Journal of Cycling and Micromobility Research最新文献

{"title":"Factors influencing the usage of shared micromobility: Implications from Berlin","authors":"Maximilian Heumann ,&nbsp;Tobias Kraschewski ,&nbsp;Philipp Otto ,&nbsp;Lukas Tilch ,&nbsp;Tim Brauner ,&nbsp;Michael H. Breitner","doi":"10.1016/j.jcmr.2025.100063","DOIUrl":"10.1016/j.jcmr.2025.100063","url":null,"abstract":"<div><div>The popularity of urban micromobility has steadily grown in cities worldwide. There is a lack of comparative studies investigating factors influencing the travel behavior of shared micromobility in Europe. From this, we investigate shared bicycle, e-scooter, and e-moped usage in Berlin based on trip data from September 2019 to March 2022. We incorporate a comprehensive set of spatial, temporal, weather-, fleet size-, and COVID-19-lockdown-related factors. To account for significant over-dispersion in our hourly resolved panel dataset for 542 traffic analysis zones, we employ a functional spatiotemporal regression model to estimate variables of trip counts for the three micromobility modes. Our descriptive results reveal spatiotemporal characteristics of shared bicycle, e-scooter, and e-moped usage and significant growth of operating fleet sizes in Berlin in recent years. We provide evidence that fleet expansion does not lead to a proportional increase in trips, implying competitive effects among operators limit potential growth. As urban space is scarce and regulations on fleet sizes are lacking, urban planners and service providers use these findings and complementary studies to plan fleets and their allocation optimally. Impacts associated with land use vary between modes and allow for demand-based planning. Precipitation is the most impactful factor among the weather variables and shows a pronounced adverse effect on all three modes. COVID-19-lockdown phases had no significant effect on e-mopeds. While bicycles were moderately affected, e-scooter trips decreased significantly. The findings can help policymakers and micromobility operators further optimize sharing mobility services and facilitate evidence-based strategies for the spatial and temporal design of micromobility.</div></div>","PeriodicalId":100771,"journal":{"name":"Journal of Cycling and Micromobility Research","volume":"4 ","pages":"Article 100063"},"PeriodicalIF":0.0,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personas-based e-scooter usage patterns analysis at a Greek research campus","authors":"Panagiota Mavrogenidou,&nbsp;Amalia Polydoropoulou","doi":"10.1016/j.jcmr.2025.100062","DOIUrl":"10.1016/j.jcmr.2025.100062","url":null,"abstract":"<div><div>Micro-mobility, particularly e-scooters, is characterized as a promising solution to urban transportation challenges by reducing congestion and pollution. However, integrating e-scooters into urban environments has been challenging due to safety concerns and friction with other transport modes, leading to public opposition and potential bans. These challenges underscore the benefits of deploying e-scooters in controlled environments like university campuses, where their impact can be better managed. This study examines e-scooter implementation on a Greek campus, focusing on identifying hidden factors influencing usage levels through exploratory factor analysis (EFA). In addition, cluster analyses reveal different personality types that significantly affect usage levels. The Real-life Experiment was conducted in two phases, compared behaviors over time, and accounted for weather variations. The study innovatively integrates questionnaire and usage data to identify hidden factors affecting usage and segment users into personas. The analysis created four perception-based personas (Reluctant, Cautious, Practical, Interested but Unconvinced) and four trip-based personas (Young and Infrequent, Young and Frequent, Older and Infrequent, Older and Frequent). Chi-square analysis and Sankey diagrams visualized personas’ patterns, while ridgeline plots showed variable distributions across the two phases. Results highlighted the significant impact of safety concerns, transport challenges, perceived e-scooter benefits, and weather on utilization levels. The insights from this study provide valuable guidance for effectively implementing e-scooter systems to enhance sustainability and reduce unnecessary car trips. Recognizing the challenges and opportunities associated with adopting e-scooter sharing systems allows research institutions to better plan and promote sustainable practices.</div></div>","PeriodicalId":100771,"journal":{"name":"Journal of Cycling and Micromobility Research","volume":"4 ","pages":"Article 100062"},"PeriodicalIF":0.0,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143629219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effectiveness of traffic signs to prevent fly parking","authors":"Alexandra Gavriilidou,&nbsp;Rolien Holster,&nbsp;Winnie Daamen","doi":"10.1016/j.jcmr.2025.100060","DOIUrl":"10.1016/j.jcmr.2025.100060","url":null,"abstract":"<div><div>As bicycle use increases, so does the need for formal parking spaces to safely store them while performing other activities at a destination. In the Netherlands, several municipalities have created indoor and outdoor formal parking spaces, which remain underutilised. Instead, many cyclists choose to ‘fly park’, i.e. informally lock their bicycle to objects on the street. This can cause dangerous situations or inconvenience, for example by blocking sidewalks. The discrepancy between the use of formal and informal parking spaces may be attributed to a lack of information provided to cyclists about the available formal parking options. This study investigated the effectiveness of different traffic sign designs in encouraging the use of formal parking spaces. The designs were developed within this research with the intention of capturing different communication strategies, namely hazardous, neutral educative and negative educative. A stated preference choice experiment was then performed to allow the comparison of the effectiveness of the different designs, and thus communication strategies. The responses were analysed using discrete choice modelling. According to the results, traffic signs alerting users to the fact that controls are performed (hazardous communication) are the most effective in the fly parking prevention, especially for frequent bicycle users.</div></div>","PeriodicalId":100771,"journal":{"name":"Journal of Cycling and Micromobility Research","volume":"4 ","pages":"Article 100060"},"PeriodicalIF":0.0,"publicationDate":"2025-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143682533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparing injuries from e-scooters, e-bikes, and bicycles in the United States","authors":"Hannah Younes","doi":"10.1016/j.jcmr.2025.100061","DOIUrl":"10.1016/j.jcmr.2025.100061","url":null,"abstract":"<div><div>There is a growing perception that e-scooters are more dangerous than bicycles and e-bikes, with towns implementing measures to ban their usage. Yet, there is not much evidence from large scale surveys to substantiate this claim. Nearly 14,000 micromobility injuries leading to emergency care in the United States in 2021 and 2022 are analyzed in this study. The following questions are addressed: What are the characteristics of injured micromobility users? Are injured e-scooter users more likely to suffer severe or fatal injuries than other injured micromobility users? What is the relationship between motor-vehicles and micromobility-related injuries? Around 15 % of injured micromobility users presenting to an emergency department were admitted to the hospital. Injured e-scooter users were not more likely to suffer severe injuries than bicyclists and e-bike users. Factors influencing micromobility injury severity included: older age, being male, involvement of a motor-vehicle, and alcohol/substance use. E-bike injuries were more likely to (33 %) involve a motor-vehicle than bicycle (26 %) and e-scooter injuries (23 %). Injured e-scooter users were more diverse (e.g., a higher proportion of women and minorities) and tended to be younger than bicyclists and e-bike users, indicating a potential wider diversity of users. As micromobility becomes a growing mode of sustainable transportation, we must ensure that conditions are safe for all users. This includes separated and protected pathways for micromobility users, traffic calming measures for motor-vehicles, adequate post-crash care for all, and policies that advocate for safe usage, instead of preventing usage, of micromobility modes.</div></div>","PeriodicalId":100771,"journal":{"name":"Journal of Cycling and Micromobility Research","volume":"4 ","pages":"Article 100061"},"PeriodicalIF":0.0,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143552455","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bike sharing systems: The impact of precise trip demand forecasting on operational efficiency in different city structures","authors":"Selin Ataç ,&nbsp;Nikola Obrenović ,&nbsp;Michel Bierlaire","doi":"10.1016/j.jcmr.2025.100058","DOIUrl":"10.1016/j.jcmr.2025.100058","url":null,"abstract":"<div><div>Increasing environmental concerns drive interest in sustainable solutions across various fields. Vehicle sharing systems such as one-way station-based bike sharing systems (BSSs) offer one such solution in transportation, although they pose operational challenges like vehicle imbalance. While many studies focus on optimizing rebalancing operations using trip demand forecasting, the added value of precise trip demand forecasting remains unexplored. This study assesses the added value of collecting detailed trip demand data and developing trip demand forecasting models. To achieve this, we create a simulation–optimization framework representing a city BSS in operation during the day. We use a discrete-event simulator representing the system dynamics and an enhanced mathematical model optimizing the rebalancing operations. We employ clustering in the optimization module to manage larger case studies, dividing the problem into smaller sub-problems. Our computational experiments compare two main scenarios, perfect demand forecast and unknown future demand, as well as several intermediate scenarios where partial future trip demand information is available. These scenarios allow us to determine the trade-off between lost trip demand and rebalancing operations costs, assess demand forecasting benefits, and identify the budget’s upper limit for precise trip demand forecasting. Subsequently, we conduct experiments on one synthetic (35 stations) and four real-life case studies, ranging from small systems (21 and 298 stations) to large systems (681 and 1361 stations). Results reveal that precise trip demand forecasting has varying impacts on small and large BSSs, with larger BSSs benefiting the most without significantly increasing the rebalancing operations costs. We also observe that the most significant improvements occur between 0% and 40% trip demand knowledge while beyond 60%, the increase in returns diminishes. The findings of this study offer valuable insights for operators in enhancing service levels and optimizing resource allocation.</div></div>","PeriodicalId":100771,"journal":{"name":"Journal of Cycling and Micromobility Research","volume":"3 ","pages":"Article 100058"},"PeriodicalIF":0.0,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429540","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"What determines the use of private and shared bicycles? Evidence from the University of Lyon (France)","authors":"Nathalie Havet,&nbsp;Louafi Bouzouina","doi":"10.1016/j.jcmr.2025.100059","DOIUrl":"10.1016/j.jcmr.2025.100059","url":null,"abstract":"<div><div>Many cities have introduced policies to promote cycling through personal and shared bicycles. However, there are limited studies simultaneously exploring the determinants affecting the types of cycling and their interactions within the urban mobility system. This article aims to analyze factors influencing the use of private and shared bicycles using data from a student survey conducted at 17 academic institutions in Lyon, using a copula-based binary choice model. Our results show that spatial factors, such as residential location, shared bike accessibility, and home-campus distance, strongly influence the active mode choice. They also provide novel evidence on the complementarity and substituability between cycling and other modes. For example, we find that while having a public transport season ticket significantly reduces the likelihood of commuting by bicycle, this substituability is more pronounced between public transport and shared bike use than between public transport and use of private bikes. However, for multomodal home-study trips, shared bikes are stronger complements to alternative modes (inclunding public transport) than private bikes. From a policy perspective, these results confirm the need for specific heterogeneous policies aimed at promoting cycling and sustainable mobility.</div></div>","PeriodicalId":100771,"journal":{"name":"Journal of Cycling and Micromobility Research","volume":"3 ","pages":"Article 100059"},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When do shared e-scooters complement or compete with public transport? A mixed-method review and comparison with bike sharing","authors":"Mahesha Jayawardhena,&nbsp;Alexa Delbosc,&nbsp;Graham Currie,&nbsp;Geoff Rose","doi":"10.1016/j.jcmr.2025.100057","DOIUrl":"10.1016/j.jcmr.2025.100057","url":null,"abstract":"<div><div>E-scooters are one of the latest additions to transport networks in many countries and their popularity is increasing rapidly. A range of studies have been conducted to understand the relationship between e-scooters and public transport. Some found that e-scooters complement public transport, serving as a first mile/last mile access mode, whereas others found that they compete by taking riders away from public transport. The contradictory results of studies in different contexts make it unclear whether results in one city are transferrable to another. This study aims to explore the definitions of ‘complement’ and ‘compete’ in literature and to identify the circumstances where e-scooters complement or compete with public transport using a mixed-method literature review. We combine a systematic literature review of e-scooter papers with a scoping review of bike-share studies to see if the two modes act in a similar manner. Most researchers found that e-scooters tend to complement rail but are more likely to compete with buses. Bike-share behaves in a similar manner, but the competing effect with buses is higher with bike-share than shared e-scooters. Both shared e-scooters and bike-share have a complementary relationship with public transport for commuting and longer trips. Moreover, shared e-scooters have the potential to promote public transport when deployed thoughtfully, but further investigation is needed given the novelty of the field. Further research should focus on a wider variety of cities (particularly outside of Europe and the USA), the reasons behind rider behavior and different ridership patterns and characteristics of personally owned e-scooters.</div></div>","PeriodicalId":100771,"journal":{"name":"Journal of Cycling and Micromobility Research","volume":"3 ","pages":"Article 100057"},"PeriodicalIF":0.0,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143097836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the Shared E-Scooter adoption behavior: A case study of Chicago, USA","authors":"Nazmul Arefin Khan ,&nbsp;Krishna Murthy Gurumurthy ,&nbsp;Amir Davatgari ,&nbsp;Abolfazl (Kouros) Mohammadian ,&nbsp;Joshua Auld","doi":"10.1016/j.jcmr.2024.100056","DOIUrl":"10.1016/j.jcmr.2024.100056","url":null,"abstract":"<div><div>In recent years, shared E-Scooters (SES) have emerged as one of the most popular and rapidly growing micromobility modes. To better understand the role of SES in urban mobility, it is critical for policymakers and planners to explore the adoption behavior and usage frequency of Shared E-Scooters. This study jointly estimates the Shared E-Scooters' potential adoption and frequency of usage using a zero-inflated ordered probit (ZIOP) model. This approach can be interpreted as whether an individual considers E-scooters as a travel mode alternative, and if so, how frequently they use E-scooters, which also has a zero occurrence. The study uses a dataset from the City of Chicago. The parameter estimation results suggest that various socio-demographics, built environment, accessibility measures and service characteristics have adequate impacts on E-Scooter adoption and usage frequency. This study also implements the model within the POLARIS agent-based transportation system simulator to examine the potential impact of various E-Scooter deployment scenarios. Results suggest that deploying more Shared E-Scooters in the traffic network not only increases the number of E-Scooter trips, but also helps to decrease the person-miles traveled and person-hour traveled. Insights from this study would be useful for planners and policymakers to develop alternative policy strategies associated with emerging mobility.</div></div>","PeriodicalId":100771,"journal":{"name":"Journal of Cycling and Micromobility Research","volume":"3 ","pages":"Article 100056"},"PeriodicalIF":0.0,"publicationDate":"2025-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143097834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Roadblocks to ride: Unraveling barriers to access shared micromobility systems in the United States","authors":"Farzana Mehzabin Tuli ,&nbsp;Suman Kumar Mitra","doi":"10.1016/j.jcmr.2024.100055","DOIUrl":"10.1016/j.jcmr.2024.100055","url":null,"abstract":"<div><div>Shared micromobility services are experiencing rapid expansion in the United States and Europe, yet certain user groups, particularly low-income and disadvantaged individuals, face significant barriers related to financial, technical, and cultural factors. This study provides a comprehensive analysis of these barriers within the US by examining bike-sharing, shared e-scooters and programs offering both services. Data was meticulously collected from diverse sources, including official bikeshare provider websites, municipal transportation sites, program reports, local news articles, and mobile applications. This comprehensive data collection methodology provides a thorough representation of 458 shared micromobility systems, encompassing all services available since the inception of shared micromobility in the US. To elucidate the specific barriers faced by users, we employed the K-Prototype clustering methodology, an unsupervised machine learning technique capable of handling datasets with both numerical and categorical features. This approach enabled us to uncover distinct patterns and groupings among shared micromobility services based on these barriers. Our analysis identified four distinct clusters: Cluster 1 faces low technical but high financial barriers; Cluster 2 excels in financial accessibility but struggles with technical barriers; Cluster 3 experiences moderate barriers with progress in reducing financial and technical challenges but still needs improvement; and Cluster 4 encounters high barriers across financial, technical, and cultural dimensions. Additionally, an in-depth analysis of these clusters is performed, considering the percentage share of bikesharing and shared e-scooter services, city sizes, regional distribution, fleet size, launching year, deployment, and operations status. The outcomes of this analysis reveal that larger cities exhibit a higher share of 'moderate barrier' (Cluster 3) systems that are currently active in the pilot phase. In contrast, shared micromobility systems from mid-size, small mid-size, and especially small cities in the US experience 'high barrier' (Cluster 4) issues the most, often with smaller fleet sizes (less than 250). Identifying these clusters is crucial for enabling targeted interventions. Rather than applying a broad, one-size-fits-all approach, policymakers and planners can develop tailored strategies that address the unique challenges of each cluster. This targeted approach ensures that interventions are more effective and equitable, ultimately improving access to shared micromobility services for all users.</div></div>","PeriodicalId":100771,"journal":{"name":"Journal of Cycling and Micromobility Research","volume":"3 ","pages":"Article 100055"},"PeriodicalIF":0.0,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143097829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empirical study of bicycle traffic characteristics relevant for microscopic simulation","authors":"Guillermo Pérez Castro ,&nbsp;Fredrik Johansson ,&nbsp;Johan Olstam","doi":"10.1016/j.jcmr.2024.100054","DOIUrl":"10.1016/j.jcmr.2024.100054","url":null,"abstract":"<div><div>Studies of bicycle traffic characteristics are essential for understanding bicyclist behavior and developing suitable microscopic models for traffic simulation. Based on empirical data on real-world bicycle traffic, obtained through video-based data collection techniques, we describe characteristics of free-riding, following, and overtaking that facilitate the simulation of bidirectional bicycle traffic. In total, we analyze data from 195 605 bicyclists across seven bicycle paths in Sweden, with five located in Stockholm and two in Gothenburg. The analysis reveals multimodal distributions of speed and lateral position due to the distinct preferences of bicyclists that vary according to the type of bicycle used. Moreover, speeds are generally highest during morning rush hours at the locations under investigation. Based on wind measurements, we conclude that there is no statistically significant effect on mean free speed from wind speeds in the range of <span><math><mo>±</mo></math></span>3 m/s. The distribution of speed differences between bicyclists at overtakings indicates a broad range of speed disparities among bicyclists, and is significantly influenced by infrastructure design. Furthermore, infrastructure design (path width, horizontal alignment, and presence of fixed objects along the edge) and traffic volumes significantly lateral positioning. Our results demonstrate the inherent heterogeneity in the characteristics of bicyclists, underscoring the need to advance modeling to incorporate these distinct characteristics into microscopic traffic simulation.</div></div>","PeriodicalId":100771,"journal":{"name":"Journal of Cycling and Micromobility Research","volume":"3 ","pages":"Article 100054"},"PeriodicalIF":0.0,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143097833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}