Sessions

• This study examined the association between fundamental user characteristics and self-reported cycling behaviors in Spain.
• 335 Spanish cyclists were involved in this research on cycling behavior and safety.
• A higher self-rated cycling performance was positively linked to the frequency of riding errors and traffic violations.
• There are significant relationships between Spanish riders’ characteristics, their cycling behaviors, and their crashes.
• This study highlights the role of mental health issues and risk perception on cyclists’ crash involvement.

• Geographical Location of Bikeability Studies
• Bikeability Measures
• Factors and Components for Measuring Bikeability
• Coefficient Ranking for Various Factors
• Safety: the most Important Factors?

• Demonstrating the effectiveness of exploratory learning in road safety by focusing on the process of bicycle behavior change.
• Naturalistic cycling data were collected to examine behavioral changes and its habituation through workshops.
• Analysis of actual behavior showed a 17% reduction in failure to stop behaviors at unsignalized intersections.
• With an increase in background factors such as motivation, commitment (p<0.05), and intention to change behavior (p<0.01).
• To spontaneously change safe behavior, “showing a distinction between undesirable and desirable behavior” was more effective.

The characteristics of dangerous conflicting patterns caused by multiple bicycles entering simultaneously at the corner of a signalized intersection with two-way bicycle traffic were clarified through an observational survey and video-tracking analysis using the Time to Collision index.

As a bicycle traffic pattern that is overlooked by drivers of left-turning vehicles, the number of cases is clearly higher for forward traffic than for oncoming traffic, and countermeasures against so-called left-hook collisions should be considered.

The most dangerous bicycle traffic pattern was when two bicycles enter different crossing points at the same time, especially in the case of short-cut bicycle through the nearside of the intersection corner.

• Consideration of route choice characteristics of cyclists in cycling safety analysis is crucial.
• The proposed zone-based crash risk metric integrating cyclists’ route choices in the cycling safety analysis is applicable in analysing impacts of built environment factors such as accessibility on cycling safety.
• The cyclists traveling to work from the city center areas in Utrecht are less at crash risk in comparison to to the Northeast and Northwest.

1. We developed a research bicycle equipped with a commercial digital lidar sensor with high spacial and temporal resolution (Ouster OS1-128 channel at up to 20 Hz).
2. The on-bicycle lidar records point cloud data of the riding environment (e.g., surrounding vehicles) that can be used for studying driver-cyclist interactions (e.g., drivers-overtaking-cyclists) with detailed distance and movement information.
3. More information and demonstrations of this project can be found at https://fenggroup.org/lidar-bike.

• Despite of the advantages of cycling for health and the environment, the use of the bicycle is still low due to safety risks.
• A new communication-oriented ADAS system is proposed to increase the safety of cyclists when interacting with vehicles.
• A bike simulator was designed to evaluate the safety impact of the ADAS system via cycling behaviour analysis.
• Subjective measurement is considered to ensure realistic cycling in VR compared to real cycling.

1. Hazard notifications informing bicyclists about potential hazards could be a measure to improve cyclist safety.
2. Such notifications should indicate the hazard type, its relative direction and the elapsed time (approach to hazard).
3. Participants rated cycling with hazard notifications significantly higher in terms of perceived safety than unassisted rides.
4. One major challenges to overcome is over-reliance on the notifications, which could lead to inattention to other hazards.
5. Notifications only indicate that a hazard may occur, not that it will, and could be misinterpreted as “false positives”.

• Travel behavior patterns are important to understand net safety effects of e-bikes
• This study describes a longitudinal machine-learning enabled travel behavior study using a smartphone app that runs passively
• Data collected can assess travel behavior shifts, including mode substitution and trip purpose
• Data collected also assesses rider behavior, including speed traveled and route choice
• Emerging data collection methods can provide insights into user-oriented travel behavior that can assess e-bike rider impacts on traffic safety.

1. The study aimed to provide a data-based and theory-driven road safety approach for e-scooter mobility.
2. An online survey (N = 99) and six online focus groups (N = 20) with frequent e-scooter riders were conducted.
3. Based on the results, an e-scooter road safety matrix for road safety campaigns was developed.
4. The matrix contains practical information regarding prevention aims, format requirements, and strategies.

1. More than one-third of Africans use active mobility as a daily mode. Walking is the primary mode of travel for 78% of Africans.
2. However, active mobility in most African cities is one of the riskiest modes of mobility mainly due to the poor infrastructure. 
3. The poster will present findings from a quantitative mobility survey conducted in three Sub-Saharan African countries.
4. The main aim of the project is to understand the perceptions, preferences, and daily experiences, of cyclists in African cities’ context.
5. Findings: lack of subjective safety, unfair space allocation, and poor law enforcement are among the obstacles to a safe cycling environment.  

• New geofencing based e-scooter parking regulation in Munich improved parking compliance, with positive effects for safety
• Survey among e-scooter users reveals that the regulation is perceived as effective for reducing e-scooter parking problems
• The survey also reveals that important aspects of e-scooter usage have worsened (e.g. flexibility, convenience)
• There is a low acceptance for extending the regulation to other city areas and the risk of trip replacement by car in future
• Improvements with GPS accuracy and parking zone visibility (physical and in provider apps) can potentially foster acceptance

1. Research project: “BRAVOUR” improves cyclist safety in construction areas, funded by the German Federal Ministry of Digital and Transport.
2. Uncovering factors influencing path choices of bicyclists.
3. Exploring potential conflicts in construction sites.
4. Comparing a traffic counting systems vs. camera for optimizing cyclist volume evaluation.
5. Contribute to enhancing public health by improving cyclist safety.

• Interviews investigating safety perception at a high-conflict area in Zurich (Switzerland)
• Comparison of four different cycling facilities
• Additional physical separation was not perceived as significantly better than only the coloured bike lane
• The bike lane equipped with speed bumps was associated with the highest safety feelings

1. No previous research analyzed bicycle riding-related distracting behaviors related to the use of new technologies in relation to city-size patterns. 
2. This study aimed to compare the prevalence of common technology-related distractions among cyclists riding in >300 cities of different sizes.
3. Cyclists from more extensive urban areas tend to report more cycling distractions of both technological and non-technological nature.
4. City size had a statistical effect on the usage of handheld devices, headphone-wearing, and non-technological generic distracting sources.
5. These outcomes highlight the need for further actions aimed at discouraging the use of technological distracting sources among cyclists.

• The mental workload of cyclists in an immersive virtual reality environment was studied.
• Participants used a bicycle simulator to ride across different road layouts.
• Mental workload assessment relied on a subjective scale, the performance to a secondary task and eye-tracking measures.
• Most participants performed differently on the different road layouts.
• The bicycle simulator is a promising tool for assessing road layouts.

1. There is still a long way to go to change the behaviours and attitudes of vehicle drivers.
2. This is especially for near misses that involve close passes, particularly on straight roads.
3. Close passes account for 44% of all near-miss events in this study.
4. Near-misses are not only a common occurrence for cyclists, but they are also preventable if other parties take different actions.
5. Under-reporting of near-miss events also poses a significant problem.

1. Single bicycle crashes (SBCs) account for the majority of serious cyclist injuries.
2. SBCs are an under-addressed, road safety issue, and work on collision/injury prevention has been limited.
3. Therefore, a dynamics-informed algorithm is proposed for tracking SBC-related bicycle/rider features from in-the-wild video footage.
4. This may be used for proactive site-specific safety assessments, and inform safer cycling infrastructure design.

1. Bicyclists are vulnerable due inadequate road design along major Non-Motorized Transport (NMT) corridors
2. Unsafe road infrastructure increases bicyclists’ exposure to crashes along major non-motorized transport NMT corridors
3. Bicyclists are exposed to speeding motorists on main road carriageway due to unsafe cycle paths or disjointed NMT routes
4. Major NMT corridors still lack dedicated cycling lanes exposing cyclists to higher traffic speeds and volumes by other motorists hindering cycling
5. Inadequate traffic control devices and poor lighting on road infrastructure increases risk of bicyclists crashes

• We implemented an online survey regarding road users’ attitudes about current and future mobility in Munich.
• Respondents were especially frustrated about the lack of cycling infrastructure and space for cyclists in Munich.
• Respondents wished for a greener, car-reduced and more active mobility with better public transport in the future.
• These wishes were significantly correlated with concerns about the climate crisis.
• Contrary to the literature, technological developments like autonomous driving were hardly mentioned in our sample.

1. Cycling in a group is replete with unwritten codes of safety critical behaviour.
2. Many cyclists choose to ride in groups due to a heightened sense of safety and security.
3. Group cycling safety behaviours may be conceptualised using a teamwork framework.
4. Shared Mental Models is the most important teamwork factor for group cyclist safety.

1. Cycling safety is not only about providing the safest infrastructure for the road; sometimes the safest option is an alternative route.
2. Ideally a cycling network has its own hierarchy which prioritises separation from high-speed and high-mass vehicles.
3. Seven indicators of cycling route safety have been identified relating to minimising exposure and conflicts with motorised traffic.
4. Cycling routes can be evaluated based on the indicators and compared with route alternatives.
5. Insight into route safety can be used to make safe routes more attractive, improve the safety of popular routes, or design new safe routes.

• In Australia, Between 1991 and 2022, cycling deaths following multivehicle crashes decreased at a rate of 1.9% per annum while annual cyclist deaths from single vehicle crashes increased by 3.7%.
• The increase in the number of single vehicle cyclist crashes coincides with an increase in the building of cycling infrastructure in Australia. 
• This infrastructure is not always built according to the best international standards and not always properly maintained.

• We investigate the Safety-in-Numbers (SiN) effect on a street-based level in two mid-sized German cities
• Crash statistics are qualified by cycling volume, car traffic volume, and infrastructure characteristics
• We look into a possible “subjective” SiN effect through crowdsourced reports about subjectively dangerous locations

1. Frailty and Aging are a major contributor to the increase in US cycling fatalities
2. Several confounding factors are also relevant, alcohol, helmet use, location of crash
3. Errors in cyclist judgement are likely a function of age, especially in crossing crashes
4. Education programs from trusted sources are a potential help. HHS/ACL on the federal level, AARP a nonprofit, and local parks and rec.

1. Impact of smart cycling technologies on cycling experience is increasing and should be evaluated, and evaluations preferably include data from body sensors.
2. Studies that use data from body sensors are limited in number and scope.
3. The conceptual framework in this study guides choices on factors and methods about the use of body sensor data in future evaluations of experiences with SCTs.
4. Knowledge gaps remain about reliability of sensor data, moving towards sensor networks, diversity of experiences, and causal analysis.  

1. There is a lack of established procedures to extract safety-relevant indicators from standard on-field surveys
2. Trajectories of cyclists and motorized vehicles were obtained from video recordings using computer vision
3. Interactions between cyclists and vehicles were identified and assigned to scenarios (longitudinal or lateral interaction)
4. Relevant parameters for each scenario are presented and calculated using trajectories

• Poor visibility of cyclists to other vehicles remains a key contributor to vehicle-cycle crashes.
• An online survey explored concerns, attitudes, and behaviours regarding visibility during the day and at night for 689 cyclists.
• Cyclists expressed high concerns about their visibility, and its importance for their safety when cycling.
• Cyclists’ perceptions and behaviours regarding effective ways to increase their visibility at night-time does not always reflect evidence-based conspicuity strategies.
• Increased education around clothing choices to improve conspicuity and safety is needed, particularly placement of reflective materials.