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

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.

Scholars and policymakers increasingly are presenting the moped as part of a transition to more sustainable modes. However, the question remains as to where moped users should ride–as they often compete for space with other sustainable modes such as cycling or walking. This study focuses on the Netherlands, known as a cycling paradise, where mopeds share the cycling infrastructure. This has sparked controversies about spatial conflicts between moped users and cyclists, especially since the emergence of e-moped rental systems in 2017. Drawing on mobility studies and social identity theory, this paper explores the stereotypes of moped users and their behaviours to understand the spatial complexities of a shift towards more micromobility in the Netherlands. By analysing interviews with moped users and how users are discussed in the press, the paper empirically maps stereotypes of the users of different mopeds i.e. (1) fuel-based and privately owned, (2) electric and privately owned, and (3) electric and rental, and their behaviour on the bicycle path. Our study shows how debates tend to focus on the behaviours of moped users and their interactions with cyclists on shared bicycle paths while the spatial domination of automobility remains unchallenged. This paper contributes to transport behaviour research on spatial conflicts and identities in the context of the rise of micromobility − a key pillar of transitions to more sustainable mobility, alongside other changes such as fleet electrification, reduction of car use, and increased public transport uptake. Micromobilities entail what was traditionally understood as active mobility or non-motorised transport, such as cycling, but also what is now often discussed under the umbrella of MaaS or (light) electric vehicles, such as motorised two-wheelers, and also 'hybrids' such as e-bikes, fatbikes or cargo bikes. This paper exemplifies how identities, stereotypes and behaviours are relevant for understanding interactions around these modes and debates, in the quest towards low-car urban transitions.

In Highly Automated Vehicles (HAVs) without operators on-board, user interaction with the vehicle automation plays an important role for a safe and inclusive use of these services. Especially when Minimal Risk Maneuvers (MRM) are performed by the system, passengers are faced with uncertain situations. A possibility to deepen passenger’s understanding and predictability of these systeḿs and reduce their uncertainties is to enhance automation transparency. However, literature shows a lack regarding enhancing system transparency of HAVs during MRMs. Therefore, we investigated the impact of “observability” and “reasoning” as transparency influencing factors. In an online study, participants evaluated multiple internal Human-Machine Interfaces (iHMI) as shuttle passengers. The presented iHMIs varied regarding their level of transparency by giving different information about what the vehicle’s “perception” and its “reasoning” is. Results show significant differences in the passengers’ understanding between different iHMI variants providing evidence that information regarding the “perception” and “reasoning” of HAVs enhance system transparency. Results of the study may provide first insights into passengers’ informational needs when using HAV. They highlight the potential benefits of system transparency when designing interfaces for HMIs of automated vehicles.

Electric vehicles (EVs) are introduced to mitigate environmental problems and develop sustainable modes of transport across the globe. Researchers often report that the non-availability of charging infrastructure is the primary concern for EV adoption. The traditional plug-in EV charging method has a higher waiting time, discouraging users from adopting EVs. Many countries, including India, are promoting an alternative battery swapping method (BSM) for EV charging to reduce the waiting time. But the user preference and willingness to adopt BSM remain unexplored, especially in developing countries. The existing refuel stations are a potential location for developing charging infrastructure that provides the EV charging service and helps create awareness among users because of their wide visibility. Thus, this study aims to bridge the research gap by exploring the influential factors, user preferences, and willingness to use the BSM at refuel stations. For this purpose, 1013 samples were collected from road users who visited 51 refueling stations using the random sampling method in the twin cities of Ahmedabad and Gandhinagar. An integrated partial least squares-structural equation modelling with the artificial neural network method was adopted in this study. The study’s findings reveal that the development of public EV charging facilities at refuel stations significantly impacts the user’s willingness to shift to EVs. The convenience and cost-related motivating factors like a lesser waiting time compared to the plug-in charging method, reduced range anxiety, no concern about battery usage, reduced initial purchase cost of an EV, and comparatively lower maintenance costs significantly motivates user’s willingness to adopt BSM. Similarly, battery-related demotivating factors like the non-reliable range of the swapped battery, non-standard battery design in terms of type, size, capacity, and brand across the country, additional cost for leasing or renting the battery, and chances that EV batteries might be replaced with fake batteries concern BSM adoption.

Objective

Driver distractions are a significant contributor to road accidents and fatalities worldwide. The present research investigated the prevalence of observable driver distractions on both sides of Nicosia, as well as exploring the effect of drivers’ characteristics and time-related variables on their prevalence.

Methods

Roadside observations were conducted at eight randomly selected locations in the city of Nicosia, Cyprus. Four of these sites were located in the area of Nicosia controlled by the Republic of Cyprus, and the other four were in the area that is referred to as the Turkish Republic of Northern Cyprus (TRNC) by its administration.

Results

A total of 16,070 drivers were observed, with 8,948 being in the Republic of Cyprus (South) and 7,122 in the Turkish-controlled section of Nicosia (North). A slightly higher proportion of drivers were observed driving distracted in the South (28.0%) than was found in the northern part of the city (25.7%). The most commonly observed secondary tasks in the South were using headphones (9.2%), talking to a passenger (8.1%) and using a mobile 0.4%, 3.7% talking and 2.7% texting). In contrast, the most commonly observed secondary tasks in the North were talking to passengers (10.2%), wearing headphones (8.4%) and using a mobile 0.6% for talking and 2.5% for texting). Gender-related differences were found for a number of different distractions (i.e., talking to passengers, drinking, and handheld mobile phone conversations), and age emerged as a significant predictor for most secondary tasks, including talking to passengers, smoking, hands-free mobile phone use, handheld mobile phone use, texting/keying numbers, drinking and engagement in any type of distraction (all distractions combined). The overall pattern for age was that middle-aged and older drivers were less likely to be distracted than younger drivers.

Conclusions

A relatively high proportion of drivers on both sides of Nicosia were engaged in a secondary task while driving. These findings clearly indicate that younger drivers are more likely to drive distracted, which probably contributes to their higher crash rates.