Transportation Research Part F-Traffic Psychology and Behaviour最新文献

Due to the vision obstruction caused by visually blind obstacles on urban roads, pedestrians suffer a high crash risk in pedestrian-vehicle conflicts. At the same time, the connected information can potentially improve driver behaviour with an earlier warning and driving aids. To ensure safer interactions between pedestrians and motor vehicles in the middle section of urban roads, this simulator-based study aims to investigate drivers’ behaviour under the influence of connected information and predict crash risk during their interaction with pedestrians on urban roads, involving six conflict scenarios based on real-world traffic situations. The test employed a mixed experimental design, with connected information as the between-subject variable. A total of 70 participants were divided into a control group and an experimental group to complete the test. Results from linear mixed-effects models indicated that the presence of connected information and crosswalks positively influenced driver braking behaviour, resulting in a shorter reaction time, longer braking duration and distance, smaller maximum deceleration, and a reduced standard deviation of deceleration. Conversely, visual obstacles led to longer reaction times, while parked cars and buses negatively affected driver behaviour. Further, aggressive drivers exhibited poorer braking behaviour compared to neutral drivers. An explainable machine learning model was developed to predict pedestrian-vehicle crash risks during interactions, demonstrating satisfactory predictive accuracy. The presence of connected information and crosswalks was found to have a positive effect on reducing crash risks and improving safety margins. These findings provide valuable insights for implementing connected driving technology and developing measures to enhance pedestrian safety.

Driverless or autonomous vehicles (AVs) have the potential to address children’s mobility disadvantage by enabling them to become more independent from their parents and other adult drivers before they reach the legal age for obtaining a driver’s license. In an online contextual interview study, we interviewed N=22 parents of underage children from Germany to investigate their willingness to use AVs for unaccompanied transportation of their children. The goal of the interview study was to investigate whether AVs are a suitable option to support unaccompanied transportation of children from the parents’ perspective and how these AVs should be designed considering the parents’ concerns and needs. In contrast to former acceptance studies, we familiarized the participants with an existing AV concept called autoELF. We created a user scenario to enable the parents to better imagine the situation. In the study, parents first described their children’s current mobility in a normal week. Parents were then asked about the expected benefits, concerns, child-related prerequisites and technical requirements for using AVs, as well as the possibilities for integrating AVs into their family’s mobility. Results showed that AVs can be a solution to provide children with unaccompanied transportation. In contrast to previous studies, the majority of parents interviewed in this study were willing to use the AV for the transportation of unaccompanied children, but only after parents had gained initial experience with the vehicle and trained their children in its use. Regarding the unaccompanied use by their children, parents based their consent to use the AV on their children’s emotional and cognitive abilities rather than on their age. In their children’s daily mobility, parents intended to replace most of the previously accompanied car journeys during leisure time with the autoELF vehicle without compromising their children’s active mobility, such as walking or bicycling. In contrast to previous literature, only a few parents cited school commuting as a use case for the autoELF vehicle. Our qualitative interview study highlights the potential of AVs for unaccompanied child transportation. Moreover, it stresses the importance to use specific, tangible concept when investigating family AVs. In the next phase of the research project, a physical prototype of the autoELF vehicle was tested with children and older adults as the primary user groups.

The integration of autonomous driving into mixed traffic environments poses unique challenges, especially at unsignalized intersections where communication and cooperation with human road users is necessary. This study addresses a critical research gap by investigating the adherence to the “priority-to-the-right” rule at an urban unsignalized intersection, comparing behavioral patterns of cyclists and motorists. Utilizing stationary mounted cameras, a 12-day traffic observation of an urban T-intersection in Braunschweig, Germany, was conducted. The class and the trajectory of road users as well as their scenarios were identified. In 202 cases, cars appearing from the right (ego, with priority) encountered cars or bikes coming from the left (foe, without priority). The study analyzed the impact of variables, ego’s direction, foe’s class and lateral position and their arrival time on their passing order through descriptive statistics and logistic regression. The findings reveal that cyclists disregard the “priority-to-the-right” rule more often than motorists. Additionally, road users who have the priority are more likely to yield when turning right, arriving at the intersection later, and encountering an opposing road user who is close to the center of the road. This study highlights the importance of implicit communication in traffic and provides essential benchmarks for developing more human-like autonomous driving systems, capable of interpreting and responding to nuanced road user interactions at unsignalized intersections.

This study examines the effect of auditory displays, which are typically used as takeover signals in highly automated driving, on drivers during emergencies. Acute stress was assessed by analyzing physiological features within 10 s post-stimulation, in particular the root mean square of successive differences, raw-skin conductance, and low-frequency/high-frequency ratio. Sixteen participants were recruited to perform autopilot tasks in a simulated cockpit. Acute stress was induced using three sets of beeps with inter-pulse intervals of 0.2, 0.5, and 1 s, which serve as the auditory takeover request (TOR). The participants were required to immediately initiate vehicle takeovers and perform lane-changing maneuvers following each TOR, and their physiological, psychological, and behavioral data were acquired for analysis. The results show that the relationship between acute stress and signal frequency conforms to Stevens’ power law, thus highlighting the significance of the signal frequency with respect to acute stress. Although correlations are observed between perceived urgency and acute stress, the acute stress does not correlate significantly with the takeover parameters, such as the takeover time, information-processing time, and steering wheel speed. This study provides valuable insights into the effects of TORs on drivers in terms of acute stress, thus contributing to enhanced driving safety and guiding the design of auditory TORs.

Autonomous vehicles equipped with automation driving assistance features are attracting significant public attention for their safety, innovation, and efficiency. While existing research has explored how individuals’ cognition of autonomous vehicles influences their acceptance or adoption intention, there is limited understanding of drivers’ post-purchase usage behavior, particularly their resistance to using automation features. Taking the lens of psychological reactance theory, this research investigates the impact of driver type and car class on resistance to using automation features. We conducted a survey (N=391) and found that drivers with limited experience exhibit higher resistance to using these features compared to experienced drivers. This effect is mediated by the perceived threat to driving freedom and is moderated by car class. Specifically, this effect only holds for economy cars but not high-end cars. Our findings can help managers develop personalized recommendations for consumers regarding autonomous vehicles, and provide a reference for designing driver assistance systems tailored to car class.

Numerous studies exploring the link between daily commuting and mental well-being have primarily relied on cross-sectional designs and self-reported surveys. These methods often limit causal inference and are prone to recall bias. This study adopts a novel approach by utilizing time-stamped stress level data (objective) and experience sampling of moods (subjective) to assess the varied stress responses triggered by daily commuting. Our aim is to reexamine the effects of daily commuting on mental well-being, with a particular focus on evaluating how subjective (self-reported moods) and objective (biosignal data) measurement techniques capture these psychological and physiological responses differently. We involved 203 employees from Beijing, who wore portable smartwatches over a week. Throughout five working days, we conducted three random experience sampling surveys daily to collect real-time mood data. Initial analysis visualized the relationships between stress levels, moods, and commuting characteristics such as duration, mode, and timing. Subsequent analysis using mixed-effects models quantified the impacts of these commuting attributes on stress and mood. Our findings reveal that commute duration and mode significantly affect both mood and stress during commuting. Specifically, longer commutes are associated with poorer moods but surprisingly, lower stress levels. Regarding commuting modes, taking the bus and bicycling were found to enhance moods relative to traveling by car. Conversely, walking and cycling appeared to elevate stress levels the most, while shuttle bus use correlated with the lowest stress levels. Our study also highlights a discrepancy between physiological stress, as measured by biosignal technology, and psychological stress, as reported in surveys. This discrepancy underscores the complexities of measuring mental well-being and enriches the ongoing discussion about the intricate relationship between daily commuting and mental health.

The proliferation of e-scooters in urban spaces has introduced safety concerns despite their potential to reduce traffic congestion and provide an environmentally friendly solution for short-distance trips. This study consolidates existing knowledge on e-scooter safety through a systematic literature review of 168 academic studies and grey literature, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our primary objective is to identify the key e-scooter safety concerns from existing literature, together with the strategies stakeholders use to address these concerns, and highlight areas for further research. The literature shows that e-scooter riders are commonly injured in single-vehicle incidents, with a clear association between severe injuries and violations of traffic rules such as speeding and alcohol consumption. Frequently recommended safety measures include separating e-scooters from pedestrians, instituting licensing and mandatory training, and enforcing helmet usage and zero alcohol consumption. On top of that, clear legislative definitions for e-scooters ease and improve enforcement, and setting technical requirements for e-scooter design can improve stability, handling performance, and reduce incidents.

Understanding the differences between user types and the underlying factors influencing risky behaviour is crucial for developing effective interventions. Users of shared schemes often lack knowledge of rules and have poorer riding skills, possibly due to their less frequent use. Conversely, private e-scooter owners pose enforcement challenges for speeding and prohibited riding, as these scooters lack geofencing and tracking capabilities often found in shared scheme e-scooters. Helmet non-use, where mandatory, is attributed to a lack of support from riders for increased law enforcement and a low perception of risk rather than a lack of knowledge about the laws. Similarly, illegal sidewalk riding is linked to factors of comfort and convenience rather than infrastructure preference or unawareness of illegality. Proactive measures that are user-based, time-based, and location-based require further investigation. Consistently collecting and analysing data informs region-specific safety decisions and allows policymakers to monitor safety risks over time and assess intervention effectiveness, which are largely absent in current literature.

This study reviews the research on the use of gamification in the eco-driving context. Through a systematic literature review (N=28), it analyzes the effectiveness of different gamification types (i.e., achievement, social, and fictional). Their effectiveness is investigated from a theory of affordances perspective, and gamification affordances, psychological outcomes, and behavioral outcomes are analyzed in detail in the reviewed corpus. The results show that achievement-oriented gamification is the most prominent type of gamification that has been studied and has shown largely positive results in improving energy-efficient driver behavior, such as reduced fuel consumption and acceleration. In contrast, there is little research on the effectiveness of social and fictional gamification. Additionally, there is a need for research to clarify the psychological effects of specific gamification affordances. In light of the current research, the study provides design implications as well as avenues for future research.