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

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.

Drivers engage in a variety of secondary activities while driving. Research suggests that many secondary tasks interfere with driving, making performance worse as compared to single-task driving, but a recent study suggests that in simple environments (low scenery and traffic) listening to an audiobook may actually benefit driving performance. Nonetheless, these effects may vary based on both the textual complexity of the audiobook and the working memory capacity of the driver. In this study, we used a driving simulator to compare single-task driving with that when the driver was listening to an audiobook (dual-task). We manipulated the complexity of the audiobook as measured by Lexile scores (a standard index of text difficulty). Licensed drivers did two 30-minute drives on simple roads, alternating between driving while listening to an audiobook (dual-task) or single-task driving. Drivers did one drive with the simple and the other with the complex audiobook (order counterbalanced). Listening to the simple audiobook improved driving performance as compared to single-task driving: braking response times to hazards were lower, as were steering and headway variability. Conversely, listening to the complex audiobook interfered with driving; braking times to hazards and steering variability were higher when drivers were listening to the audiobook than for single-task driving. Individual differences in working memory capacity as measured by the OSPAN (Operation Span) predicted how much listening to an audiobook benefitted performance, with the highest OSPAN scorers benefitting most, though these OSPAN-related differential benefits were restricted to reduced hazard response times while listening to the simple audiobook.

Pedestrian risky behaviors are one of the contributing factors to crashes involving pedestrians. Therefore, it is crucial to comprehend the mechanisms by which pedestrians interact with many influential components in the traffic environment. This study aimed to evaluate pedestrians’ red light running intentions and related factors under different traffic flow scenarios, including straight traffic flow, right-turning traffic flow, and left-turning traffic flow. A theoretical approach based on the theory of planned behavior (TPB) and the prototype willingness model (PWM) was employed. Data were collected from an online survey of 2250 participants in Tehran, Iran. Structural equation modeling (SEM) was used to identify the significant factors that explain intentions. All models successfully explained the behavioral intention for red light running violation; however, the findings revealed that the integrated model was the best-performing model to represent violation and, thus, was selected for interpreting the results and drawing relevant conclusions. Different traffic flow scenarios had varied effects on violation intentions for individual characteristics and model constructs. Previous crash experiences and driving-related background variables emerged to impact pedestrian violation intention across three scenarios. The findings also suggested that the rational constructs (attitude, perceived behavioral control, and facilitating conditions) had a more robust impact on violation intention compared to reactive constructs (prototype similarity, prototype favorability), with facilitating conditions being the strongest predictor of the model, followed by attitudes toward violation as a significant predictor of intention for red light violation. According to the results, the mechanism of risk-taking varies depending on the direction of the traffic flow. Higher risk was associated with the violation at the intersections with straight traffic flow compared to the intersections with turning traffic flow. Based on the findings of this study, several implications, including interventions focusing on individuals’ transportation safety attitudes, countermeasures to increase the risk perception of pedestrians toward turning vehicles, and countermeasures regarding the use of mobile phones while walking for the context of this study were proposed.

Research has demonstrated the benefits of external human–machine interfaces (eHMIs) in increasing vulnerable road users’ (VRU) feeling of safety in interactions with automated vehicles (AVs). However, two key gaps exist in the literature. First, existing studies examined AV-VRU communication aspects in the context of conventional roads with traffic controls, but not for shared spaces where VRU-AV interaction is reliant on communication between the two parties. Second, limited knowledge is available on the differences between cyclists and pedestrians when interacting with AV. This paper aims to address these gaps through an online questionnaire among 254 cyclists and pedestrians in Australia and the UK. Perceived safety was measured in terms of willingness to cross in front of an AV, feeling of security, and feeling of relaxation. Results from a three-stage least square regression analysis identified differences in the factors for pedestrians and cyclists. Pedestrians that were male, over the age of 35, not regular cyclists, or residents of the UK reported lower feelings of safety, relaxation, and willingness to cross than their counterparts. Similar results were found cyclists who are older than 45 years, and UK residents compared to other cyclist participants. Both pedestrians and cyclists reported more willingness to cross and higher feelings of security and relaxation when an eHMI was present. These findings indicate that for effective use and understanding of eHMIs targeted interventions are needed to address the specific concerns of different demographic groups, as identified in this research. By increasing public understanding and acceptance of AVs – as well as eHMIs – across all demographic groups, researchers can promote a smooth integration of these technologies into shared spaces.

Evaluating drivers’ situation awareness (SA) is important in the implementation of alert prioritization. This study investigates the relationship between driving performance measures (speed, acceleration and brake usage, steering wheel and lane deviation), pedestrian interaction (location, direction and motion), and driver SA. To achieve this, a controlled study was conducted with 56 participants using a Balanced Incomplete Block Design, where each participant drove 18 out of 48 possible intersections in a driving simulator environment. The Situational Awareness Global Assessment Technique (SAGAT) method was used to assess drivers’ SA. Mixed effects logit models were developed to examine the different SA Levels (perception, comprehension, projection). The driving performance measures were aggregated across three time windows (1, 3, and 5 s). The findings show significant contributions from both driving performance measures and pedestrian interactions in predicting driver SA. More specifically, a one-second time window was useful for predicting pedestrian direction and a three-second time window was best for predicting pedestrian location and intention to cross. The results indicate the importance of considering different time windows for predicting various levels of driver SA responses. These findings offer insights into factors to be considered in driver SA predictive models.

The transition from automated to manual driving, referred as to Take-over conditions (TOC), in highly automated vehicles (e.g., SAE Level 4 or higher) is a subject of great interest to driver’s safety researchers, considering advancement of automotive technologies. While the literature has focused primarily on the post-take-over behavior of passenger car drivers, assessing different aspects of Commercial Motor Vehicle (CMV) drivers’ post-take-over behavior has received less attention, although it is anticipated that CMVs will be the first to vastly adopt highly automated technology. This paper aims to address the question of how long the effect of TOC lasts in CMV drivers and how automated operation duration before TOC, repeated TOC, and driver’s factors (i.e., age, gender, education, and driving history) affect the duration of TOC’s effect. To accomplish this, we designed a 40-minute experiment on a driving simulator and compared participants’ responses to TOC with continuous manual driving to first, assess significant changes in driving behavior indices (e.g., acceleration, velocity, and headway) in different time intervals and second, evaluate the survival patterns of unsafe behaviors (e.g., hard brakes, sharp turns, and speeding) over time. Multilevel Mixed-effect Linear Models and Multilevel Mixed-effect Parametric Survival Models are incorporated to assess the duration of TOC’s effects. Results showed that the first 10 s of TOC carries the most significant driving behavior changes while the probability of observing unsafe behaviors reduces significantly after 20 s. The results indicated that the effect of TOC lasts longer in long-automated operations, old drivers, and drivers with bad driving history, while repeated TOCs, showed positive effects on mediating the effect of this transition. The findings of this paper offer valuable insights to automotive companies and transportation planners on the nature of Take-over conditions.

Electronic fences are now used to regulate the parking behavior of bike-sharing users, but the issue of improper parking within such fenced areas has not been resolved. Based on the theories of perceived value and perceived risk, this study used online behavioral experiments to simulate a scenario of users parking shared bicycles. By considering three factors — economic incentives, punitive measures, and travel scenarios — this study examined variations in users’ willingness to standardize the parking of shared bicycles. Data from 809 valid questionnaires were collected and empirically analyzed using bootstrap and regression analyses. According to the results, both economic incentives and penalties significantly enhanced users’ willingness to standardize the parking of shared bicycles, and the impact of penalties was slightly stronger than that of incentives. Perceived value played a mediating role between economic incentives and users’ willingness to properly park shared bicycles. Perceived risk acted as a mediator between punitive measures and the regulated parking intention of users. Travel scenarios served as a moderating factor between penalties and users’ willingness to park shared bicycles in a compliant manner, with the users’ compliance willingness in non-commuting travel scenarios significantly surpassing that in commuting contexts. These findings enrich the knowledge of sustainable usage behaviors among bike-sharing users, providing insights for bike-sharing companies to manage user behavior. Based on these results, several policy recommendations aimed at guiding governments and companies in regulating electronic fences and user parking behaviors are proposed.