Journal of Cycling and Micromobility Research最新文献

Safety concerns expressed by micro-mobility users seem to practically constrain the use and flexibility of these new modes. This paper introduces a new, parametric agent-based modeling approach for simulating micro-mobility, using MATSim as a platform. Perceived safety is introduced as a factor, which affects travel behavior of micro-mobility modes in a car-dominated, heterogeneous, and perceived unsafe road network. To meet the research objectives, different scenarios are simulated, using the city of Athens, Greece as a test bed, to examine the model performance and applicability. A universal scoring function based on travel time, cost, and safety, is proposed. This study also discusses the concept of unsafe discontinuities. Simulation results show that an unsafe road segment of 500 m long is sufficient to induce evident behavioral variations and hinder the practical use of e-bikes and e-scooters in the base scenario. The establishment of a cycle-friendly road network leads to significant changes in the chosen routes and decreases the average trip distance for micro-mobility users. In this case, the simulation process is guided by perceived safety, primarily focusing on formulating safer paths for micro-mobility mode users. Nevertheless, the routing behavior of car users is not modified due to the spatial uniformity of safety perceptions in a car-dominated road environment.

Autonomous Vehicles (AVs) present a jarring new normal for negotiation on public streets. Current communication and interaction stand to be disrupted with the presence of AVs. Active transport users, specifically bicycle users, rely on human communication and subtle cues to feel confident when negotiating with other road users. Shifts in communicability with AVs presents a unique challenge for bicycle users. It remains unclear how AVs will impact urban bicycle users. This paper employs a mixed-methods approach to understanding impacts that AVs have on urban bicycle users in four test sites with varying levels of traffic stress. Interviews and focus groups were used across different traffic stress scenarios in three countries to understand how bicycle users will be impacted by AVs in real-world scenarios. The results represent a pioneering cross-section of four bicycle cultures’ exposure to AVs. Results universally show that, compared to conventionally operated vehicles, an enduring sense of unease remains unresolved with AVs and that shifting focus to bicycle user experiences and prioritizing the needs of a diverse population of non-occupants will be critical. If AVs are not deployed responsibly and responsively, they could turn bicycle users away from cycling in a streetscape where active transport users are already marginalized.

Providing adequate infrastructure for cycling is crucial for increasing its modal share and for supporting the shift towards sustainable mobility. To foster well-targeted, efficient, and effective improvements of infrastructure in favor of cycling, we need data and methods for assessing its current state in an automated, scalable, and reproducible way. Present models are limited due to dependency on proprietary and/or scarce data, being closed-source and not taking into account the many nuances of bikeability on segment scale. Therefore, we propose an open, adjustable, and extendible model of bikeability that relies on open and globally available data sets. It allows to consider aspects of safety, comfort, and the immediate environment. Results from an evaluation study show its applicability while underlining the importance of considering diversity in regional, individual, and purpose-related mobility demands. Future bikeability research may be informed by results of the online survey conducted as part of the evaluation study. The proposed bikeability model can form the foundation for advanced network and accessibility analysis and serves as an important information layer for decision making.

Recent studies have demonstrated the importance of a well-maintained and safe bicycle network to increase winter cycling. However, inequities in the access to cycling infrastructure in winter have not been documented yet. Based on the concept of equity in transport, this research aims to fill the gap and assess whether inequities are exacerbated during winter in the city of Montréal, Canada. The distance to the nearest cycling network section and kilometres of cycling network with 2.5 km and 5 km were computed in GIS. Two types of statistical analysis were then conducted to assess potential inequities for four population groups: weighted t-tests and seemingly unrelated regression (SUR) models. Our results demonstrate that the winter cycling network is more concentrated in central neighbourhoods and that accessibility issues are increasing in winter. Visible minorities face the most lack of accessibility, compared to the rest of the population. People under the age of 15 and over the age of 65 years old are also in unequal situations, while the low-income population has better access to winter cycling infrastructure than other groups. Our results innovate by incorporating measures of accessibility to the winter cycling network into the assessment of transport inequities.

Purpose

The aim of this study was to describe how electric-assist (e-assist) handcycles facilitate participation in adapted mountain biking for people with a spinal cord injury.

Materials and Methods

Ten adults (n=10) living with a spinal cord injury who actively ride trails each completed an online semi-structured interview. Seven of these participants have ridden nature trails using an e-assist handcycle. Following descriptive phenomenology principles, interviews were thematically analyzed using NVivo software.

Results

Commentary on e-assist was categorized into the following themes: e-assist descriptions, e-assist as enjoyable, and e-assist accessibility. Handcycles with pedal e-assist were described as a prominent facilitator, whereby the electric motor can mitigate overexertion, help navigate uneven terrain, and reduce injuries. Participants described using e-assist mountain biking handcycles as a way to facilitate perceived safety, inclusivity, and overall accessibility in adapted mountain biking participation.

Conclusions

Findings of this research emphasize the importance of innovative technology in facilitating adapted mountain biking for people with spinal cord injuries. E-assist mountain biking handcycles make the outdoors more accessible to people with a spinal cord injury by increasing opportunities to enjoy exploring nature and travel further, with enhanced safety features, which are not replicable while using a traditional handcycle or wheelchair.

While shared micromobility has been gaining popularity in developed countries, these innovative technologies have yet to penetrate the market of mid-sized cities in developing countries, which make up the overwhelming majority of cities in the world. Shared micromobility includes inexpensive systems that could drive the first wave of electrification in the transportation sector in these regions. We designed and implemented a dynamic stated preference pivoting survey and used a panel data mixed logit model to assess the effect of temperature, precipitation, and availability of bike lanes on the propensity to use bikeshare, e-bike share, and e-moped share, controlling for sociodemographic factors. Using Kathmandu, Nepal, as a case study, where shared micromobility does not currently exist, we also assessed modal shifts from the existing travel modes. We found heavy rain negatively impacts users’ preference for shared micromobility, while users preferred e-moped share during cold temperatures. The effect of bike lane availability was positive but weak on bikeshare and e-bike share. Gender also had an effect on the choice of shared micromobility vehicles – females preferred e-mopeds over other vehicles. Ride-hailing users had a high preference for e-moped share, while introducing bikeshare and e-bike share caused a uniform modal shift among existing travel modes. We recommend that transportation agencies begin micromobility pilot programs by combining this study’s findings with the best practices of existing micromobility programs. We also suggest collecting usage and operations data to empower data-driven decision-making.

Our understanding of non-linear and time varying effects on shared e-scooter ridership dynamics is limited. Consequently, both operators and city councils supporting shared e-scooter schemes do not have the requisite information to help optimise infrastructure planning and operation management. Focussing on subtropical Brisbane, Australia, the current study examines time varying and non-linear effects of weather and built environment factors on shared e-scooter ridership. Results from XGBoost models reveal threshold relationships with both the availability of cycling infrastructure and the presence of park and commercial land uses. Additionally, we show how hot weather increases ridership especially around large parks and in commercial areas on both weekdays and weekends. Understanding the intricate (non-linear) interplay (interaction) between weather and built environment factors and their variation over time on shared e-scooter ridership have important implications for policymakers, transportation planners, and environmental advocates in providing the requisite evidence for data driven decision making.

Many cities are currently planning and building new large-scale active transport networks to achieve a wide array of environmental, economic, and social equity goals. This is often combined with developing public campaigns to increase public awareness of their plans and introduced infrastructure to build a culture that celebrates and supports using them. While several studies explored the impacts of active transport infrastructure on users perception and travel behaviour, very little has been done to explore the factors associated with people’s awareness of such infrastructure at an early stage of their introduction. Accordingly, this study examines the factors affecting people’s likelihood of being aware of a new flagship cycling network in Montréal known as Réseau Express Vélo (REV), while understanding equity of awareness across gender identities. To achieve this goal, the study uses summary statistics and weighted multilevel logistic regressions to analyze data collected from a large-scale survey. The results of the paper show that various socioeconomic factors including age, ethnicity, income, language, as well as individuals’ travel behaviour and lifestyle are associated with being familiar with such a large bike network. Significant differences between women and men can also be observed, in which women are less likely to be aware of REV. Younger women in their 20 s tend to know much less about the project in comparison with men in the same age group. Women who identify as non-white only and used English to complete the survey are the group with the lowest probability of being aware of the project. Findings from this research unmask key aspects related to the likelihood of being aware of a new large-scale cycling network, offering important insights to transport planners, policy makers, and researchers.

Active travel to school is an important contributor to the physical activity levels of children and adolescents and the source of many health benefits. In this work, we model cycling to school in Finland. The probability to cycle on a given trip is modelled using a binary logistic regression model based on trip length, average route gradient, the cyclist’s gender, and age. Variables denoting the city regions were also included to account for differences in cycling cultures and infrastructure. In addition, weather variables were added as cycling levels in Finland are highly dependent on the season. Air temperature and the presence of snow were found to reflect well the observed seasonal variations. The observed influence of winter conditions on trip distances and the cycling of girls is also replicated in the model through interaction terms. This model is employed to explore two sustainable mobility scenarios: a scenario where the cycling of girls increases to the same level as that of boys and a scenario where all school children cycle as much as those living in Oulu, Finland’s top cycling region. Our results suggest that it would be possible to increase the number of trips by bicycle and cycled mileage significantly, up to 76 % in the Oulu scenario, even though school children already cycle much more than the general population.

In recent years, efforts to promote safer active school travel (AST), i.e., walking and cycling behaviors in girls, have heightened in light of huge gender disparities in micromobility adoption. In developing countries where transport infrastructure is not advanced, and AST adoption is influenced by societal perceptions, theorizing empirical studies will help better explore and understand the travel needs of girls for effective planning. This study investigated the factors influencing AST behaviors of 232 adolescent girls in primary, junior, and senior high schools based in Sunyani Municipality, Ghana. A novel combination of the Health Belief Model and the Theory of Planned Behavior was employed to formulate a conceptual model that was evaluated using SEM-MIMIC modeling. Results revealed that age plays a significant role in AST preferences, with younger girls favoring walking and older girls showing interest in cycling. Interventions can capitalize on this to promote cycling habits during the transition to senior high school. Moreover, environmental attitudes have the most decisive influence on the perceived social benefits of AST, while perceived parental support positively impacts safety self-efficacy. Together with perceived parental support, safety self-efficacy, and distance/accessibility barriers, they significantly influence girls' intentions to use active transportation. Authorities can adopt proposed targeted interventions such as the walking school bus and bicycle train concepts to make AST more attractive to girls.