Public Bike-sharing Systems Research Articles

User intention to adopt public bicycle sharing system: a priori acceptance approach

ABSTRACT Bicycle-sharing services have received worldwide attention as a sustainable form of transportation. This study explores a priori acceptance of public bicycle-sharing system (PBSS) in India, which is still in the early phases of adopting PBSS. The effects of psychological factors, such as perceived usefulness (PU), perceived ease of use (PEoU), perceived fun (PF), health value (HV), and environment values (EV), on intention to use PBSS are studied, utilizing an extended technology acceptance model. 747 samples were collected from online questionnaires in Dehradun, India. Results of Structural Equation Modelling revealed that intention to use PBSS is strongly predicted by PU and PF together, while PF mediates the influence of PEoU. Furthermore, EV and HV generate positive behavior intention to use PBSS through PU, PF, and PEoU. The study suggests promoting PBSS as a green and active transportation mode offering high PU and enjoyment, with theoretical and practical implications discussed.

Delayed effects of air pollution on public bike-sharing system use in Seoul, South Korea: A time series analysis

Background:As a complementary means to urban public transit systems, public bike-sharing provides a green and active mode of sustainable mobility, while reducing carbon-dioxide emissions and promoting health. There has been increasing interest in factors affecting bike-sharing usage, but little is known about the effect of ambient air pollution. Method:To assess the short-term impact of daily exposure to multiple air pollutants (PM2.5, PM10, NO2, and O3) on the public bike-sharing system (PBS) usage in Seoul, South Korea (2018–2021), we applied a quasi-Poisson generalized linear model combined with a distributed lag nonlinear model (DLNM). The model was adjusted for day of the week, holiday, temperature, relative humidity, and long-term trend. We also conducted stratification analyses to examine the potential effect modification by age group, seasonality, and COVID-19. Results:We found that there was a negative association between daily ambient air pollution and the PBS usage level at a single lag day 1 (i.e., air quality a day before the event) across all four pollutants. Our results suggest that days with high levels of air pollutants (at 95th percentile) are associated with a 0.91% (0.86% to 0.96%) for PM2.5, 0.89% (0.85% to 0.94%) for PM10, 0.87% (0.82% to 0.91%) for O3, and 0.92% (0.87% to 0.98%) for NO2, reduction in cycling behavior in the next day compared to days with low levels of pollutants (at 25th percentile). No evidence of effect modification was found by seasonality, age nor the COVID-19 pandemic for any of the four pollutants. Conclusions:Our findings suggest that high concentrations of ambient air pollution are associated with decreased rates of PBS usage on the subsequent day regardless of the type of air pollutant measured.

Assessment of the Public Bicycle Sharing System (PBSS) in Urban Mobility: A Case Study of Bhubaneswar, Odisha

Assessment of the Public Bicycle Sharing System (PBSS) in Urban Mobility: A Case Study of Bhubaneswar, Odisha

Effects of Mobi’s equity initiatives on public bike share access and use

Since its launch, Vancouver’s public bike share system has implemented changes to reduce barriers, enhance uptake, and make bike sharing more equitable. These include hiring an equity coordinator, expanding the service area, adding e-bikes to the fleet, reducing the age eligibility, reducing financial barriers through their Community Pass, and partnering with community organizations. We used a mixed methods study design to assess the impact of these initiatives on access to and use of public bike share. We found that the service area expansion reduced inequities in spatial access by socioeconomic status, age, and race, but higher socioeconomic status and white populations continue to have better access. Our analysis of system and survey data, and interviews with community organizations, revealed how the Community Pass is enhancing transport justice by expanding the benefits of bike share and improving access to opportunities for more diverse populations.

Micromobility systems and disease transmission: a spatially explicit agent-based approach

We propose a novel micro-level and spatially explicit agent-based modeling framework dubbed TranEpiSim to model the spread of infectious diseases through micromobility systems and a baseline population in an urban area. A case study is conducted on the Chicago City public bikesharing system to demonstrate the ability of the model to isolate the role of transportation as a vector and assess the efficacy of the model. Results show that the emergence of viral disease through micromobility transportation is possible, but the overall impact of the system on the disease dynamics in a worst-case scenario, especially with the current size of the system, is rather small. The proposed model offers a comprehensive approach to estimate the impact of micromobility (and more generally, specific transportation modes) on disease spread by considering infections that occur both at destinations and in/on transportation vehicles and infrastructure. The spatial pattern for the risk of exposure shows a higher risk in the central business district and north of it, where most of the shared bike transportation occurs. Because of its intrinsic features, the proposed framework is uniquely placed to assess the efficacy of interventions and make trade-offs between competing scenarios when dealing with epidemics.

Comparing e-bike and conventional bicycle use patterns in a public bike share system: A case study of Richmond, VA

Bicycle-sharing systems have emerged as a viable transportation alternative in numerous urban areas, owing to their multifaceted benefits. These benefits include reduced transportation expenses, health improvements, and decreased emission levels. While extensive research has been conducted on travel behaviors in shared bicycle systems, there is currently a lack of research on travel behaviors changes with the introduction of e-bikes. This study presents a comprehensive analysis of the similarities and differences between e-bike (pedelec) and conventional bicycle use in a bike share system in Richmond City, Virginia.The results show that pedelecs are generally associated with longer trip distances, shorter trip times, higher speeds, and lower rates of uphill elevation change. The origin–destination analysis considering the business, mixed use, residential, and other uses shows extremely similar trends, with a large number of trips staying within either business or residential locations or mixed use. The roadway use analysis shows that pedelecs are used farther outside of the city than bikes.

Enhancing Urban Mobility with Self-Tuning Fuzzy Logic Controllers for Power-Assisted Bicycles in Smart Cities.

In smart cities, bicycle-sharing systems have become an essential component of the transportation services available in major urban centers around the globe. Due to environmental sustainability, research on the power-assisted control of electric bikes has attracted much attention. Recently, fuzzy logic controllers (FLCs) have been successfully applied to such systems. However, most existing FLC approaches have a fixed fuzzy rule base and cannot adapt to environmental changes, such as different riders and roads. In this paper, a modified FLC, named self-tuning FLC (STFLC), is proposed for power-assisted bicycles. In addition to a typical FLC, the presented scheme adds a rule-tuning module to dynamically adjust the rule base during fuzzy inference processes. Simulation and experimental results indicate that the presented self-tuning module leads to comfortable and safe riding as compared with other approaches. The technique established in this paper is thought to have the potential for broader application in public bicycle-sharing systems utilized by a diverse range of riders.

A data-driven agent-based simulation of the public bicycle-sharing system in Sejong city

In this study, we propose a data-driven agent-based model for simulating Eoulling, the public bicycle-sharing systems (PBSSs) in Sejong City, the administrative capital of South Korea. Most existing models for PBSSs based on top-down approaches have limitations in reflecting Eoulling users’ behavioral characteristics and analyzing their convenience. Unlike these, the proposed model is based on a bottom-up approach of agent-based simulation. We model each user as an agent to capture their bicycle rental and return behaviors, and analyze user convenience through interactions with bicycle station agent models. To improve model fidelity, multiple parameters for determining agent behaviors are extracted from the actual operations data of Eoulling, along with the population and geographic information of Sejong City. The validation results showed that the proposed model accurately describes the behavioral characteristics. We provide a workable solution addressing multiple concerns with Eoulling by evaluating its utilization and user convenience in virtual scenarios via model simulations.

Scalability evaluation of forecasting methods applied to bicycle sharing systems

Public Bicycle Sharing Systems (BSS) have spread in many cities for the last decade. The need of analysis tools to predict the behavior or estimate balancing needs has fostered a wide set of approaches that consider many variables. Often, these approaches use a single scenario to evaluate their algorithms, and little is known about the applicability of such algorithms in BSS of different sizes. In this paper, we evaluate the performance of widely known prediction algorithms for three sized scenarios: a small system, with around 20 docking stations, a medium-sized one, with 400+ docking stations, and a large one, with more than 1500 stations. The results show that Prophet and Random Forest are the prediction algorithms with more consistent results, and that small systems often have not enough data for the algorithms to perform a solid work.

The spatial-temporal evolution of public bike-sharing systems in China: The disruption of dockless bike-sharing emergence

Many Chinese cities have implemented the station-based public bike-sharing systems (PBSs). However, the recent spread of the dockless bike-sharing systems (DBSs) has significantly impacted PBSs, which has not been thoroughly investigated in previous research. This study bridges this research gap by examining the spatiotemporal evolution of China’s PBSs, with a particular focus on the changes brought by the entry of DBSs, by analyzing data on the start and end dates of PBSs and DBSs across the country. We utilized logistic regression to identify factors that may influence the decision to discontinue PBS operations, and examined selected representative cities to uncover the underlying structural and political factors affecting PBSs’ persistency. Findings reveal that the entry of DBSs disrupts PBS operations in many cities. PBSs are less likely to cease operation in cities with subways and in coastal areas, but more likely to do so in densely populated cities. Furthermore, technical advancements, operational consistency, adherence to government guidelines, and a well-planned station layout contribute to the continued viability of PBSs amidst the challenges posed by DBSs. Based on these results, we suggest that cities should improve the competitiveness of PBSs through better integration with public transit and optimization of PBS operations.

Public Bicycle Sharing in India: Lessons Learned from Implementation in Three Cities

This working paper examines the growth and challenges of public bicycle-sharing (PBS) systems in India, within the context of global efforts towards low-carbon transport. While many Indian cities initially adopted rental-based PBS systems with limited bicycle availability, Mysuru, Bhopal, and Pune emerged as pioneers, introducing innovative models based on public-private partnerships, smart technology, and quality service incentives.

Ranking barriers and optimum solutions to implement public bicycle-sharing system in cities

Decision makers around the world adopted public bicycle-sharing systems (PBSS) due to their easy access at major strategic locations and user-friendly operations. The documented studies identify various barriers and solutions for PBSS, however, studies on identification of optimum solution for varied conditions are limited. Therefore, the purpose of this study is to rank the barriers and solutions for PBSS implementation for Indian urban areas. The framework is robust so that the methodology can apply globally. Initially, 31 PBSS barriers and 14 solutions were identified after reviewing literature and assessment from professionals. Then two multi-criteria decision-making methods were integrated to rank barriers and solutions for Indian cities using an expert opinion survey. The result shows that infrastructure barriers of the city, social barrier for cycling and travel characteristics barriers have more impact in the main criteria, whereas the presence of exclusive bicycle lanes, government policies and the provision of modified and e-bicycles are found to be the most optimum solutions and have potential to overcome the influence of barriers. The outcome of this research will help various stakeholders to develop pro-cycling policies, make decisions on financial resource allocation, understand the existing barriers and solutions.

Public bicycle sharing systems control and performance evaluation: A Petri net-based approach

Public bicycle sharing systems (PBSS) allow citizens to move between two points within a region using bicycles, being composed of stations where users can either pick up or return bicycles after using them. Depending on the demand for bicycles, stations may either become empty or full of bicycles. This problem is usually solved by means of a vehicle that exchanges bicycles among the stations following some balancing strategy. In this paper, we propose a model for PBSSs using generalized stochastic Petri nets with external control, a Petri net with an external agent that decides how to execute the balancing strategy. The main advantage of our model is that it allows different balancing strategies to be implemented without changing the Petri net structure. In addition, since the model is a Petri net, we can easily implement it by making a Petri net simulator built with the incidence matrix associated with the Petri net model. We also propose two balancing strategies and validate both the simulation algorithm and the balancing strategies by applying them to the performance evaluations of the model of a real system, named Integra UFRJ PBSS. The performance evaluation of the system under the balacing strategies have shown that both strategies considerably reduce the times, in average, that stations remain full or empty throughout the system operation, solving problems related to stations being empty of full; in particular, the first strategy reduced those times in such a way that no more than five percent of the users of each station had trouble returning their bicycles due to stations being full, whereas the second strategy reduced the percentage of lost users due to stations being empty to no more than five percent for each station.

Determining the Sustainable Development Strategies and Adoption Paths for Public Bike-Sharing Service Systems (PBSSSs) under Various Users’ Considerations

Public bike-sharing service systems (PBSSSs) offer an alternative to satisfy users’ needs for short-trip connections. The PBSSSs provide options for short-trip connections and diversify the service experience for different users. PBSSSs also play a critical role in enabling urban citizens to reduce the needs to drive their cars and using public transport instead. This study explores the service performance of the public bike-sharing service systems for three styles of users. It proposes the integrated evaluation model of the public bike-sharing service system (PBSSS). The DEMATEL (Decision Making Trial and Evaluation Laboratory) was used to solve the network relation structure between aspects. The ANP (analytic network process) was applied to evaluate the relationship between aspects and component weights. VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje) was used to analyze the public bike-sharing system’s service performance for different users regarding its strengths and weaknesses. After comparing the strengths and weaknesses of the various users’ preferences for the urban public bike service systems, the study proposes a service development strategy for different styles of users based on the NRM (network relation map). The results can aid PBSSS providers and urban managers, strengthen the PBSSSs’ competitiveness, and make the PBSSSs become the best urban short-trip connection transportation tool.

Addressing the gender gap in cycling: Lisbon's journey for a more inclusive cycling ecosystem

Despite significant investment towards the promotion of cycling in Lisbon, data collected reveal a substantial gender gap both in private bicycle use and in the public bike-sharing system, GIRA (around 70% are male users). To tackle this issue, the work (herein presented) consisted of an investigation to key factors underpinning the observed gender gap, knowledge that informed an action plan that aims to promote a more equal access to GIRA. Our journey included a thorough qualitative and quantitative user research process aiming at gathering gender-disaggregated data to better understand access barriers and unmet needs. We resorted to various methods such as an online survey, in-depth interviews and an immersive experience with GIRA. The exploratory phase was then followed by a set of co-creation sessions with bicycle users and non-bicycle users which was the basis of EMEL's action plan.

Study to Shift From Motorised to Non-Motorised Transport – A Case of Nashik City

With the aim to reduce the adverse environmental impact caused due to the urban transportation system, an alternative solution is identified. Non-motorized transport is the most relevant alternative for low-carbon mobility. It not only helps in the city's sustainable development but also helps reduce traffic problems and improve one’s health. In India and in foreign countries, the government is taking initiatives to promote Non Motorised Transport (NMT) and funding the project to come into operation. In most of the surveys, the solutions are given for improving NMT infrastructure, but from the literature, a gap is found that only improving the infrastructure is not important, instead at first it is important to recognize the actual need as to where we need to develop infrastructure, secondly recognizing the potential trips and then proposing infrastructure respectively. There is no study done on the potential trips that could be converted to NMT with reference to Nashik City. This research aims to study the mobility plan of the Gangapur road area of Nashik city and identify the potential trips of such area which can be shifted to non-motorised transport. The survey includes the study of daily trips taken by people for various activities, which caters to all age groups. The study also includes an understanding of the trip length, alignment of the roads, and important commercial and institutional zones in the area. A thought is also given for redesigning Public Bicycle Sharing System in the study area for the maximum usage of the system. A module is proposed after an analysis of the survey and the existing transportation plan. A plan representing the module and indicating the potential trips that can be converted to non-motorised transport is proposed.

The impact of public bike-sharing systems on mobility patterns: Generating or replacing trips?

Bike-sharing systems allow occasional and regular users to travel by replacing other transport modes for the same trip or generating a new journey. Our research assesses the demand for Lisbon’s public dock-based bike-sharing system (BSS), named GIRA. This paper aims to identify the determinant factors that influence the potential of the BSS to generate new trips or replace previous modes using a conditional logit model based on a survey of 3112 BSS users. The survey results indicate that GIRA generated approximately 20% of the BSS trips, i.e., they would not have been realized if GIRA did not exist. The remaining BSS trips replaced other motorized (55%) and non-motorized (25%) trips. The main determinants explaining a higher likelihood of replacing different modes are having a yearly GIRA pass and a bike-sharing station within a 5-min walk. In contrast, regular car users are more likely to generate new trips, suggesting they use bike-sharing for recreational purposes. The findings provide policymakers with an assessment of determinants which may influence bike-sharing users to generate or replace trips from other modes and, consequently, define policies to potentially increase bike-sharing.

A VNS-Based Matheuristic to Solve the Districting Problem in Bicycle-Sharing Systems

A matheuristic approach that combines a reduced variable neighbourhood search (rVNS) algorithm and a mathematical programming (MP) solver to solve a novel model for the districting problem in a public bicycle-sharing system is presented. The problem is modelled as an integer programming problem. While the rVNS algorithm aims to find a high-quality set of centres for the repositioning zones, the MP solver computes the optimal allocation network of the stations to the centres of the repositioning zones. We use a predefined grid to reduce the search space the rVNS needs to explore. The proposed approach obtains promising results for small and medium-sized instances, and is also able to handle large-sized models.

Impacts of the COVID-19 pandemic on the spatio-temporal characteristics of a bicycle-sharing system: A case study of Pun Pun, Bangkok, Thailand.

The COVID-19 pandemic is found to be one of the external stimuli that greatly affects mobility of people, leading to a shift of transportation modes towards private individual ones. To properly explain the change in people's transport behavior, especially in pre- and post- pandemic periods, a tensor-based framework is herein proposed and applied to Pun Pun-the only public bicycle-sharing system in Bangkok, Thailand-where multidimensional trip data of Pun Pun are decomposed into four different modes related to their spatial and temporal dimensions by a non-negative Tucker decomposition approach. According to our computational results, the first pandemic wave has a sizable influence not only on Pun Pun but also on other modes of transportation. Nonetheless, Pun Pun is relatively more resilient, as it recovers more quickly than other public transportation modes. In terms of trip patterns, we find that, prior to the pandemic, trips made during weekdays are dominated by business trips with two peak periods (morning and evening peaks), while those made during weekends are more related to leisure activities as they involve stations nearby a public park. However, after the first pandemic wave ends, the patterns of weekday trips have been drastically changed, as the number of business trips sharply drops, while that of educational trips connecting metro/subway stations with a major educational institute in the region significantly rises. These findings may be regarded as a reflection of the ever-changing transport behavior of people seeking a sustainable mode of private transport, with a more positive outlook on the use of bicycle-sharing system in Bangkok, Thailand.

Infrastructure evaluation, role of public bike sharing systems – Global and Indian context

Public bike-sharing systems have become a prominent feature across the globe. In less than a decade, bike-sharing systems increased from 347 in 2010 to 2006 in 2020. Despite the bike-sharing ongoing growth, more research is needed, especially in developing countries like India, where the available literature on bike-sharing is minimal. The paper’s main objective is to present a comparative evaluation of bike-sharing systems in Indian cities to other bike-sharing cities worldwide. Further, to examine the differences present between Indian cities and International cities and analyse the reasons for such differences. This study also tried to understand the relationship between various parameters affecting bike-sharing metrics such as bike-share performance, usage, and market penetration. A bivariate correlation and regression analysis revealed several significant predictions among the bike-sharing parameters. These results provide insights into the relative influence of bike-share parameters on bike-share metrics, which can be helpful to city planners and operators in effectively planning bike-share systems. Further, the study also examined the role of bike share as a mode of urban transport and how its relation with other transport systems is changing from city to city. The insights from this analysis also help the city administrators in India to define the role of bike-share based on its size and availability of transport system alternatives in the city.