Traffic Injury Prevention最新文献

{"title":"Methods for assessing submarining occurrence in PMHS frontal sled tests: Exploring potential indicators.","authors":"Karthik Somasundaram, Klaus Driesslein, Anjishnu Banerjee, Frank A Pintar","doi":"10.1080/15389588.2025.2542973","DOIUrl":"https://doi.org/10.1080/15389588.2025.2542973","url":null,"abstract":"<p><strong>Objective: </strong>Assessment of submarining occurrence in PMHS (Post-Mortem Human Subject) testing can be challenging, particularly for obese PMHS. This study investigates varied kinetic and kinematic response parameters as potential indicators of submarining. Data from 36 whole-body PMHS frontal sled tests conducted under varying boundary conditions were analyzed, incorporating three spring-controlled seat configurations, two extreme anthropometric profiles, two crash pulses, and two seatback angles.</p><p><strong>Methods: </strong>Submarining assessment was based on seven response parameters: (1) Visual inspection of video, (2) Lap belt load trace morphology, (3) Pelvis rotational displacement, (4) Iliac bone fracture, (5) Torso-knee angle, (6) Hip-forward displacement, and (7) Anti-submarining plate deflection. High-speed video evaluations were independently performed by two authors and an expert from injury biomechanics field, with inter-observer agreement quantified using the Kappa statistic. A logistic regression model was developed to estimate submarining probability based on alternative indicators, using cases where inter-observer agreement confirmed submarining or its absence. A bootstrap technique with stepwise covariate selection identified the most significant indicators for the final model.</p><p><strong>Results: </strong>Among the 36 tests, the final inter-observer agreement for cases with definitive conclusions was 98.5%, with a Kappa score of 0.95. Based on these analyses, 33 out of 36 cases were used for training the statistical model. The stepwise logistic regression model identified lap belt load trace morphology, pelvis rotational displacement, and torso-knee angle as the most significant indicators, forming the basis of the final submarining predictive equation. When final model was applied to all cases, the tests involving a soft spring seat exhibited the highest submarining probability (33%), while a reclined (45°) seatback position accounted for 21% of submarining cases. Among subject profiles, small females showed the highest likelihood of submarining (23%), whereas obese subjects exhibited a comparatively lower likelihood (11%).</p><p><strong>Conclusion: </strong>This study explored varied kinetic and kinematics indicators for assessing submarining occurrence in frontal PMHS sled tests and developed statistical regression model to predict the occurrence of submarining. Softer spring seat, small female anthropometry, and reclined configurations had higher probability of submarining. These findings may help guide future biomechanics research by highlighting relevant indicators and extrinsic factors that influence submarining. For the modeling community, the probabilistic framework and identified predictors offer inputs for refining computational human body models and enhancing the fidelity of injury prediction in diverse occupant scenarios.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-11"},"PeriodicalIF":1.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145034647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coupling mechanism of nighttime lighting glare and driver cognitive load based on visual-physiological parameters.","authors":"Mingwei Xu, Chengliu Yu, Ke Wang, Yutong Liu, Shangxue Yang, Guanlin Liu, Guantao Wang, Zhiqiang Hou","doi":"10.1080/15389588.2025.2542539","DOIUrl":"https://doi.org/10.1080/15389588.2025.2542539","url":null,"abstract":"<p><strong>Objective: </strong>To clarify the potential risks and causative mechanisms of glare from nighttime road fill lights on driving safety, this study investigates the dual interference of glare-induced visual cognitive load and physiological stress.</p><p><strong>Methods: </strong>A field driving experiment involving 20 drivers was conducted, with real-time collection of visual data (e.g., pupil variability coefficient, fixation area distribution) <i>via</i> portable eye trackers and synchronized monitoring of heart rate variability (HRV) indicators.</p><p><strong>Results: </strong>Excessive illuminance or rapid flickering of fill lights significantly increased pupil area variability coefficient (mean ± SD: 1.25 ± 0.43 vs. 0.68 ± 0.21, <i>p</i> < 0.01) and local blind spot probability by 23%. Concurrently, RMSSD (parasympathetic activity) decreased by 18.7%, and LF (sympathovagal balance) dropped by 31.2%, indicating aggravated psychological load and neural imbalance.</p><p><strong>Conclusion: </strong>Nighttime driving safety model integrating visual-physiological parameters was proposed, enabling dynamic glare risk intervention through threshold monitoring and adaptive lighting strategies. The findings provide scientific foundations for optimizing road lighting design, establishing fill light technical standards, and developing in-vehicle human-machine interaction warning systems.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-10"},"PeriodicalIF":1.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145034699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Speed control, visual adaptation, and mental workload in urban short underpass tunnels: A naturalistic driving study.","authors":"Jialin Mei, Shoushuo Wang, Shiming He, Zhigang Du, Fangtong Jiao","doi":"10.1080/15389588.2025.2543500","DOIUrl":"https://doi.org/10.1080/15389588.2025.2543500","url":null,"abstract":"<p><strong>Objective: </strong>Urban short underpass tunnels, characterized by steep longitudinal slopes, limited lengths, and abrupt light transitions, pose significant driving risks. This study aims to comprehensively investigate drivers' speed control behavior, visual adaptation processes, and mental workload mechanisms within such tunnels under real traffic conditions.</p><p><strong>Methods: </strong>A real-vehicle experiment was conducted involving 35 drivers. Data on speed, acceleration, pupil area, and heart rate were collected. The experimental road segment was divided into five sections: entry, downhill, tunnel, uphill, and departure, to analyze driving behavior characteristics and psychophysiological responses systematically.</p><p><strong>Results: </strong>Speed increased significantly in the downhill section and decreased notably in the uphill and departure sections. The tunnel section exhibited a high incidence of speeding, while the uphill section showed the most significant speed variability, both identified as high-risk zones for rear-end collisions. Regarding visual adaptation, drivers entered a dark adaptation ∼70 m before reaching the tunnel entrance, marked by a gradual increase in pupil area. Around 50 m before the tunnel exit, drivers transitioned to light adaptation, and the pupil area decreased rapidly. Mental workload analysis revealed that drivers' heart rates increased during the downhill section, peaked shortly after entering the tunnel, and gradually declined as light adaptation began. Further analysis showed that acceleration was negatively correlated with heart rate growth rate (HRG), while pupil area change rate (PAC) and vehicle speed positively correlated with HRG.</p><p><strong>Conclusion: </strong>This study reveals that speed behavior, visual adaptation, and mental workload in urban short underpass tunnels vary significantly across road sections, with the tunnel and uphill sections posing the highest risk for rear-end collisions, highlighting the need for targeted tunnel design and traffic safety measures.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-9"},"PeriodicalIF":1.9,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145006874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 spatiotemporal traffic dynamics toward conflict risk levels using trajectory data in heterogeneous traffic conditions.","authors":"Vineet Jain, Ashish Dhamaniya","doi":"10.1080/15389588.2025.2541269","DOIUrl":"https://doi.org/10.1080/15389588.2025.2541269","url":null,"abstract":"<p><strong>Objective: </strong>This study aimed to identify dynamic spatiotemporal traffic factors influencing conflict risk levels on National Highways under heterogeneous traffic conditions in India. The research addresses gaps by capturing vehicle interactions using high-resolution UAV-based trajectory data and proposes a novel two-stage methodology for real-time conflict risk evaluation, moving beyond traditional binary risk classifications to a four-level framework (High, Moderate, Low, No-Risk).</p><p><strong>Methods: </strong>Over 40,000 conflict risk sequences were classified into four severity levels using the Modified Time-to-Collision (MTTC) surrogate safety measure. Lane-specific spatiotemporal variables including vehicle dynamics (speed and acceleration variability, traffic flow, traffic density, proportion of heavy vehicles, and lane-change frequency) were systematically extracted up to five seconds preceding each conflict event, resulting in a comprehensive dataset of 65 variables. In the first stage, influential variables were identified using an aggregated normalized feature importance analysis from Random Forest, XGBoost, and LightGBM models. The second stage employed an ordered probit model to statistically evaluate the causal impact of selected critical variables on the categorized risk levels.</p><p><strong>Results: </strong>Incremental feature importance analyses revealed that immediate vehicle dynamics, particularly speed and acceleration variability within one second before the event, were the strongest predictors of conflict risk. Variables such as lane-change frequency and adjacent-lane traffic flow became influential over the broader five-second timeframe. The ordered probit model further quantified these relationships: each unit increase in speed variability and lane-change frequency elevated the high-risk probability by approximately 10%, whereas higher traffic density significantly reduced high-risk probability. A one-unit increase in traffic flow within adjacent lanes was associated with a 3.6% reduction in the likelihood of high-risk events, suggesting spatial interaction effects on safety.</p><p><strong>Conclusions: </strong>The study introduces a robust methodological approach that combined advanced machine learning and statistical modeling to understand complex spatiotemporal dynamics influencing traffic conflict risks under mixed traffic conditions. By capturing these interactions at fine resolution and demonstrating their impact on conflict severity, this research offers significant implications for developing real-time risk-alert systems. Such systems can proactively warn drivers, enabling safer and more informed driving decisions, and thus enhancing overall highway safety in heterogeneous traffic environments.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-10"},"PeriodicalIF":1.9,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145006893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Relationship with sex-based anatomical differences to lower extremity injury severity in frontal crashes.","authors":"Thomas Hartka, Pavel Chernyavskiy, Colleen Mullins, Joseph Ash, George Glass, Carl Greg Shaw","doi":"10.1080/15389588.2025.2541296","DOIUrl":"https://doi.org/10.1080/15389588.2025.2541296","url":null,"abstract":"<p><strong>Objective: </strong>Multiple studies have demonstrated an increased risk of lower extremity injuries for females in frontal crashes. This study aimed to investigate whether sex-based anatomical differences, as measured on computed tomography (CT) scans of the abdomen and pelvis, contribute to lower extremity injury risk.</p><p><strong>Methods: </strong>The Crash Injury Research and Engineering Network (CIREN) database (2017-2023) was queried for frontal collisions. Cases were included if the occupant was an adult (≥18 years), seated in the front row, properly restrained, and had an analyzable CT scan of the abdomen and pelvis. Anatomical measurements included soft tissue over the anterior superior iliac spine (ASIS) along three vectors, thigh diameter, thigh anterior soft tissue, subcutaneous adipose tissue (SAT) area, psoas area, lumbar spine bone mineral density (BMD), femur cortical thickness, height, weight, and body mass index (BMI). Ordinal regression analysis was employed to examine the individual associations between these measurements and the highest Abbreviated Injury Scale (AIS) injury severity of the lower extremities, after adjusting for age, change in velocity (delta-V), knee bolster intrusion, toe pan intrusion, seat track position, airbag deployment, and sex. The same analysis was repeated for the highest AIS injury severity in the hip-thigh-knee and the lower leg regions.</p><p><strong>Results: </strong>A total of 195 occupants were included, of which 114 (58%) were female. Among the anatomical measurements from the computed tomography (CT) scans, significant differences between the sexes were observed only in the SAT and psoas areas, with the SAT area being higher in females and the psoas area being higher in males. Ordinal regression analysis revealed that SAT area, weight, and BMI were significantly associated with the severity of lower extremity injuries. These three variables were also significantly associated with hip-thigh-knee injuries but not with injuries to the lower leg. Further analysis indicated that SAT area is a significant mediator of the effect of sex on lower extremity injury severity.</p><p><strong>Conclusions: </strong>The area of subcutaneous tissue at the level of the ASIS was significantly associated with increased severity of lower extremity injuries, especially in the hip-thigh-knee region. This measurement was higher in females and may account for some of the observed differences in injury risk between sexes.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-7"},"PeriodicalIF":1.9,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145006888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From extraversion to psychopathy: Personality predictors of drink-driving.","authors":"Renan P Monteiro, Phillip Dyamond Gomes da Silva, Carlos Eduardo Pimentel, Gabriel Lins de Holanda Coelho, Thiago Marques de Brito","doi":"10.1080/15389588.2025.2544212","DOIUrl":"https://doi.org/10.1080/15389588.2025.2544212","url":null,"abstract":"<p><strong>Objective: </strong>The present study examined the predictive role of ten personality traits (i.e., Five Factor Model, Dark Triad, impulsivity, and sensation seeking) in the history of drink-driving and investigated the mediating role of this behavior in the relationship between personality traits and aberrant driving behaviors, such as traffic fines and accidents.</p><p><strong>Methods: </strong>Participants were 303 individuals from the general population, with ages ranging from 18 to 77 years (<i>M</i> = 35.4; <i>SD</i> = 11.96). The sample consisted predominantly of women (53.1%), individuals with average income levels (52.1%), and drivers who had held a license for more than 10 years (50.2%). Participants completed self-report instruments assessing the frequency of driving under the influence of alcohol, as well as measures of personality traits. Data were analyzed using Pearson correlations to examine general patterns of association among variables, multiple linear regression to identify predictors of drink-driving, and structural equation modeling to test the contextual mediated model.</p><p><strong>Results: </strong>The findings revealed that openness, extraversion, psychopathy, and sensation seeking were significant predictors of drink-driving. Moreover, these traits indirectly influenced aberrant driving behaviors, while drink-driving itself emerged as a direct predictor of such behaviors.</p><p><strong>Conclusion: </strong>This research replicates and extends previous studies by demonstrating both direct and indirect effects of various personality traits on problematic traffic behaviors (including drink-driving, traffic fines, and accident involvement). The findings underscore the importance of assessing personality traits in the context of driver licensing processes.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-7"},"PeriodicalIF":1.9,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 effects of methamphetamine on driving performance and behavior: A thematic linking of consumption patterns and cognitive-behavioral outcomes from in-depth interviews with methamphetamine users.","authors":"Steven Love, Bevan Rowland","doi":"10.1080/15389588.2025.2541902","DOIUrl":"https://doi.org/10.1080/15389588.2025.2541902","url":null,"abstract":"<p><strong>Objective: </strong>This study sought to investigate the thematic links between <i>methamphetamine</i> (MA) users' consumption patterns; their perceptions about the effects that MA has on their thoughts, feelings, and behavior; and their tendency to drive following MA consumption.</p><p><strong>Methods: </strong>Seventeen MA users were recruited through a combination of social media advertising and third-party outreach. Participants completed a semi-structured interview lasting approximately 30 min. Interview data were analyzed using thematic analysis to identify key patterns undermining impaired driving behavior.</p><p><strong>Results: </strong>An overarching theme revealed that participants' beliefs about MA use and their tendency to drive while intoxicated were largely dependent on their history and patterns of MA use. Three primary profiles of MA users were identified: (a) sporadic users, who used \"speed\" infrequently and in the context of social situations; (b) progressed users, who described similar initial patterns but had progressed to frequent use of more potent \"crystal\" MA and displayed characteristics of substance dependency; and (c) regressed users, who acknowledged a previous history of problematic use, but had since reduced their use patterns significantly. Where sporadic users tended to perceive MA as detrimental to their attention and behavior on the road, progressed users commonly believed that MA positively influenced their driving. However, it was typically acknowledged among all users that regardless of intoxication, extended MA use could lead to significant driving risk due to the severe cognitive (erratic thinking) and behavioral (aggression) symptoms associated with fatigue and the 'come down' of MA. Finally, the analysis showed that the tendency to drive while intoxicated was contextual to participants' beliefs about the associated cognitive-behavioral outcomes of MA use.</p><p><strong>Conclusions: </strong>The findings highlight how MA use patterns and perceptions contribute to impaired driving behaviors. These insights can inform the development of more targeted interventions addressing the interconnected issues of substance dependence and drug-impaired driving.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-9"},"PeriodicalIF":1.9,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Injury patterns and safety implications for electric bikes compared to mopeds in the United States.","authors":"Elise Atkinson, Theresa Atkinson","doi":"10.1080/15389588.2025.2543497","DOIUrl":"https://doi.org/10.1080/15389588.2025.2543497","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;Electric bikes (e-bikes) are increasingly popular in the United States, with studies documenting increased injuries associated with their use. U.S. laws vary widely with licensure required in only 7 states, age restriction and helmet use varying by bike class in 35. This differs from the stricter regulations applied to higher-speed vehicles like mopeds. This study examines numbers of injuries and characteristics of serious injury events, comparing e-bikes to the more regulated moped.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Emergency department data from 2019 to 2023 was extracted from the U.S. Consumer Product Safety Commission's National Electronic Injury Surveillance System. Event narratives were parsed using text search algorithms to classify cases into e-bike and moped groups. Frequency, rider age, involvement of motor vehicles, drugs/alcohol use, and pedestrian involvement were examined. Regression analyses were conducted using R. Rao-Scott Pearson Chi-Square tests were used to compare case characteristics between vehicle types.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;E-bikes accounted for 28.2% of the weighted 268,828 two-wheeled vehicle injury cases, with mopeds at 53.3%. E-bike injury case counts significantly increased with 7948 additional cases/year (&lt;i&gt;r&lt;/i&gt;&lt;sup&gt;2&lt;/sup&gt; = 0.96), significantly outpacing increases in moped injury counts. For both, head injuries were most common, however, helmet use/non-use documentation in the data set was low (37.9% for e-bike and 38.9% for moped) limiting assessment. Counts of e-bike injury in the 13-19 year age group showed rapid increase, becoming the second greatest frequency age group by 2023. More serious e-bike injuries also significantly increased. Drug (2.2%) and alcohol involvement (7.6%), as well as pedestrian involvement (1.6%), was rare. Motor vehicle interactions were a significantly higher proportion of the serious moped injuries (50.7%) in comparison to e-bikes (32.5%). Interaction with motor vehicles was noted more than twice as frequently in cases treated at urban versus rural hospitals for both e-bikes and mopeds. There was one e-bike and 16 moped fatalities (raw counts), with all but one associated with impact with a motor vehicle.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Injury counts for e-bikes increased significantly greater than moped injury counts and increasingly involved younger riders. Alcohol involvement was significantly lower in e-bike injuries compared to moped injuries. Low reported rates of drug or pedestrian involvement were observed. Helmet use was poorly documented, despite head injuries being the most common injury type. Given the high prevalence of internal head trauma, universal helmet laws for e-bike and moped users should be considered. While fatalities remain rare for e-bikes compared to mopeds, the consistent role of motor vehicle interactions in the most severe cases points to a systemic issue in roadway safety. These findings suggest that e-bikes ","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-9"},"PeriodicalIF":1.9,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 risk-level identification incorporating personality traits, demographic characteristics, and driving behaviors.","authors":"Yu Liu, Tangzhi Liu, Xingliang Liu, Song Wang, Wei Wu, Changjun Wang, Tong Liu","doi":"10.1080/15389588.2025.2541901","DOIUrl":"https://doi.org/10.1080/15389588.2025.2541901","url":null,"abstract":"<p><strong>Objective: </strong>Human factors have a profound influence on the prevalence of vehicle crashes, particularly among high-risk drivers. This study aims to develop a driver risk-level identification method to effectively evaluate the safety of drivers and design training programs.</p><p><strong>Methods: </strong>The personality traits of 50 drivers were quantitatively evaluated using the Symptom Checklist-90 scale, with parallel documentation of demographic information. A tri-level risk categorization (low, medium, and high) was established for drivers based on risky driving behaviors investigated <i>via</i> field tests. Correlations between driver personality traits, demographic characteristics, and risk levels were systematically analyzed. Driver risk-level identification models were developed utilizing four machine learning algorithms: support vector machines, classification and regression tree, eXtreme gradient boosting, and multi-layer perceptron, with the relevant personality traits and demographic characteristics serving as predictor inputs. Evaluation indicators were tested to determine the optimal method for driver risk-level identification.</p><p><strong>Results: </strong>Factors such as sex, obsessive-compulsive disorder, depression, anxiety, hostility, and paranoid ideation are significantly correlated with driver risk levels. Furthermore, all four models have a recall of 100%, demonstrating high efficacy in identifying high-risk drivers. Among the four methods, the multi-layer perceptron model achieves the highest overall accuracy (86.7%) and F1-score (87.0%), along with a precision of 90.5% and a recall of 86.7%.</p><p><strong>Conclusion: </strong>Overall, personality traits and demographic characteristics play a crucial role in understanding driver risk levels, offering new insights to improve driver safety.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-11"},"PeriodicalIF":1.9,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144978956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 COVID-19 pandemic influence on fatal car crashes and impaired driving in Arkansas.","authors":"Velimir Petrovic, Kimberly O'Brien, Stephen M Bowman, Jerrilyn Jones, Carly Eastin, Sowmya Sivakumar, Austin Porter","doi":"10.1080/15389588.2025.2541267","DOIUrl":"https://doi.org/10.1080/15389588.2025.2541267","url":null,"abstract":"<p><strong>Objectives: </strong>The COVID-19 pandemic had a profound impact on motor vehicle traffic patterns, leading to a noticeable decrease in traffic volume during the peak of the pandemic. Previous studies have highlighted an increase in risky driving behaviors during the pandemic, such as impaired driving and not wearing seatbelts. Despite reduced traffic, many states, including Arkansas experienced an increase in motor vehicle crash fatality rates. This trend highlights the need to better understand the factors associated with this trend. This study aimed to examine the potential role of impaired driving and the lack of restraint use in the rise of fatal crashes during the pandemic.</p><p><strong>Methods: </strong>Record-level data from fatal car crashes occurring in Arkansas between 2018 through 2021 were obtained from the Fatality Analysis Reporting System (FARS). Multivariable logistic regression analyses were conducted to compare restraint use among both deceased drivers and passengers before (January 1, 2018 through March 10, 2020) and during the pandemic (March 11, 2020 through December 31, 2021), as well as impaired driving among drivers who died in a crash and all drivers involved in fatal crashes during the study period.</p><p><strong>Results: </strong>During the study period, there were 1,226 deceased drivers, 369 deceased passengers, and 2,200 drivers involved in fatal crashes. Among the 1,226 deceased drivers, there was a 34% decrease in the odds of seatbelt use during the pandemic compared to before the pandemic (<i>p</i> = 0.001). There were no significant changes in impaired driving among deceased drivers during the pandemic (AOR: 1.24; <i>p</i> = 0.09).Seatbelt use among the 369 deceased passengers did not change (AOR: 0.99; <i>p</i> = 0.96).Among the 2,200 drivers involved in fatal crashes, there was a 31% decrease in the odds of seatbelt use (<i>p</i> < 0.0001) and a 38% increase in the odds of impaired driving (<i>p</i> = 0.0002) during the pandemic when compared to before the pandemic.</p><p><strong>Conclusion: </strong>The increase in fatal car crashes during the pandemic may be attributed to the increase in impaired driving and decrease in restraint use. These findings highlight the need for public health interventions, such as sobriety checkpoints, public awareness campaigns, and strengthened enforcement to address impaired driving and promote restraint use.</p>","PeriodicalId":54422,"journal":{"name":"Traffic Injury Prevention","volume":" ","pages":"1-6"},"PeriodicalIF":1.9,"publicationDate":"2025-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144979116","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}