On the use of naturalistic methods to examine safety-relevant behaviours amongst children and evaluate a cycling education program

A data-driven framework for the safe integration of micro-mobility into the transport system: Comparing bicycles and e-scooters in field trials

INTRODUCTION

Recent advances in technology create new opportunities for micro-mobility solutions even as they pose new challenges to transport safety. For instance, in the last few years, e-scooters have become increasingly popular in several cities worldwide; however, in many cases, the municipalities were simply unprepared for the new competition for urban space between traditional road users and e-scooters, so that bans became a necessary, albeit drastic, solution. In many countries, traditional vehicles (such as bicycles) may not be intrinsically safer than e-scooters but are considered less of a safety threat, possibly because-for cyclists-social norms, traffic regulations, and access to infrastructure are established, reducing the number of negative stakeholders. Understanding e-scooter kinematics and e-scooterist behavior may help resolve conflicts among road users, by favoring a data-driven integration of these new e-vehicles into the transport system. In fact, regulations and solutions supported by data are more likely to be acceptable and effective for all stakeholders. As new personal-mobility solutions enter the market, e-scooters may just be the beginning of a micro-mobility revolution.

METHOD

This paper introduces a framework (including planning, execution, analysis, and modeling) for a data-driven evaluation of micro-mobility vehicles. The framework leverages our experience assessing bicycle dynamics in real traffic to make objective and subjective comparisons across different micro-mobility solutions. In this paper, we use the framework to compare bicycles and e-scooters in field tests.

RESULTS

The preliminary results show that e-scooters may be more maneuverable and comfortable than bicycles, although the former require longer braking distances.

PRACTICAL APPLICATIONS

Data collected from e-scooters may, in the short term, facilitate policy making, geo-fencing solutions, and education; in the long run, the same data will promote the integration of e-scooters into a cooperative transport system in which connected automated vehicles share the urban space with micro-mobility vehicles. Finally, the framework and the models presented in this paper may serve as a reference for the future assessment of new micro-mobility vehicles and their users' behavior (although advances in technology and novel micro-mobility solutions will inevitably require some adjustments).

Global lessons learned from naturalistic driving studies to advance traffic safety and operation research: A systematic review

The state of practice of investigating traffic safety and operation is primarily based on traditional data sources, such as spot sensors, loop detectors, and historical crash data. Recently, researchers have utilized transportation data from instrumented vehicles, driving simulators, and microsimulation modeling. However, these data sources might not represent the actual driving environment at a trajectory level and might introduce bias due to their experimental control. The shortcomings of these data sources can be overcome via Naturalistic Driving Studies (NDSs) considering the fact that NDS provides detailed real-time driving data that would help investigate the safety and operational impacts of human behavior along with other factors related to weather, traffic, and roadway geometry in a naturalistic setting. With the enormous potential of the NDS data, this study leveraged the Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA) approach to shortlist the most relevant naturalistic studies out of 2304 initial studies around the world with a focus on traffic safety and operation over the past fifteen years (2005-2020). A total of 117 studies were systematically reviewed, which were grouped into seven relevant topics, including driver behavior and performance, crash/near-crash causation, driver distraction, pedestrian/bicycle safety, intersection/traffic signal related studies, detection and prediction using NDSs data, based on their frequency of appearance in the keywords of these studies. The proper deployment of Connected and Autonomous Vehicles (CAV) require an appropriate level of human behavior integration, especially at the intimal stages where both CAV and human-driven vehicles will interact and share the same roadways in a mixed traffic environment. In order to integrate the heterogeneous nature of human behavior through behavior cloning approach, real-time trajectory-level NDS data is essential. The insights from this study revealed that NDSs could be effectively leveraged to perfect the behavior cloning to facilitate rapid and safe implementation of CAV.

Inventory of child bicycle education programs reveals need for age, development, and skill-level considerations

Objective: There are a plethora of child bicycle safety education programs worldwide. However, the content and durations vary widely from program to program and no gold standard has been established. The main objective of this project was to create an inventory of youth bicycle safety education programs and their content, approaches, and age and developmental considerations.Methods: Methods used to gather program information included web and online database searches, extraction from personal lists, and a widely distributed online survey. A total of 89 programs met inclusion criteria and were reviewed (78 from the United States and 11 from other countries).Results: Over half (56.2%) of the included programs were not explicitly age specific, meaning that the content was not appropriately designated by age and developmental cut points. Many programs had target age groups, but these were often very wide age ranges (e.g., all elementary school-age children) resulting in content too advanced for the youngest children. Only 12.4% of included programs had published program evaluations and their scientific rigor varied widely. Main results from this inventory revealed a weak evidence base for program effectiveness due to lack of program evaluations. Results also highlighted a need for age, development, and skill-level considerations in youth bicycle education programs.Conclusions: This study provides a comprehensive list of program components and approaches that can be used as a foundation upon which child bicycle education standards can be evaluated and built, with the long-term goal of increased childhood safety.

An evaluation of the effects of an innovative school-based cycling education program on safety and participation

Cycling education programs for children could play a role in promoting both cycling participation and cycling safety, and they exist in many countries - often in school settings. Evaluations have generally shown improvements in skills and knowledge, but effects on less-researched outcomes such as safety-related behaviour, crashes or injuries, cycling participation, and cycling confidence, are unclear. The present research evaluated Safe Cycle, an innovative Australian school-based program that addresses hazard awareness and overconfidence in addition to more typical content (e.g. handling skills), in terms of a comprehensive range of outcomes. Students from Years 4 to 8 (n = 108) completed online surveys in class before, immediately after, and approximately 14 weeks after, the 8-week program was delivered. Significant increases in knowledge and confidence were observed, while results also suggested increases in cycling participation. The program appeared to address illusory invulnerability effectively, but there was no evidence that the program improved safety-relevant cycling behaviours or experience of crashes. The benefits of Safe Cycle might be enhanced by including elements to increase motivation to perform safety-relevant behaviours and durability of program effects.

Revealed Preference Methods for Studying Bicycle Route Choice-A Systematic Review

One fundamental aspect of promoting utilitarian bicycle use involves making modifications to the built environment to improve the safety, efficiency and enjoyability of cycling. Revealed preference data on bicycle route choice can assist greatly in understanding the actual behaviour of a highly heterogeneous group of users, which in turn assists the prioritisation of infrastructure or other built environment initiatives. This systematic review seeks to compare the relative strengths and weaknesses of the empirical approaches for evaluating whole journey route choices of bicyclists. Two electronic databases were systematically searched for a selection of keywords pertaining to bicycle and route choice. In total seven families of methods are identified: GPS devices, smartphone applications, crowdsourcing, participant-recalled routes, accompanied journeys, egocentric cameras and virtual reality. The study illustrates a trade-off in the quality of data obtainable and the average number of participants. Future additional methods could include dockless bikeshare, multiple camera solutions using computer vision and immersive bicycle simulator environments.