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• The analysis of total crash rates does not disclose the nature of crashes of cyclist from different age groups. • Effects of external variables on safety widely vary among different age groups. • Effects of external variables on safety is more complicated than what generalized linear models capture. • Nonlinear analysis can provide a profound understanding of nature of cyclist crashes. • Traditional approaches are still important for interpretability and practical purposes. In the Netherlands and all over the world, traffic safety problem has been growing particularly for cyclists over the last decades with more people shifting to cycling as a healthy and sustainable mode of transport. Literature shows that age is an important factor in crash involvement and consequences; however, few studies identify the risk factors for cyclists from across different age groups. Therefore, this study aims to identify and understand the effects of traffic, infrastructure, and land use factors on vehicle-to-bike injury and fatal crashes involving cyclists from different age groups. For this purpose, we adopted an approach consisting of resampling and machine learning (XGBoost-Tweedie) techniques to analyse police-reported crashes between the years 2015 and 2019 in the Netherlands. The analysis shows that effects of external variables on crashes widely vary among different age groups and the analysis of total crash rates may not disclose the nature of crashes of cyclist from different age groups. The analysis also shed light on the nonlinear effects of traffic and built environment factors on cyclist crashes, which are usually disregarded in the traffic safety literature. The proposed approach and findings provide a profound understanding of the nature of cyclist crashes and the complex relationships between factors, which can contribute to developing effective crash prevention strategies tailored to different age groups. [ABSTRACT FROM AUTHOR]

Increasing accessibility and improving cycling safety are the primary objectives of cities and policymakers. In the literature, there are several studies examining cycling safety and few studies examining cycling accessibility. However, few studies conduct a joint examination of these two topics to understand the relationship between them. This paper aims to develop and apply a methodological framework to conduct a joint zone-based analysis of traffic safety and accessibility. The developed framework integrates route choice modelling and four-step modelling into traffic safety and accessibility analysis and the outcome is a novel zone-based crash risk estimation incorporating traffic crashes with trip characteristics (including, trip purpose, origin-destination, and alternative routes). The proposed framework was applied in a case study to examine the injury crash risk imposed on commuting cyclists and job accessibility in the city of Utrecht, the Netherlands. The results illustrate the need to embed trip characteristics into zone-based traffic safety estimation to be able to compare the spatial distribution of traffic safety with other mobility and transport-related indicators. Moreover, the findings reflect on significance of taking route choice features into account in accessibility analysis to avoid overestimating accessibility levels. They show that safety and accessibility levels are not equally distributed in the city of Utrecht. For example, low-income areas generally have lower job accessibility levels and higher cycling crash risks which imply the spatial and social inequalities in the transport system's effects. [ABSTRACT FROM AUTHOR]

• Joint assessment of accessibility and safety revealed inequity issues more clearly. • Low-income people have disadvantages in terms of job accessibility and traffic safety. • Low-income zones have the highest crash risk and/or lowest job accessibility by bicycle. • City centers are the best zones regarding safety and accessibility. • People aged between 45 and 64 are exposed to higher cycling crash risks while having lower job accessibility. Problem: Transport policies generally prioritize improving safety and accessibility levels, as they are regarded as the most important indicators of the quality of the transport system serving the public. However, inequalities associated with safety and accessibility issues are generally overlooked in these policies. Despite the importance and necessity of transport policies to address equity issues, there is still scarce knowledge on the interactions between equity, safety, and accessibility. This research aims to address this gap in the literature by creating a better understanding of the relationships between accessibility levels and traffic safety with a focus on social equity perspectives. Method: A crash risk evaluation method and a Gravity model are utilized to analyze cycling safety and accessibility to jobs by bicycle. Two linear regression models (LM) were conducted to investigate the statistical correlations between cycling crash risk and accessibility. Moreover, the Bivariate local Moran's I method was employed to assess the spatial inequalities of distribution of crash risk and job accessibility over different income-level populations. Results: The analyses showed that low-income people are not only disadvantaged in terms of job accessibility by bicycle but are also exposed to higher cycling crash risks, compared to high-income groups. Furthermore, most disadvantaged zones that have the highest need for road safety and accessibility improvements are identified as areas where low-income populations are exposed to higher crash risk and/or have lower access to jobs by bicycle. Summary: This study contributes to the transport literature by investigating the interactions between safety and accessibility and the impacts on transport equity. The findings of the statistical and spatial analysis are beneficial for the decision-makers, considering the probable mutual implications of land-use and transport developments and projects aiming to improve safety, accessibility, or both for different population groups. [ABSTRACT FROM AUTHOR]

Electric bicycles (e-bikes) have been promoted in many countries to replace motorised transport modes and mitigate transport externalities such as traffic congestion and emissions. However, there are also concerns about crash risks and crash severity for e-bike users. Leveraging new technologies could help improve e-bike safety, amongst other safety enhancing measures, but there is little knowledge of the users' acceptance of such technologies. This study aims to explore the user acceptance of e-bikes (pedelec with power assistance up to 25 km/h or speed-pedelec with assistance up to 45 km/h) with active road safety assistance (in short: Smart e-bikes) to improve cycling safety by adopting the extended unified theory of acceptance and use of technology 2 (UTAUT2). A cross-country survey was administered in five European countries-Austria, Belgium, Germany, Greece, and the Netherlands, each differing in population, cycling culture and e-bike market sizes. A sample of 1,589 respondents, including e-bike owners and people interested in buying an e-bike, was analysed using a structural equation model (SEM). Conclusions indicate that performance expectancy, hedonic motivation and perceived safety were the strongest constructs of behavioural intention to use Smart e-bikes in the aggregated sample. All constructs vary significantly across the five countries, which can partly be explained by socio-demographic factors. Geographical factors such as city size, low availability of cycle paths and population density do not explain differences in user acceptance. [ABSTRACT FROM AUTHOR]