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

{"title":"The Impact of Pedestrian Interactions in Intersections on the Three Levels of Drivers’ Situation Awareness","authors":"Sami Park ,&nbsp;Yilun Xing ,&nbsp;Kumar Akash ,&nbsp;Teruhisa Misu ,&nbsp;Shashank Mehrotra ,&nbsp;Linda Ng Boyle","doi":"10.1016/j.trf.2024.08.023","DOIUrl":"10.1016/j.trf.2024.08.023","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 167-180"},"PeriodicalIF":3.5,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142149981","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":"How long the effect of take-over conditions Lasts? a survival analysis of Commercial Motor vehicle drivers’ reaction time and driving behavior in Level 4 of automated vehicles","authors":"Ali Riahi Samani,&nbsp;Sabyasachee Mishra","doi":"10.1016/j.trf.2024.08.033","DOIUrl":"10.1016/j.trf.2024.08.033","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 149-166"},"PeriodicalIF":3.5,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142149955","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":"What limits improper bike-sharing parking most: Penalties or incentives? Findings from an online behavioral experiment","authors":"Hongyun Si ,&nbsp;Jiaxuan Liang ,&nbsp;Jintao Ke ,&nbsp;Long Cheng ,&nbsp;Jonas De Vos","doi":"10.1016/j.trf.2024.09.001","DOIUrl":"10.1016/j.trf.2024.09.001","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 133-148"},"PeriodicalIF":3.5,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142149954","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":"Predictability of driver’s stop/go decisions at flashing-light-controlled grade crossings by coupling functional brain network and deep learning methods","authors":"Siwei Ma ,&nbsp;Yingnan Yan ,&nbsp;Jianqiang Wang ,&nbsp;Deqi Chen ,&nbsp;Jingsi Yang ,&nbsp;Xiaobing Liu","doi":"10.1016/j.trf.2024.08.031","DOIUrl":"10.1016/j.trf.2024.08.031","url":null,"abstract":"<div><p>Detecting and predicting the stop/go decisions of drivers at grade crossings is crucial for enhancing road safety. Electroencephalography (EEG) data, which provides direct and effective physiological indicators for recognizing driver states, combined with associated machine-learning techniques, can be used to monitor driver decisions. However, the ability of EEG to predict a driver’s stop/go decisions remains unclear. To investigate this, we collected both EEG and behavioral data from drivers at a flashing-light-controlled grade crossing, where stop/go decisions are critical, using a driving simulator. Herein, we propose an EEG-based prediction framework that combines functional brain network analysis with conventional neural networks (FBN-CNNs) to predict drivers’ stop/go decisions. The functional brain network was measured using phase-lag index matrices and minimum-spanning tree techniques. We subsequently compared the obtained results of the FBN-CNN with those from traditional machine learning methods, specifically random forest (RF) and Support Vector Machines (SVM). The results indicate that when facing a flashing red light, drivers who decide to stop exhibit stronger alpha band connectivity and weaker delta and theta activity than those who run the red-light. Furthermore, the FBN-CNN model outperformed the machine learning methods (RF and SVM) in both extracting EEG features and achieving high prediction accuracy. Interestingly, the EEGs of drivers during normal driving stages could help to predict their stop-or-go behavior at the onset of a flashing red light. In the typical dilemma zone, combining EEG data from the normal driving stage with those from the pre-decision stage improved the accuracy from 76% to 90%. These findings demonstrate the efficacy of EEG and deep learning methods in driver decision monitoring.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 115-132"},"PeriodicalIF":3.5,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142135952","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 the situational dynamics of visual information sampling in lateral vehicle control – Subjective vs. objective estimates of spare visual capacity","authors":"Hilkka Grahn ,&nbsp;Tuomo Kujala ,&nbsp;Toni Hautaoja ,&nbsp;Dario D. Salvucci","doi":"10.1016/j.trf.2024.08.034","DOIUrl":"10.1016/j.trf.2024.08.034","url":null,"abstract":"<div><p>Drivers continually adapt their information sampling behavior to changing traffic conditions for safe driving. Scientists have studied this sampling behavior for decades; however, the literature on how drivers adapt their visual information sampling in response to observed driving dynamics is still incomplete, especially concerning what might be considered safe adaptation from an external perspective. While occlusion methods are commonly employed to study drivers’ visual information sampling, the variability in self-selected occlusion times and their relationship to actual driving performance has yet to be fully understood. In a driving simulator study with 30 participants, we analyzed and compared the situational dynamics influencing visual information sampling and performance in an occluded lane-keeping task. The findings underscore the significant influence of speed, lane position, time-to-line-crossing at the start of occlusion, and steering during occlusion on spare visual capacity in lane-keeping. Although the participants were able to make slight adjustments to their visual sampling based on these variables, their occlusion time choices appeared to be stable and primarily driven by individual preferences, unrelated to their driving experience or general lateral control instability under occlusion. In contrast, drivers’ general instability in lateral control under single-occlusion driving emerged as the strongest predictor of lane crossing during continuous, intermittently occluded driving. These insights contribute to the understanding of information sampling dynamics and spare visual capacity in lateral vehicle control, potentially guiding the development of personalized and contextually intelligent driver attention monitoring and warning systems.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 98-114"},"PeriodicalIF":3.5,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1369847824002419/pdfft?md5=25e886016aed5e8432bf634e18461e74&pid=1-s2.0-S1369847824002419-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142135951","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":"Characterizing the driving behavior of manual vehicles following autonomous vehicles and its impact on mixed traffic performance","authors":"Young Jo ,&nbsp;Aram Jung ,&nbsp;Cheol Oh ,&nbsp;Jaehong Park","doi":"10.1016/j.trf.2024.08.028","DOIUrl":"10.1016/j.trf.2024.08.028","url":null,"abstract":"<div><p>An important issue for mixed traffic conditions, in which autonomous vehicles (AVs) and manual vehicles (MVs) coexist, is to analyze various vehicle interactions caused by different driving behaviors. Understanding the responsive behavioral characteristics of the following MV affected by the maneuver of the leading AV is a backbone in evaluating mixed traffic performance. The purpose of this study is to characterize the driving behavior of MVs following AVs in mixed-traffic situations. To characterize vehicle interactions between AVs and MVs, this study conducts multi-agent driving simulation (MADS) experiments, which can synchronize the space and time domains on the road by connecting two driving simulators. A maneuvering control logic for AV driving, which is used for MADS, is developed in this study. The driving behavioral data of MVs following AVs obtained from MADS are used to modify the parameters associated with the intelligent driver model (IDM). The IDM is a microscopic car-following model to represent the longitudinal following behavior of vehicles. This study identifies how the MV following AV would be different from the case where the MV follows MV. The results show that the average time headway of the following MVs in the AV-MV pair increased by 13.9% compared to the MV-MV pair. However, the maximum acceleration and average deceleration decreased by 44.45% and 4.89%, respectively. The proposed IDM for MV following AV was further plugged into a microscopic traffic simulation platform. VISSIM simulations were conducted to identify the difference in driving behavior between the proposed IDM and the original IDM. The outcome of this study is expected to simulate the maneuvering behavior of MV more realistically in the mixed traffic stream.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 69-83"},"PeriodicalIF":3.5,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142122062","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":"Using distributed simulations to investigate driver-pedestrian interactions and kinematic cues: Implications for automated vehicle behaviour and communication","authors":"Yue Yang ,&nbsp;Yee Mun Lee ,&nbsp;Amir Hossein Kalantari ,&nbsp;Jorge Garcia de Pedro ,&nbsp;Anthony Horrobin ,&nbsp;Michael Daly ,&nbsp;Albert Solernou ,&nbsp;Christopher Holmes ,&nbsp;Gustav Markkula ,&nbsp;Natasha Merat","doi":"10.1016/j.trf.2024.08.027","DOIUrl":"10.1016/j.trf.2024.08.027","url":null,"abstract":"<div><p>As we move towards a future with Automated Vehicles (AVs) incorporated in the current traffic system, it is crucial to understand driver-pedestrian interaction, in order to enhance AV design and optimization. Previous research in this area, which has primarily used naturalistic observations or single-actor virtual reality simulations, has been limited by its inability to draw causal conclusions, also due to a lack of real human–human interactions. Our study addresses these limitations by employing a high-fidelity distributed simulation setup that links drivers in a motion-based simulator with pedestrians in a CAVE-based environment. This method allows for the examination of real-time and reciprocal interactions across a range of road-crossing scenarios. Using thirty-two pairs of drivers and pedestrians, we investigated how different factors, such as the presence of zebra crossings and varying time gaps of the approaching vehicle, influence driver behaviour and pedestrian crossing decisions. The effect of drivers’ control of the vehicle during such crossings (e.g., braking behaviour and lateral deviation) on pedestrians’ crossing decisions were also analysed. We found that the distribution of drivers’ average deceleration values were bimodal, where drivers either markedly yielded to pedestrians, or continued in their path, with very few instances of intermediate behaviour. We also found that pedestrian decisions were seemingly influenced by the different braking strategies adopted by the driver, with pedestrians crossing before the vehicles in response to soft and early, or late and hard braking, while late and soft braking often resulted in the vehicle passing first. We also observed a slight lateral movement of the vehicle away from pedestrians when drivers were not yielding, but more of a lateral deviation towards them when yielding. This may be because drivers subconsciously transfer their walking interaction habits to their driving behaviour, to avoid a collision with pedestrians. Finally, our results showed a stronger influence of these kinematic cues on pedestrian crossing decisions, when compared to zebra crossings. As well as highlighting the value of a novel approach for investigating vehicle–pedestrian interactions, this study illustrates how vehicle cues can assist pedestrian decisions, adding new knowledge in the development of human-like behaviour for future AVs.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 84-97"},"PeriodicalIF":3.5,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1369847824002341/pdfft?md5=3556bd963730d2fe523bb74942ee37d1&pid=1-s2.0-S1369847824002341-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142122063","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":"Eye tracking measures of bicyclists’ behavior and perception: A systematic review","authors":"Shiyu Ma,&nbsp;Wenwen Zhang,&nbsp;Robert B. Noland,&nbsp;Clinton J. Andrews","doi":"10.1016/j.trf.2024.08.026","DOIUrl":"10.1016/j.trf.2024.08.026","url":null,"abstract":"<div><p>With improved portability and affordability, eye tracking devices have facilitated an expanding range of cycling experiments aimed at understanding cycling behavior and potential risks. Given the complexity of cyclists’ visual behavior and gaze measurements, we provide a comprehensive review with three key focuses: 1) the adoption and interpretation of various gaze metrics derived from cycling experiments, 2) a summary of the findings of those experiments, and 3) identifying areas for future research. A systematic review of three databases yielded thirty-five articles that met our inclusion criteria. Our review results show that cycling experiments with eye tracking allow analysis of the viewpoint of the cyclist and reactions to the built environment, road conditions, navigation behavior, and mental workload and/or stress levels. Our review suggests substantial variation in research objectives and the consequent selection of eye-tracking devices, experimental design, and which gaze metrics are used and interpreted. A variety of general gaze metrics and gaze measurements related to Areas of Interest (AOI) are applied to infer cyclists’ mental workload/stress levels and attention allocation respectively. The diversity of gaze metrics reported in the literature makes cross-study comparisons difficult. Areas for future research, especially potential integration with computer vision are also discussed.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 52-68"},"PeriodicalIF":3.5,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S136984782400233X/pdfft?md5=29db3bc011d61c69670416cd89c796be&pid=1-s2.0-S136984782400233X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142122061","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":"Therapists’ perspectives on experience and treatment of mobility-related anxiety disorders","authors":"Christian Ratering ,&nbsp;Rob van der Heijden ,&nbsp;Karel Martens","doi":"10.1016/j.trf.2024.08.022","DOIUrl":"10.1016/j.trf.2024.08.022","url":null,"abstract":"<div><p>In this paper, we explore how psychology professionals understand and treat the mobility issues of people diagnosed with anxiety disorder, based on 13 in-depth interviews. All interviewees regularly treat clients facing challenges using various modes of transportation due to anxiety disorders. Their clients exhibit a range of mobility issues, with some struggling with driving or being a passenger in a car, while others encounter difficulties when using public transport, cycling, or being a pedestrian. The mobility problems their clients experience affect their daily lives. Next to applying individual Cognitive Behavioral Therapy (CBT) adopted by most interviewees, they also suggest that adjustments in the mobility system could assist individuals with anxiety disorders to participate more fully in society. Hence, we advocate for more research on the mobility system that integrates psychological perspectives on mobility-related problems caused by anxiety disorder to support a more inclusive mobility planning, design, and organization of the system. Inclusive planning implies (1) designing mainstream infrastructures and services enabling people with anxiety disorders to move around independently while reducing anxiety-triggering situations without them becoming disclosed; (2) enhancing walkability and cyclability through both transport and land use planning, since having destinations within a short distance from home seems to be especially beneficial for people with anxiety disorders.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 39-51"},"PeriodicalIF":3.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1369847824002298/pdfft?md5=db841cca980128e7d8ab9a78a9eac7f7&pid=1-s2.0-S1369847824002298-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142117732","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":"Effects of hazard type on the hazard perceptions of violation-involved and violation-free drivers: An ERP study","authors":"Long Sun ,&nbsp;Shilong Yu ,&nbsp;Yuxi Wang ,&nbsp;Shan Liang,&nbsp;Liang Cheng","doi":"10.1016/j.trf.2024.08.025","DOIUrl":"10.1016/j.trf.2024.08.025","url":null,"abstract":"<div><h3>Objective</h3><p>Hazard perception, which is closely related to crash risk, is the ability to anticipate potential dangers on the road. This study aimed to investigate the effects of drivers’ previous traffic violation history on their neural processing of hazard perception under different hazard types.</p></div><div><h3>Methods</h3><p>A mixed experimental design was employed, involving two groups of drivers (driver group: violation-involved, violation-free) and three types of images (no-hazard image, covert hazard image, overt hazard image). Twenty covert hazard images, 20 overt hazard images and 40 no-hazard images were randomly presented to 19 drivers with previous violation histories and 28 drivers without violations. The participants were asked to detect whether there was a hazardous situation in the images and press the keyboard quickly after detecting one. Response time, response accuracy and changes in the N1 (100–140 ms), N2 (250–300 ms) and P300 (300–400 ms) components of event-related potentials (ERP) were obtained and analysed.</p></div><div><h3>Results</h3><p>The response time to the covert hazard images was significantly greater than that to the no-hazard and overt hazard images, and the lower accuracy also revealed that the covert hazard images were harder to detect than the no-hazard and overt hazard images. Under both overt and covert hazard images, the response time of violation-involved drivers was longer, and their accuracy was worse than that of violation-free drivers. The N1 latency of violation-involved drivers was significantly longer than that of violation-free drivers. The amplitude of N2 was significantly larger in the no-hazard image than in the covert and overt hazard images. The P300 amplitude was significantly greater in the overt hazard images than in the covert and no-hazard images.</p></div><div><h3>Conclusion</h3><p>Violation-involved drivers have poorer hazard perception abilities than violation-free drivers regardless of hazard type. N1 latency can differ from that of drivers with and without previous violations. These findings provide support for the development of hazard perception training systems for drivers who are prone to traffic violations.</p></div>","PeriodicalId":48355,"journal":{"name":"Transportation Research Part F-Traffic Psychology and Behaviour","volume":"107 ","pages":"Pages 29-38"},"PeriodicalIF":3.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142099256","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}