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

{"title":"Effect of monitoring duration on merging performance and eye movement after takeover request considering different driving styles","authors":"Kai Kang,&nbsp;Yongfeng Ma,&nbsp;Junjie Zhang,&nbsp;Beibei Xu,&nbsp;Wenhu Qin,&nbsp;Shuyan Chen","doi":"10.1016/j.trf.2026.103779","DOIUrl":"10.1016/j.trf.2026.103779","url":null,"abstract":"<div><div>Ensuring safe transitions from automated to manual control remains a critical challenge in conditionally automated driving. Monitoring requests issued before potential takeover requests have been shown to facilitate the development of situational awareness. However, takeover performance still varies considerably, influenced by individual driving styles and system design. This study examines how monitoring duration and driving style influence merging performance and gaze behavior following takeover requests in Level 3 automated driving. A driving simulator experiment was conducted with 63 participants representing different driving styles. Participants encountered takeover requests during a merging scenario under three monitoring durations (short, medium, and long) and driving style conditions (aggressive, normal, and defensive). Eye-tracking data and merging performance measures were collected and analyzed using linear mixed-effects models. In addition, takeover time was modeled using a Weibull accelerated failure time with shared frailty. The results showed that monitoring requests directed drivers' visual attention toward the driving task. Although monitoring duration affected forward roadway attention differently across driving styles, the medium-duration condition was associated with shorter takeover times than the short monitoring condition. In contrast, longer monitoring durations were associated with greater steering angle variability, as reflected by an increased steering angle standard deviation. These findings imply that a 5-s monitoring request may effectively support timely driver responses across different driving styles compared with shorter monitoring durations. Designing monitoring stages with appropriate durations may enhance situational awareness and reduce takeover time, thereby improving takeover safety. These findings provide practical guidance for developing monitoring request strategies in conditionally automated driving systems.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"122 ","pages":"Article 103779"},"PeriodicalIF":5.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148771780","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":"Understanding consumer acceptance of autonomous delivery services: the asymmetric roles of technology readiness in dual-valence behavioral reasoning","authors":"Ya Liang,&nbsp;Lixian Qian,&nbsp;Yang Lu,&nbsp;Tolga Bektaş","doi":"10.1016/j.trf.2026.103794","DOIUrl":"10.1016/j.trf.2026.103794","url":null,"abstract":"<div><div>E-commerce expansion has intensified pressure on urban last-mile delivery, spurring interest in autonomous delivery services (ADS) enabled by autonomous delivery vehicles and robots. As ADS combine app-based coordination with autonomous movement and parcel handover in shared urban spaces, consumer acceptance is psychologically complex, involving functional benefits alongside concerns about reliability, privacy, pedestrian safety, and accountability. Drawing on behavioral reasoning theory (BRT) and technology readiness (TR), this study examines ADS acceptance as a dual-valence reasoning process and investigates how four TR dimensions relate to context-specific reasons for and against use. Survey data from 827 adults in five Chinese cities were analyzed using covariance-based structural equation modeling. Results reveal a pronounced asymmetry: functional “reasons for” has a strong positive association with intention (<em>β</em> = 0.857), whereas “reasons against” shows a weak negative association (<em>β</em> = −0.064). TR dimensions also exhibit asymmetric patterns: innovativeness and discomfort are associated with both reasoning valences in opposite directions, while optimism and insecurity primarily relate to supportive and inhibitive reasoning, respectively. Further indirect-effect analysis shows that innovativeness and discomfort are associated with intention primarily through consumers' reasoning, whereas optimism has both direct and reasoning-based associations with intention. For insecurity, only the pathway through inhibitive reasoning is statistically supported. This study advances ADS acceptance research by conceptualizing acceptance as a dual-valence reasoning process and extends BRT by showing that TR dimensions are distinctly associated with supportive and inhibitive reasoning. The findings suggest communicating functional utilities, reducing operational concerns, and tailoring support to technology-readiness profiles to foster ADS acceptance.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"122 ","pages":"Article 103794"},"PeriodicalIF":5.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148958574","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":"Trust in the wild: Multi-modal safety perceptions in naturalistic AV deployment","authors":"Carlos Guirado,&nbsp;SangHyouk Oum,&nbsp;Julia Griswold,&nbsp;Joan Walker","doi":"10.1016/j.trf.2026.103738","DOIUrl":"10.1016/j.trf.2026.103738","url":null,"abstract":"<div><div>Public acceptance remains a major barrier to autonomous vehicle (AV) deployment, yet most perception research relies on hypothetical surveys or small controlled experiments with AV-naive respondents. This cross-sectional study surveys 811 San Francisco Bay Area residents with real-world AV exposure (376 robotaxi passengers and 435 non-passengers: pedestrians, cyclists, and drivers) in one of the world’s most mature deployment environments. We ask whether trust levels among AV-exposed residents differ from national baselines, whether trust varies by interaction mode, and whether experience is associated with differential recalibration of specific safety concerns. We find that 61% trust AVs to be safe, 4.7 times the 13% national rate. Trust varies sharply by mode: passengers report 82% trust versus 43-45% among non-passengers. Even non-riders far exceed national levels, consistent with ambient exposure beyond ridership alone contributing to higher trust, though residential selection cannot be ruled out. Concern about system malfunction is significantly lower among passengers (45%) than pedestrians and cyclists (63%), consistent with recalibration through direct performance feedback, whereas concern about unpredictable human behavior remains constant across all modes ( ∼ 55%). These patterns suggest that experience is associated with attenuation of technology-related concerns while human-behavior concerns persist: a divergence with implications for communication strategies and infrastructure design as AV deployment expands.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"122 ","pages":"Article 103738"},"PeriodicalIF":5.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148638931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Eco-safe driving for challenging terrains: Development of a machine learning–driven benchmarking framework for bus drivers","authors":"Arun T. Moonjely,&nbsp;Munavar Fairooz Cheranchery,&nbsp;Harikrishna Madhavan","doi":"10.1016/j.trf.2026.103787","DOIUrl":"10.1016/j.trf.2026.103787","url":null,"abstract":"<div><div>Bus transport systems in emerging economies are significantly affected by unsafe driving practices and poor fuel-efficient driving behaviour, indicating a pressing need to impart eco-safe driving practices. The study proposes a machine-learning driven benchmarking framework for eco-safe driving that accounts for terrain heterogeneity, developed using an extensive dataset of 126 h and 3960 km of naturalistic driving. The data was collected from experienced master drivers who have maintained a zero-crash history and demonstrated superior fuel efficiency over the years. The novel framework included multiple stages focusing on feature identification, behaviour classification, and cluster validation driven by advanced machine learning tools. Key features were identified using an XG-Boost classifier integrated with Permutation Importance, which were subsequently used in a Fuzzy C-Means clustering framework to classify eco-safe driving styles. This was further validated using a supervised LSTM model. The study was conducted in challenging geographic terrain, where nearly 20% of the study stretch comprising of mountainous segments including nine hairpin curves, exposing the analysis to realistic operational complexities. Feature selection and modelling revealed that driving behaviour is highly terrain-dependent, and a universal eco-safe threshold is inadequate. The key contribution of this study lies in the development of terrain-specific, data-driven thresholds for eco-safe driving behaviour, derived through a two-stage framework involving driving pattern identification and statistical benchmark generation. The study identified two distinct eco-safe driving styles, challenging the traditional belief that only conservative driving ensures safety and fuel economy. Accordingly, the framework establishes terrain-specific eco-safe driving thresholds, enabling accurate benchmarking across plain, rolling, and mountainous roads. While the study questions the conventional unimodal drivers training approach followed in emerging economies like India, it introduces a machine learning driven framework with terrain-specific benchmarks to systematically promote eco-safe driving in challenging operating environments.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"122 ","pages":"Article 103787"},"PeriodicalIF":5.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148844574","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":"A safety comparison of touchscreen and physical controls for driving-related tasks","authors":"Chelsea A. DeGuzman,&nbsp;Suzan Ayas,&nbsp;Joanne Harbluk,&nbsp;Caroll Lau,&nbsp;Peter C. Burns,&nbsp;Birsen Donmez","doi":"10.1016/j.trf.2026.103775","DOIUrl":"10.1016/j.trf.2026.103775","url":null,"abstract":"<div><div>Some vehicle manufacturers have replaced physical driving-related controls (e.g., windshield wiper settings) with touchscreen controls. However, there is limited research investigating how this change may affect driver behaviour. We conducted a driving simulator study to compare touchscreen and physical controls for performing driving-related tasks across five systems: exterior lighting, windshield wipers, turn indicators, hazard lights, and climate. Tasks varied by length and were completed under lower demand and higher demand road conditions. We also conducted a preliminary exploration of whether driver behaviour is affected by touchscreen layout changes, which may occur due to an over-the-air software update. Thirty-two participants completed the study (17 M, 15 W; mean age = 34.8). For tasks requiring more than one button press, the touchscreen was associated with worse task performance (e.g., longer task completion time) and worse driving performance (e.g., higher speed and lane position variance, longer reaction time to lead vehicle braking) than physical controls. For all tasks, the touchscreen was associated with increased visual distraction. A minor layout change (switching the location of two controls on the screen) impaired task performance and increased long glances to the touchscreen for the first task after the layout change. These results can be used to inform touchscreen design guidelines and requirements for retaining task-appropriate physical controls for certain driving-related tasks. For example, our findings suggest that touchscreens should be avoided for any critical driving-related tasks requiring more than one button press. Further, if over-the-air software updates are used, manufacturers may want to restrict initial interactions while the vehicle is in motion.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"122 ","pages":"Article 103775"},"PeriodicalIF":5.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148958575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stakeholder-Informed Analysis of Teen Driver Safety Perceptions: The Michigan Case","authors":"Ying Thaviphoke,&nbsp;Osama Abudayyeh,&nbsp;Chowdhury Ashraful Hossain,&nbsp;Inan Ishraque","doi":"10.1016/j.trf.2026.103754","DOIUrl":"10.1016/j.trf.2026.103754","url":null,"abstract":"<div><div>Teen drivers continue to be disproportionately involved in motor vehicle crashes, raising concerns despite the presence of structured licensing systems and safety education programs. This study investigates teen drivers' perceptions of crash risks, driving behaviors, and overall safety awareness using a mixed-methods approach. This study uses a mixed-methods survey of 120 teen drivers (18–19 years old) in Michigan to investigate their perceptions of crash risks and driving behaviors. Quantitative results indicate that while seatbelt compliance is high, engagement in high-risk behaviors, specifically speeding, nighttime driving, and cellphone use, remains common. Qualitative findings offer a nuanced view of peer influence, with respondents describing peers as both sources of distraction and support. Furthermore, participants identified gaps in current driver education, calling for more interactive, hands-on training in adverse conditions. By centering teen perspectives, these findings provide a data-driven basis for tailoring safety interventions to the real-world experiences of novice drivers. This research underscores the potential value of incorporating teen-informed insights into the development of more effective traffic safety programs.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"122 ","pages":"Article 103754"},"PeriodicalIF":5.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148638990","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":"Reliability generalization of the alpha coefficient: the driving cognitions questionnaire meta-analysis","authors":"Wahyu Syahputra,&nbsp;Bahrul Hayat,&nbsp;Muhammad Dwirifqi Kharisma Putra,&nbsp;Rezky Eka Wardana","doi":"10.1016/j.trf.2026.103736","DOIUrl":"10.1016/j.trf.2026.103736","url":null,"abstract":"<div><div>Anxiety and fear while driving contribute to risky driving behavior and involvement in traffic accidents. The Driving Cognitions Questionnaire (DCQ) is widely used to measure maladaptive cognitions related to driving anxiety, but there has been no systematic synthesis of its reliability across studies. This study aims to evaluate the internal reliability of the DCQ using the reliability generalization (RG) approach. A meta-analysis was conducted on Cronbach's alpha coefficients for the three DCQ subscales (Panic, Accident, and Social). The literature search followed the PRISMA guidelines, and the analysis was conducted according to the REGEMA guidelines. A total of 16 independent studies were analyzed using a random effects model, with alpha transformation using the Bonett approach. Heterogeneity, publication bias, and meta-regression analyses were performed to test for variations in reliability between studies. The results show that the population reliability estimates are in the good to very good category, with alphas of 0.884 (Panic), 0.870 (Accident), and 0.854 (Social). Very high levels of heterogeneity were found in all subscales (I² &gt; 90%). Meta-regression identified age and male gender proportion as significant moderators on the Social subscale, while no significant moderators were found on the Panic and Accident subscales. These findings indicate that the DCQ is a reliable instrument at the population level, but its reliability is contextual. This study emphasizes the importance of reporting reliability based on cumulative evidence in traffic psychology research.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"122 ","pages":"Article 103736"},"PeriodicalIF":5.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148638946","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":"Development of an assessment method to identify high-risk elderly drivers based on driving performance evaluation","authors":"Sooncheon Hwang,&nbsp;Daewon Kim,&nbsp;Dongmin Lee","doi":"10.1016/j.trf.2026.103735","DOIUrl":"10.1016/j.trf.2026.103735","url":null,"abstract":"<div><div>This study proposes a multidimensional screening framework based on visual and cognitive assessments to manage high-risk drivers—a critical traffic safety issue in an increasingly aging society. Visual and cognitive abilities were evaluated in 62 participants (aged 26 to 82), while concurrent vehicle-based experiments were conducted using a functional driving test. Cluster analysis revealed that the group with the lowest visual and cognitive performance exhibited the most unstable driving behavior on average. These findings suggest that comprehensive visual-cognitive assessments can serve as a policy tool for identifying high-risk drivers and prioritizing them for in-depth driving proficiency evaluations. Furthermore, this study demonstrates the necessity of implementing systematic screening procedures that integrate both visual-cognitive tests and on-road driving assessments within a driver's license policy. The significance of this research lies in its contribution to establishing a methodological foundation for the systematic management of high-risk drivers.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"122 ","pages":"Article 103735"},"PeriodicalIF":5.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148732140","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":"Bridging the supervision gap: Technology-mediated mentorship to increase accompanied driving and moderate novice driver stress","authors":"Anat Goldstein,&nbsp;Mordechai Ollech,&nbsp;Oren Musicant","doi":"10.1016/j.trf.2026.103781","DOIUrl":"10.1016/j.trf.2026.103781","url":null,"abstract":"<div><div>Novice drivers (NDs) face significantly elevated crash risks during their initial months of independent driving, often due to limited hazard perception and situational awareness. While Graduated Driver Licensing (GDL) systems utilize parental supervision to bridge this gap, the conventional model is constrained by parental availability and interpersonal tension. This study presents a two-stage investigation into technology-mediated mentorship as a transformative solution: remote parental accompaniment and AI-driven avatar accompaniment. Using a high-fidelity driving simulator, 43 parent-ND dyads were exposed to safety-critical “challenging events”, including sudden pedestrian crossings, lead-vehicle braking, and amber light decision points, that are too hazardous for real-world testing.</div><div>The investigation assessed subjective experiences (usability, safety, tension), physiological stress indices (heart rate variability), and driving performance across three conditions: conventional in-person, remote, and avatar-based accompaniment. Results revealed that both technology-mediated conditions achieved usefulness ratings comparable to those of conventional accompaniment, while significantly reducing peak stress levels during challenging driving moments. Furthermore, at high steering intensity thresholds, technology-mediated guidance was associated with lower event probabilities compared to traditional supervision. These findings validate the potential of alternative mentorship models to enhance the GDL process. Furthermore, this study establishes the empirical foundation and a four-module architecture (integrating perception, guidance, style, and conversation) required for the development of a fully autonomous, empathetic Generative AI driving mentor.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"122 ","pages":"Article 103781"},"PeriodicalIF":5.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148771879","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":"Do scooters obstruct access—or attention? Perceptions of sidewalk conflicts and overlooked causes of obstruction","authors":"Anne Brown,&nbsp;Kelcie Ralph,&nbsp;Nicholas J. Klein,&nbsp;Calvin Thigpen","doi":"10.1016/j.trf.2026.103792","DOIUrl":"10.1016/j.trf.2026.103792","url":null,"abstract":"<div><div>Shared e-scooters have drawn scrutiny from the public and policymakers due to their potential to block sidewalk access, an issue especially salient for people with disabilities. Yet scooters are only one of many sidewalk obstructions. How often do people see misparked scooters—and how annoyed are they—relative to other sidewalk objects like parked bikes, signs, and cars? To answer this question, we administered an online survey to 2347 US adults and asked respondents to rate the frequency and annoyance of various obstructions on a 0–10 scale. Respondents say signs and automobiles block sidewalks more frequently than scooters (mean score of 3.7 and 3.8 vs. 2.6). Car obstructions are seen as more annoying than scooters on average (6.5 vs. 5.2) but signs are seen as less annoying (3.7 vs. 5.2). And as sidewalks narrow, people become substantially more annoyed with all types of sidewalk obstructions. People with and without mobility disabilities are equally annoyed by sidewalk obstructions, but the former report encountering them more often.</div><div>We find broad public support for policies to manage scooter parking, with more support among people with mobility disabilities. Findings suggest that while people support managing scooters, focusing policy and planning efforts on only scooters distracts from broader sidewalk accessibility issues including more common sidewalk obstructions and narrow sidewalks that intensify conflict.</div></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"122 ","pages":"Article 103792"},"PeriodicalIF":5.0,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148844575","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}