Although cycling offers numerous advantages, existing research identifies significant barriers to its uptake. These include feeling unsafe in traffic. While cyclist-centered infrastructure may address objective safety deficits, its impact on perceived insecurity remains uncertain. To address this gap and as an approach to map the safety continuum, we conducted a national field study in Germany that combined on-site observations and interviews to determine the number of so far undocumented safety-critical events (SCEs), which are precursors to crashes and indicators of infrastructure quality. Specifically, we investigated SCEs and their characteristics (involved interaction partners, causes, evasive actions) in relation to infrastructure type and assessment method (observation, interview). Over 12 weeks, we observed 34,676 cyclists in three medium-sized German cities, and surveyed 978. The results clearly show that SCEs occur frequently. From the perspective of cyclists, 10 to 28 times more SCEs are reported than observed, depending on the infrastructure. These results have several implications: SCEs should be considered when designing infrastructure, as they can reduce subjective perceptions of safety and potentially lead to less sustainable mobility. Infrastructure should be designed so that all road users are not only objectively safe but also subjectively, i.e., fear-free, when travelling. The findings underscore the importance of incorporating both cyclists' perspectives and SCEs into infrastructure planning, as cyclists perceive risk differently and often avoid crashes through defensive riding, so SCEs are not recorded in official crash statistics.
Artificial test environments are indispensable for modeling human behavior in traffic because they provide more control of experimental factors and fewer ethical concerns than a real traffic environment. These advantages are particularly critical for research on interactions involving vulnerable road users such as cyclists and drivers of motorized vehicles. However, previous research comparing test environments has predominantly focused on car-to-car interaction scenarios. This study investigated a cyclist-overtaking scenario in three different environments: a driving simulator (N = 25), a test track (N = 18), and a hybrid “driver-vehicle-in-the-loop” environment (N = 33) in which the participants drove a real vehicle on a test track while wearing a virtual-reality headset. Results indicated that the main factors influencing overtaking strategies and performance were consistent across all environments. Drivers tended to favor a cautious approach—waiting behind the cyclist—when facing a close oncoming vehicle, with this tendency being most pronounced in the driving simulator. Safety margins to the cyclist followed a similar trend in all environments; however, the test-track environment had the smallest margins, suggesting that virtual visual cues induce safer behavior. Because overtaking maneuvers depend on depth estimation, the visual resolution of the virtual environment may be more important than the environment itself in explaining the results.
In this study, the temporal dynamics of mental workload and its association with task-induced fatigue were investigated, along with the role of factors such as traffic interaction complexity, curve density, driver characteristics, and prior-day rest quality on mental workload and changes in task-induced fatigue. A field-based experiment was conducted with 30 truck drivers in Kerala, India, and data from 28 drivers were included in the analysis. This study introduces a novel methodology capturing driving difficulty at 10-min intervals via audio prompts without disrupting natural driving behavior, while simultaneously collecting real-time traffic interaction, physiological, and performance measures. Structural equation modeling was used to evaluate temporal associations and relationships among the key variables. The findings indicate that exposure to elevated mental workload shows a carryover pattern over time and is associated with delayed fatigue responses, whereas task-induced fatigue shows strong temporal persistence, reflecting its progressive nature. Traffic interaction complexity was significantly associated with higher mental workload, which in turn mediated the association between traffic interaction complexity and changes in fatigue. In addition to traffic-related factors, driver characteristics such as sleep duration, sleep quality, driving distance, age, and driving experience were significantly associated with variations in mental workload. Curve density was also found to be directly associated with the changes in task-induced fatigue. Overall, the findings emphasize the importance of accounting for traffic interaction complexity, rest quality, and driver characteristics when evaluating mental workload and fatigue under real-world driving conditions. The results also highlight the importance of adequate rest, considering the cumulative nature of fatigue. These insights may provide preliminary guidance for improving truck driver safety and future research on the planning and placement of rest facilities.
Tailgating remains a common risky driving behaviour and a major contributor to rear-end crashes. Rear-end crashes constitute the most common crash type associated with compulsory third-party claims in Queensland, Australia. Despite its prevalence and contribution to crashes, few interventions exist that seek to educate drivers about what unsafe and safe following distances are. Even fewer interventions still, exist that have been implemented on-road, and which offer real-time messaging to drivers based on their own vehicle headways. This study evaluated an innovative roadside technology that was trialled by the Department of Transport and Main Roads (TMR) to detect following distances and delivers targeted behavioural feedback through a variable message sign (VMS) to nudge behavioural change through increasing understanding of what safe following distances constitute. A quasi-experimental pre–post field trial was conducted at three sites in Southeast Queensland: two were more metropolitan-based and the other a more regionally located site. In this trial, two cameras measured vehicle headways before and after drivers were exposed to a roadside message. During the intervention phase, drivers travelling with unsafe headways received a warning message, while those maintaining safer headways received a positive message. The trial evaluation assessed the capability of the system in detecting tailgating and delivering targeted messaging, as well as evaluating drivers' following distances and speeds during the messaging period compared to the baseline phase. Across the trial, the system detected more than 2.54 million vehicles and successfully matched approximately 1.69 million vehicles between cameras. The findings showed consistent patterns of positive changes in behaviour as evidenced by significant reductions in tailgating behaviour and increases in the proportion of drivers increasing their headway in the intervention phase relative to the baseline phase. The analysis of speeds indicated that BAM significantly influenced drivers' travel speeds, though the magnitude and direction of changes varied by sites and following distance categories. These findings demonstrate the capability of BAM to accurately detect tailgating behaviour and provide real-time behavioural feedback that reduces unsafe following distances and reinforces safe driving behaviour.
Climate change requires rapid adoption of green street designs that encourage sustainable mobility, such as walking and cycling, while also helping to mitigate urban heat. In aging societies, these transformations must address the needs of older people. Focusing on Lisbon, Portugal, as a case study, this study explores how street configurations affect older pedestrians' walking behaviors, focusing on environmental features and behavioral dynamics. Using a mixed-methods approach, we conducted structured observations of 911 older pedestrians and 1340 cyclists in flow observations, and 174 older pedestrians in behavioral mapping, complemented by semi-structured interviews, across four streets with contrasting layouts (e.g., sidewalks and cycle lanes on the same level vs. separated, presence vs. absence of trees). Observations spanned four weeks in summer and fall, covering weekdays, weekends, and different times of day. Findings reveal that street design configurations are associated with cautious and risk-related walking behaviors. The study offers empirical insights into sustainable street design, supporting evidence-based policies to enhance older pedestrians' mobility.
