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

{"title":"Investigating nighttime driver behaviors and interactions at pedestrian Hybrid Beacons","authors":"Xi Zhang,&nbsp;Alyssa Ryan,&nbsp;Yao-Jan Wu","doi":"10.1016/j.trf.2025.07.011","DOIUrl":"10.1016/j.trf.2025.07.011","url":null,"abstract":"<div><div>Pedestrian safety remains a critical concern globally and in the United States. Pedestrian Hybrid Beacons (PHBs) at marked crosswalks have been effective in increasing driver-yielding rates and reducing pedestrian crashes. However, nighttime driver behaviors and social interactions at PHBs, e.g., imitating the behavior of peer drivers, have remained understudied in the post-pandemic context. This study investigates nighttime driver behaviors and explores empirical evidence of social interactions at PHBs following the pandemic. Driver behaviors are collected from videos from four PHB locations in Pima County, Arizona. Descriptive analysis and logistic regression models are used to reveal drivers’ non-compliance rates and interactions with pedestrians and peer vehicles at PHBs at night. Results indicate that 94% to 97% of drivers stopped during the steady red phase of PHBs at night and compliance dropped further to 53% during the flashing red phase. Compared to initial drivers in a platoon approaching during the steady red phase, those approaching during the flashing red phase were approximately 3.6 times more likely to fail to stop. Among leading-following pairs in a platoon (excluding the first vehicles), 50% to 83% of following drivers mimicked the leading vehicle’s behavior, even when the leading driver violated traffic laws. At intersections with a speed limit of 25 mph, 41.7% of drivers resumed travel during the flashing red phase, even when pedestrians were in the crosswalk. These findings provide critical insights into nighttime driver behaviors and social interactions at PHBs. The results can inform improvements in PHB design, implementation, and pedestrian crossing treatments.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"114 ","pages":"Pages 919-932"},"PeriodicalIF":3.5,"publicationDate":"2025-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The role of social perceptions on willingness-to-pay for innovations","authors":"Milad Mehdizadeh ,&nbsp;Christian A. Klöckner","doi":"10.1016/j.trf.2025.07.008","DOIUrl":"10.1016/j.trf.2025.07.008","url":null,"abstract":"<div><div>Innovations might be catalysts for societal progress, driving economic growth, and elevating living standards. By estimating willingness-to-pay (WTP), we can gain insight into the extent to which individuals are willing to adopt innovations. WTP studies so far have estimated <em>individual</em> WTP (WTP_I), which refers to the amount individuals are willing to pay for an innovation. We argue that adoption is likely also affected by an individual’s perception of how much others are willing to pay, thus setting the standard, which we refer to as <em>others’</em> WTP (WTP_O). WTP_O can affect WTP_I, as people may think this is a sensible amount to pay for an innovation (cf. follow social norms). At the same time, WTP_I can influence WTP_O, because when individuals are not sure about what others prefer, they may rely on their own preference as a proxy. Hence, WTP_I and WTP_O are likely to mutually influence each other. Yet, studies have not considered the role of WTP_O. We extend the literature by also accounting for WTP_O in the estimation of WTP. As a case in point, we focus on WTP for automated vehicles (AVs). Results reveal that WTP_I and WTP_O positively influence each other. Further, we examined which factors affect WTP, and found that the overall WTP (i.e., the strength of the correlation between WTP_I and WTP_O) is higher among certain population segments, such as current electric vehicle users and people with a higher level of innovativeness. Interestingly, overall WTP is more strongly affected by WTP_O than WTP_I, indicating that the perception of how much others will be willing to pay may have a greater impact on the adoption likelihood of an innovation than the perception of our own willingness to pay.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"114 ","pages":"Pages 906-918"},"PeriodicalIF":3.5,"publicationDate":"2025-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144588817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting Drivers’ situation awareness and response times in the emergency situation using an integrated cognitive architecture","authors":"Linli Xu ,&nbsp;Lie Guo ,&nbsp;Xu Wang ,&nbsp;Pingshu Ge ,&nbsp;Longxin Guan","doi":"10.1016/j.trf.2025.07.007","DOIUrl":"10.1016/j.trf.2025.07.007","url":null,"abstract":"<div><div>Because drivers are allowed to perform non-driving related tasks (NDRTs) in Level 3 (L3) automated driving, it is necessary to investigate the effects of NDRTs on driver behavior to ensure a safe transition of control. This study aims to examine drivers’ situation awareness (SA) changes and response abilities under NDRTs with different resource demands. Significantly, this study presents a novel cognitive mechanism to refine the takeover cognitive model under different NDRTs. Besides, time stress was considered as a latent variable manifested by the change in drivers’ SA recovery and takeover strategies after the takeover request (TOR). Seven single-task models were built using the Queuing Network-Adaptive Control of Thought Rational (QN-ACTR) cognitive architecture. The study combined them into a more complex takeover model naturally by utilizing the multi-task scheduling mechanism of QN-ACTR to simulate multi-tasking performance. Simultaneously, 80 drivers’ visual behavior and response time were recorded. The experiment results showed that visual resource demands significantly impaired drivers’ SA recovery and prolonged takeover decision time after the TOR. Physical resource demands primarily increased drivers’ motor readiness time and takeover time. In contrast, engaging in NDRTs that require only cognitive resources enabled drivers to remain alert during automated driving and respond more quickly after the TOR. These findings suggest that NDRTs with a moderate level of cognitive resource demand may be more appropriate for L3 automated driving. Regarding model fitness, coefficients of determination (<em>R²</em>) for visual behavior before and after the TOR were 0.96 and 0.94, respectively. <em>R²</em> was 0.98 for the response time. The model could fit the human data well. Overall, the modeling method and production rules in this study are reasonable representations of drivers’ takeover strategies and skills. The model can be used to explain drivers’ cognitive mechanisms under different NDRTs.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"114 ","pages":"Pages 873-887"},"PeriodicalIF":3.5,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144579371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of the difficulty of the box task on its sensitivity when combined with a detection response task to assess secondary task demand while driving","authors":"Daniel Trommler ,&nbsp;Tina Morgenstern ,&nbsp;Ines Karl ,&nbsp;Frederik Naujoks ,&nbsp;Josef F. Krems ,&nbsp;Andreas Keinath","doi":"10.1016/j.trf.2025.06.028","DOIUrl":"10.1016/j.trf.2025.06.028","url":null,"abstract":"<div><div>Multimodal in-vehicle infotainment systems offer drivers a range of non-driving-related functions but can increase visual-manual and cognitive task demand, compromising road safety. Therefore, it is important to estimate the secondary task demand of these systems early in the development process. To do so, the Box Task combined with a Detection Response Task (BT + DRT) was developed as a straightforward laboratory method. The BT is used to quantify the visual-manual task demand, while the DRT is capable of assessing cognitive demand. However, previous studies showed that difficult cognitive secondary task demand led to a similar decrease in performance in the BT to that found in the easy visual-manual demand. Therefore, this study aimed to enhance the BT’s sensitivity to visual-manual demand and discriminability from cognitive demand by increasing the difficulty of the BT. Additionally, the effects of increased BT difficulty on DRT metrics, self-assessed mental workload and secondary task performance were examined. In total, <em>N</em> = 39 participants performed the BT + DRT with varying BT difficulty levels (easy, moderate and difficult), secondary task types (visual-manual vs. cognitive) and secondary task difficulty levels (easy vs. difficult). The results indicated that lateral variability at moderate and difficult BT levels was the BT metric with the largest and most consistent effect sizes for assessing visual-manual secondary task demand and to discriminate from performance impairments resulting from cognitive task demand. At both BT levels, the DRT is also capable of effectively assessing cognitive demand, either through response time or the number of omissions. For self-assessed workload, only slight increases in ratings were observed for higher BT difficulty levels. There were only minor changes in secondary task performance, such as slightly slower responses, during more difficult BT levels. Consequently, a higher BT difficulty than previously used is recommended for the BT + DRT paradigm.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"114 ","pages":"Pages 888-905"},"PeriodicalIF":3.5,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144588816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating simulator validity by using physiological and cognitive stress indicators","authors":"Marcin Czaban ,&nbsp;Chantal Himmels","doi":"10.1016/j.trf.2025.07.006","DOIUrl":"10.1016/j.trf.2025.07.006","url":null,"abstract":"<div><div>Driving simulators are indispensable tools in modern automotive research and development. However, the transferability of findings to real-world driving, and thus, the validity of simulator-based results, cannot be assumed without empirical validation.</div><div>In this study, we examined physiological (Galvanic Skin Response-based measures, Electrocardiogram-based measures, salivary cortisol) and cognitive (NASA Task Load Index, Short Stress State Questionnaire, single-item ratings) stress indicators by comparing a real-world driving circuit with seven distinct sections to a medium-fidelity driving simulator, applying a Bayesian analytical approach. The results present a mixed picture, with both absolute and relative validity observed for certain physiological and cognitive stress indicators. Overall, our findings suggest that stress responses in the simulator and real-world driving are comparable, although the simulator was subjectively perceived as more stressful.</div><div>These results provide valuable insights into the validity of simulators for stress research and underscore the need to consider individual differences, experimental conditions, and methodological approaches in future studies.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"114 ","pages":"Pages 831-851"},"PeriodicalIF":3.5,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144571286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving road safety in rural areas: An examination of the traffic safety climate in rural Wales","authors":"Burcu Tekeş ,&nbsp;Charles Musselwhite ,&nbsp;Pınar Bıçaksız","doi":"10.1016/j.trf.2025.07.003","DOIUrl":"10.1016/j.trf.2025.07.003","url":null,"abstract":"<div><div>Although there is a body of research conducted on traffic safety and driver behaviors in the UK, studies on traffic safety climate, particularly in rural Wales, are limited. In this study, the effect of traffic safety climate in Wales on several driving-related characteristics was investigated and expected to find a difference between rural and urban Wales. The model investigated the moderator role of rural/urban areas on the relationship between traffic safety climate and driver behaviors, driver anger, anger expression, and driver risk. Using data from 346 participants, we found that drivers in rural areas perceive traffic as having more internal requirements, but also engage in more risk-taking, whereas drivers in urban areas score higher in aggressive violations and verbal aggressive expression. In the following steps, we found links between traffic safety climate and various driver-related outcomes, and this link differs across drivers living in rural and urban areas. These findings suggest the need for tailored strategies to address road safety in rural areas in Wales.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"114 ","pages":"Pages 864-872"},"PeriodicalIF":3.5,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144571877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Driver dysfunctional impulsivity dominates over others in anger expression","authors":"Berfin Töre ,&nbsp;Bilgesu Kaçan-Bibican ,&nbsp;Türker Özkan","doi":"10.1016/j.trf.2025.06.026","DOIUrl":"10.1016/j.trf.2025.06.026","url":null,"abstract":"<div><div>The aim of this study is to examine whether driver impulsivity predicts aggressive driver behavior and to compare the predictive power of driver impulsivity and general impulsivity towards aggressive driver behavior. A total of 312 drivers, 113 women and 199 men, participated in the study and completed the Demographic Information Form, Driver Anger Expression Inventory, Barrat Impulsivity Scale-Short Form and Impulsive Driver Scale by way of an online link. The hierarchical regression analyses showed that driver dysfunctional impulsivity positively predicted physical anger expression, verbal anger expression and the use of a vehicle to express anger whereas it negatively predicted the adaptive anger expression. Driver functional impulsivity positively predicted physical anger expression, the use of a vehicle to express anger and the adaptive anger expression. The dominance analyses results show that driver dysfunctional impulsivity completely dominates all other driver impulsivity and general impulsivity dimensions for both adaptive and non-adaptive anger expression of drivers. The results of the study emphasize the importance of conceptually addressing impulsivity in future studies and the impact of the measurement tool to be used on the results.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"114 ","pages":"Pages 852-863"},"PeriodicalIF":3.5,"publicationDate":"2025-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144571287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring driver decision-making in lane-changing: A human factors approach using AI and naturalistic data","authors":"Akshay Gupta ,&nbsp;Pushpa Choudhary ,&nbsp;Manoranjan Parida","doi":"10.1016/j.trf.2025.06.030","DOIUrl":"10.1016/j.trf.2025.06.030","url":null,"abstract":"<div><div>Anticipating lane-change patterns represents a crucial dimension within the intricate framework of lane-change decision-making, exerting a profound influence on the fluidity of traffic dynamics and the overarching spectrum of road safety. Previous studies have mostly focused on fixed sections of highways, missing the changing and complex traffic patterns that drivers experience throughout the entire highway journey. This study explores the behavioural dimensions of lane-changing by leveraging an innovative data collection approach using cost-effective 3D LiDAR technology integrated into an instrumented vehicle platform. This system enables real-time, high-resolution data capture under diverse driving conditions, including nighttime and low-visibility scenarios. The study introduces the Expressway Drive Instrumented Vehicle (EDIV) Dataset, which captures naturalistic driving behaviour from 60 drivers over approximately 8,100 km on Indian expressways. Beyond the mere prediction of drivers’ lane-changing events, the research delves deeper into the intricate composition of lane transitions, employing a sophisticated repertoire of Machine Learning (ML) methodologies. Notably, the Extreme Gradient Boosting (XGBoost) technique emerges as the preeminent contender, showcasing better efficacy in accordance with classification metrics. Culminating in the application of elucidatory Artificial Intelligence (AI) paradigms, such as SHapley Additive exPlanations (SHAP) values, to interpret the intricacies of XGBoost-derived insights into driving behaviour. By integrating human factors research with data-driven methodologies, this study contributes to the development of safer and more behavioural informed traffic systems in mixed traffic environments.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"114 ","pages":"Pages 794-820"},"PeriodicalIF":3.5,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144570946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of urban vs rural environments on driving mobility and safety in older age","authors":"Sol Morrissey ,&nbsp;Stephen Jeffs ,&nbsp;Rachel Gillings ,&nbsp;Mizanur Khondoker ,&nbsp;Mary Fisher-Morris ,&nbsp;Ed Manley ,&nbsp;Michael Hornberger","doi":"10.1016/j.trf.2025.07.005","DOIUrl":"10.1016/j.trf.2025.07.005","url":null,"abstract":"<div><div>Older rural drivers rely more on driving due to limited transportation options, but the impact of cognition on driving in urban versus rural settings is unclear. This study examined whether cognitive changes affect driving mobility and road safety differently across these populations. In a prospective cohort study, 969 older drivers completed driving behaviour and road traffic incident (RTI) history questionnaires, followed by cognitive testing, with a follow-up one year later. We find that older rural drivers have a greater driving mobility than older urban drivers and are less likely to reduce their driving mobility over time, as only urban residents with cognitive decline reduced their driving space. RTI incidence was higher in urban areas, with a stronger link between poor cognition and increased RTI risk in urban residents. This study suggests the interaction between cognitive changes and environmental setting on driving behaviour, providing insights for policy development on driving mobility and safety among older adults.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"114 ","pages":"Pages 821-830"},"PeriodicalIF":3.5,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144570947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting lane changes in real-world driving: analysing explicit, implicit and contextual cues on the motorway","authors":"Konstantin Felbel ,&nbsp;Maximilian Hentschel ,&nbsp;Katharina Simon ,&nbsp;André Dettmann ,&nbsp;Lewis L. Chuang ,&nbsp;Angelika C. Bullinger","doi":"10.1016/j.trf.2025.06.023","DOIUrl":"10.1016/j.trf.2025.06.023","url":null,"abstract":"<div><div>Communication of intention between drivers relies on explicit cues and implicit cues. While these cues have been extensively studied in urban environments, their application to motorway driving remains underexplored. This gap is particularly evident in lane change scenarios, where communication failures such as the failure to accurately predict an imminent lane change can result in significant safety risks. Furthermore, although contextual cues are theorised to play an important role, empirical studies of their influence are limited. Results of our research start to fill both gaps by investigating how drivers predict lane changes on motorways, considering explicit, implicit and contextual cues. We utilized a Naturalistic Driving Study (NDS) approach, wherein 30 participants documented 798 relevant lane change situations during their daily drives. Data was collected through smartphones equipped with a custom app for real-time voice and video recording. The results highlight that effective communication relies primarily on implicit cues, such as longitudinal and lateral vehicle motion and movement patterns, which drivers use to predict driving behaviour. Contextual cues, including dynamic cues such as vehicle spacing and static cues such as the wider traffic environment, play a secondary role in shaping drivers’ predictions. Interestingly, explicit cues were rarely used by drivers in their decision making, highlighting their limited role in communication in motorway scenarios. These results support the development of automated driving styles that emulate human-like behaviour which could lead to automated vehicles that are more intuitive and predictable for human drivers, both within the automated vehicle and in the surrounding traffic.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"114 ","pages":"Pages 780-793"},"PeriodicalIF":3.5,"publicationDate":"2025-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144557470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}