been generally successful. A country-wide program to upgrade regular and secure bicycle parking at train stations has led to an increase in user satisfaction and a growth in bicycles parked at stations. Smaller programs to stimulate the combined use of bike-and-bus have resulted in an increase in bicycle use, bus use, and share of infrequent bus passengers. Bicycle lockers at bus stops are hardly used by bus passengers, due in part to the dominance of students among bus users as well as the relatively high price of lockers in comparison to the value of bicycles used for access trips. Measures to promote the use of the bicycle in egress trips have met with more varying results. Projects to introduce leasing bicycles for egress trips have failed to attract passengers, for both train and bus services. In contrast, the introduction of flexible rental bicycles at train stations has resulted in a small reduction in car use, growth in train trips, and growth in bicycle use for non-recurrent trips. The Dutch experiences suggest some lessons for promoting bike-and-ride in countries and cities with a less well-developed bicycle infrastructure.     

Bike Share: A Synthesis of the Literature

This paper begins by providing an overview of bike share programs, followed by a critical examination of the growing body of literature on these programs. This synthesis of previous works, both peer-reviewed and gray, includes an identification of the current gaps in knowledge related to the impacts of bike sharing programs. This synthesis represents a critically needed evaluation of the current state of global bike share research, in order to better understand, and maximize the effectiveness of current and future programs. Several consistent themes have emerged within the growing body of research on bike share programs. Firstly, the importance bike share members place on convenience and value for money appears paramount in their motivation to sign up and use these programs. Secondly, and somewhat counter intuitively, scheme members are more likely to own and use private bicycles than nonmembers. Thirdly, users demonstrate a greater reluctance to wear helmets than private bicycle riders and helmets have acted as a deterrent in jurisdictions in which helmets are mandatory. Finally, and perhaps most importantly from a sustainable transport perspective, the majority of scheme users are substituting from sustainable modes of transport rather than the car.     

Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto

Bike Share Toronto is Canada’s second largest public bike share system. It provides a unique case study as it is one of the few bike share programs located in a relatively cold North American setting, yet operates throughout the entire year. Using year-round historical trip data, this study analyzes the factors affecting Toronto’s bike share ridership. A comprehensive spatial analysis provides meaningful insights on the influences of socio-demographic attributes, land use and built environment, as well as different weather measures on bike share ridership. Empirical models also reveal significant effects of road network configuration (intersection density and spatial dispersion of stations) on bike sharing demands. The effect of bike infrastructure (bike lane, paths etc.) is also found to be crucial in increasing bike sharing demand. Temporal changes in bike share trip making behavior were also investigated using a multilevel framework. The study reveals a significant correlation between temperature, land use and bike share trip activity. The findings of the paper can be translated to guidelines with the aim of increasing bike share activity in urban centers.     

Objective correlates and determinants of bicycle commuting propensity in an urban environment

ObjectiveBicycle use for commuting is being encouraged not only to address physical inactivity, but also vehicular congestion, air pollution and climate change. The current study aimed to ascertain the urban environmental correlates and determinants of bicycle use for commuting (bicycle commuting) among the working or studying population in Barcelona, Spain.MethodsAdults (n = 769; 52% females) recruited whilst commuting within Barcelona (Spain) responded to a comprehensive telephone survey concerning their travel behaviour. Based upon responses collected from June 2011 to May 2012, participants were categorised into four groups: frequent bicyclists, infrequent bicyclists, willing non-bicyclists, and unwilling non-bicyclists. The determinants of frequency and willingness (propensity) to commute by bicycle were assessed by multinomial logistic regression models adjusted for potential confounders and covariates.ResultsThe number of public bicycle stations surrounding the home address and amount of greenness surrounding the work/study address were significant positive determinants of bicycle commuting propensity. On the other hand, the number of public transport stations surrounding the home address and elevation of the work/study address were significant negative determinants of bicycle commuting propensity. Individual age, education level, gender, nationality, physical activity level and commute distance significantly affected this propensity.ConclusionGreater availability of public bicycle stations and higher levels of urban greenness may increase bicycle use by adults commuting within a city such as Barcelona, Spain. Electrically-assisted public bicycles may address the challenge of elevation, making this system a more competitive mode against traditional motorised public transport.     

Modelling bicycle use intention: the role of perceptions

Users’ perceptions are identified as key elements to understand bicycle use, whose election cannot be explained with usual mobility variables and socio-economic characteristics. A hybrid model is proposed to model the intention of bicycle use; it combines a structural equations model that captures intentions and a choice model. The framework is applied to a case of a university campus in Madrid that is studying a new internal bike system. Results show that four latent variables (convenience, pro-bike, physical determinants and external restrictions) help explaining intention to use bike, representing a number of factors that are linked to individual perceptions.     

Short-term planning and policy interventions to promote cycling in urban centers: Findings from a commute mode choice analysis in Barcelona,Spain

BackgroundCycling for transportation has become an increasingly important component of strategies to address public health, climate change, and air quality concerns in urban centers. Within this context, planners and policy makers would benefit from an improved understanding of available interventions and their relative effectiveness for cycling promotion. We examined predictors of bicycle commuting that are relevant to planning and policy intervention, particularly those amenable to short- and medium-term action.MethodsWe estimated a travel mode choice model using data from a survey of 765 commuters who live and work within the municipality of Barcelona. We considered how the decision to commute by bicycle was associated with cycling infrastructure, bike share availability, travel demand incentives, and other environmental attributes (e.g., public transport availability). Self-reported and objective (GIS-based) measures were compared. Point elasticities and marginal effects were calculated to assess the relative explanatory power of the independent variables considered.ResultsWhile both self-reported and objective measures of access to cycling infrastructure were associated with bicycle commuting, self-reported measures had stronger associations. Bicycle commuting had positive associations with access to bike share stations but inverse associations with access to public transport stops. Point elasticities suggested that bicycle commuting has a mild negative correlation with public transport availability (−0.136), bike share availability is more important at the work location (0.077) than at home (0.034), and bicycle lane presence has a relatively small association with bicycle commuting (0.039). Marginal effects suggested that provision of an employer-based incentive not to commute by private vehicle would be associated with an 11.3% decrease in the probability of commuting by bicycle, likely reflecting the typical emphasis of such incentives on public transport.ConclusionsThe results provide evidence of modal competition between cycling and public transport, through the presence of public transport stops and the provision of public transport-oriented travel demand incentives. Education and awareness campaigns that influence perceptions of cycling infrastructure availability, travel demand incentives that encourage cycling, and policies that integrate public transport and cycling may be promising and cost-effective strategies to promote cycling in the short to medium term.     

Built environment effects on the integration of dockless bike-sharing and the metro

Bike-sharing provides a convenient feeder mode for connecting to a metro and is believed to be an efficient way to solve the first- and last-mile problem. Despite the increasing attention paid on the use of bike-sharing, few studies have investigated how built environment factors affect the integrated use of dockless bike-sharing (DBS) and the metro. Using data from one of the largest DBS operators in China (Ofo), this paper employed a series of negative binomial regressions to examine the effect of the built environment on the integrated use of DBS and the metro, using Shenzhen as a case study. The findings show that mixed land use is positively related to integrated use. Residential areas have higher access-integrated rates during the morning peak hours, while industrial areas are associated with more integrated uses, connecting factories and metro stations. Furthermore, parks and public squares encourage both access- and egress-integrated use during peak times. Transportation facility features, including bus stops and dedicated bike lanes, are positively related to integrated use, while areas with dense metro distribution and main streets with many intersections are negatively related. Transfer distance also plays a crucial and negative role in integrated use. In addition, metro stations that are closer to the city center with a higher number of passengers are more likely to be integrated with bike-sharing. These findings can be used to collectively facilitate a connection between cycling and metro transit by creating a bicycle-friendly environment.     

Free-floating bike sharing: Solving real-life large-scale static rebalancing problems

Free-floating bike sharing (FFBS) is an innovative bike sharing model. FFBS saves on start-up cost, in comparison to station-based bike sharing (SBBS), by avoiding construction of expensive docking stations and kiosk machines. FFBS prevents bike theft and offers significant opportunities for smart management by tracking bikes in real-time with built-in GPS. However, like SBBS, the success of FFBS depends on the efficiency of its rebalancing operations to serve the maximal demand as possible.Bicycle rebalancing refers to the reestablishment of the number of bikes at sites to desired quantities by using a fleet of vehicles transporting the bicycles. Static rebalancing for SBBS is a challenging combinatorial optimization problem. FFBS takes it a step further, with an increase in the scale of the problem. This article is the first effort in a series of studies of FFBS planning and management, tackling static rebalancing with single and multiple vehicles. We present a Novel Mixed Integer Linear Program for solving the Static Complete Rebalancing Problem. The proposed formulation, can not only handle single as well as multiple vehicles, but also allows for multiple visits to a node by the same vehicle. We present a hybrid nested large neighborhood search with variable neighborhood descent algorithm, which is both effective and efficient in solving static complete rebalancing problems for large-scale bike sharing programs.Computational experiments were carried out on the 1 Commodity Pickup and Delivery Traveling Salesman Problem (1-PDTSP) instances used previously in the literature and on three new sets of instances, two (one real-life and one general) based on Share-A-Bull Bikes (SABB) FFBS program recently launched at the Tampa campus of University of South Florida and the other based on Divvy SBBS in Chicago. Computational experiments on the 1-PDTSP instances demonstrate that the proposed algorithm outperforms a tabu search algorithm and is highly competitive with exact algorithms previously reported in the literature for solving static rebalancing problems in SBSS. Computational experiments on the SABB and Divvy instances, demonstrate that the proposed algorithm is able to deal with the increase in scale of the static rebalancing problem pertaining to both FFBS and SBBS, while deriving high-quality solutions in a reasonable amount of CPU time.     

Using the sustainable modified TAM and TPB to analyze the effects of perceived green value on loyalty to a public bike system

This article explores the effects of perceived green value, perceived green usefulness, perceived pleasure to use, subjective norms and perceived behavioral control on green loyalty to a public bike system. The mediators between perceived green value and green loyalty and a moderator of general attitude toward protecting the natural environment are also discussed. The aim of this research was to understand how to establish green loyalty via the other dimensions based on the sustainable modified technology acceptance model (modified TAM), the theory of planned behavior (TPB), and a moderator. The findings reveal that perceived pleasure to use and subjective norms have the strongest power to influence loyalty for both users and non-users. The implications of this finding are that fun in people’s lives has a strong influence on sustainable continuous use of public bikes, and that subjective norms are more effective for non-users. In addition, environmental attitude has stronger moderating effects for non-users than for users on perceived green usefulness, perceived pleasure and subjective norms. Therefore, governmental policies should promote the attitude of protecting the natural environment, perceptions of pleasure, and subjective norms so as to increase green loyalty to public bike-sharing.     

Managing a smart bicycle system when demand outstrips supply: the case of the university community in Seville

Of the many public initiatives used to promote the use of bicycles in the urban environment, the one that has achieved the most spectacular results in a short period of time is the public bicycle hire system. The experience of Seville is one of the most successful internationally, where 6.6 % of mechanised trips were being made by bicycle within 30 months. This paper analyses this experience in the university community, which represents one-third of system users. We conclude that the people who are most satisfied with the system are those who use it for leisure and recreation activities, non-residents of the city, more environmentally aware people and those who have no alternative mode of transportation. Their satisfaction is also closely linked to their appreciation of the bicycles’ level of comfort, the ease with which users can hire bicycles and return them and the small amount of paperwork involved required to sign up for the system. However, user appreciation has fallen over time because the system’s rapid success has caused it to become overloaded. This experience therefore provides one main lesson: the system’s success can result in eventual difficulties.