Accident; analysis and prevention最新文献_第2页

Identifying disorder and abnormal incidents in traffic flow: a thermodynamics approach based on differential velocity entropy 交通流中无序和异常事件的识别：基于微分速度熵的热力学方法

IF 6.2 1区工程技术

Accident; analysis and prevention Pub Date : 2025-09-24 DOI: 10.1016/j.aap.2025.108248

Wei Ye , Yueru Xu , Yichang Shao , Zhirui Ye , Chen Wang

{"title":"Identifying disorder and abnormal incidents in traffic flow: a thermodynamics approach based on differential velocity entropy","authors":"Wei Ye , Yueru Xu , Yichang Shao , Zhirui Ye , Chen Wang","doi":"10.1016/j.aap.2025.108248","DOIUrl":"10.1016/j.aap.2025.108248","url":null,"abstract":"<div><div>Macroscopic traffic safety situation estimation is an important prerequisite for identifying abnormal incidents and ensuring the safe operation of road network. Existing traffic flow metrics fail to comprehensively quantify disorder associated with crash risks and abnormal events. Inspired by thermodynamics, this research proposes a differential velocity entropy based on the distribution of velocity vectors and the maximum entropy (ME) approach. This entropy models the disorder in traffic flow, capturing additionally information typically overlooked in traditional fundamental diagrams. As a non-parametric measure of disorder, it eliminates heterogeneity arising from bin selection and sample size effects in quantitative analysis. Numerical simulations demonstrate its sensitivity to traffic phase transitions, revealing the spatial and temporal locations of bottlenecks. Subsequently, we conducted an empirical study with the I-24 MOTION dataset to assess the metric’s ability to identify crash impacts. The results show that entropy peaks correlate spatially and temporally with accident locations, and its evolution captures the propagation range of accident’s impact. Additionally, differential velocity entropy shows a strong association with conflict frequency and can serve as a key traffic-flow indicator for identifying the macroscopic traffic safety situation.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"223 ","pages":"Article 108248"},"PeriodicalIF":6.2,"publicationDate":"2025-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evaluating safety effects of variable speed limit systems via joint modeling 通过联合建模评估变速限制系统的安全效果

IF 6.2 1区工程技术

Accident; analysis and prevention Pub Date : 2025-09-23 DOI: 10.1016/j.aap.2025.108247

Yangsong Gu , Hairuilong Zhang , Lee D. Han , Xiaoyang Jia , David Jung-Hwi Lee

{"title":"Evaluating safety effects of variable speed limit systems via joint modeling","authors":"Yangsong Gu , Hairuilong Zhang , Lee D. Han , Xiaoyang Jia , David Jung-Hwi Lee","doi":"10.1016/j.aap.2025.108247","DOIUrl":"10.1016/j.aap.2025.108247","url":null,"abstract":"<div><div>Variable Speed Limits (VSL) systems are key components in Active Traffic Management System (ATMS). They dynamically and coordinately adjust speed limits to harmonize traffic flow thereby enhancing travel safety and reliability. The objective of this study is to evaluate the safety impacts of the VSL deployed on the I-24 Smart Corridor, Nashville, Tennessee, which went online in June of 2023. Safety indicators were measured by various crash outcomes, and they were typically modeled separately in previous studies. The potential correlations between collision type and its consequence represented by severity were often overlooked, leading to the underestimation of treatment effects. Hence, this study attempts to jointly model the rear-end, injury, and Property Damage Only (PDO) under the copula framework. The treatment effect, which is also known as the Crash Modification Factor (CMF) in before-after studies, is estimated by the Difference-in-Differences estimator in the marginal Negative Binomial (NB) model. Gaussian, Frank, and Clayton copulas were compared, and the best-fitting copula was used to estimate the model parameters. The results indicate that the copula models significantly outperform the separate NB models. The CMFs of rear-end and injury crashes resulting from VSL implementation are 0.677 and 0.686 respectively. Their scale-invariant correlation is very high (i.e., 0.91 out of 1), which suggests that the reduction in injury crashes may be attributed to the reduction of rear-end crashes. However, the change in PDO crashes was not statistically significant, possibly due to the shift from injury crashes to PDO crashes after traffic slowing down in adverse traffic conditions. Finally, the study results confirm the positive impact of implementing VSL systems and help justify future investments for candidate corridors.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"223 ","pages":"Article 108247"},"PeriodicalIF":6.2,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145120653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Revealing the lateral interference of lateral organization of automated truck platoon on surrounding manual vehicles 揭示了自动卡车排横向组织对周围手动车辆的横向干扰

IF 6.2 1区工程技术

Accident; analysis and prevention Pub Date : 2025-09-22 DOI: 10.1016/j.aap.2025.108244

Qi Li, Feng Chen

{"title":"Revealing the lateral interference of lateral organization of automated truck platoon on surrounding manual vehicles","authors":"Qi Li, Feng Chen","doi":"10.1016/j.aap.2025.108244","DOIUrl":"10.1016/j.aap.2025.108244","url":null,"abstract":"<div><div>Automated truck platoon (ATP) represents a promising near-term automated mobility solution that can advance road sustainability by reducing pavement wear when configured with lateral offsets. As ATPs will initially share the roadway with human-driven vehicles (HDVs) before a full shift to autonomous transport, understanding how ATP lateral organization affects adjacent-lane HDVs is critical to preventing unintended safety risks. To address this gap, we first conducted driving simulation experiments with 38 nonprofessional commuters to quantify the effects of lateral-offset ATPs on driver behavior. We then compared the critical lateral distances between driving simulation data and naturalistic driving data using nonparametric probability model, and used Monte Carlo simulation on naturalistic driving data to model ATP‐induced interference under varying distribution scenarios. Our results show that lateral‐offset ATPs induce significantly greater lateral deviations and speed reduction for HDV, especially on curves. Specifically, ATP elevates driver fear perception score by 22.77 %, increases lateral deviation of HDV by 38.46 %, and raises interference probability by 25 %. Moreover, drivers’ responses to ATPs do not fully align with risk-homeostasis theory. Based on these insights, we recommend limiting ATP lateral dispersion, particularly avoiding right-biased formations, and prohibiting such configurations on curved segments. By clarifying how lateral organization of ATP shapes mixed-traffic dynamics, this study informs the safe integration of platooning technologies into existing road networks.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"222 ","pages":"Article 108244"},"PeriodicalIF":6.2,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118237","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mapping high-speed railway accidents 2000–2024: characteristics, patterns, and preventive measures 2000-2024年高速铁路事故制图：特征、模式和预防措施

IF 6.2 1区工程技术

Accident; analysis and prevention Pub Date : 2025-09-22 DOI: 10.1016/j.aap.2025.108255

Dai Wan-Lin , Shan Ming , Zhai Zhao , Hwang Bon-Gang

{"title":"Mapping high-speed railway accidents 2000–2024: characteristics, patterns, and preventive measures","authors":"Dai Wan-Lin , Shan Ming , Zhai Zhao , Hwang Bon-Gang","doi":"10.1016/j.aap.2025.108255","DOIUrl":"10.1016/j.aap.2025.108255","url":null,"abstract":"<div><div>With the scale of high-speed railways growing globally, high-speed railway accidents during operation occur more and more frequently. However, a critical analysis of high-speed railway accidents happening in the past two decades remains lacking in extant literature. The aims of this study are to explore the characteristics and patterns of high-speed railway accidents worldwide and to propose feasible preventive measures accordingly. To achieve these goals, 150 high-speed railway accidents occurring globally between 2000 and 2024 were gathered first. Then, content analysis was performed to systematically examine distribution characteristics across four aspects of the information of the 150 accidents: dates and locations, casualties, causes and types. Subsequently, contingency table test was performed to assess the correlations between: (1) accident type and casualty; (2) accident type and cause; and (3) accident country and cause. Lastly, preventive measures that could potentially help to improve the safe operation of high-speed railway systems were proposed. Results showed that equipment factors (41.61%) are exposed to be the main causes, followed by human factors (33.58%) and environmental factors (24.82%). Furthermore, derailment and collision accidents are the most common accident types having the most serious consequence. Results also revealed significant correlations between accident type and both casualty and cause. As limited research has been conducted to explore the characteristics and patterns of global high-speed railway accidents, this study is a contributory research to the current body of knowledge. Additionally, the results of this study can provide practitioners with a deeper understanding of global high-speed railway accidents and thereby helping them develop more feasible measures to ensure the safe operation of high-speed railway systems.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"222 ","pages":"Article 108255"},"PeriodicalIF":6.2,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic risk assessment for autonomous vehicles from spatio-temporal probabilistic occupancy heatmaps 基于时空概率占用热图的自动驾驶汽车动态风险评估

IF 6.2 1区工程技术

Accident; analysis and prevention Pub Date : 2025-09-20 DOI: 10.1016/j.aap.2025.108226

Han Wang , Yuneil Yeo , Antonio R. Paiva , Jack P. Goodman , Jean Utke , Maria Laura Delle Monache

{"title":"Dynamic risk assessment for autonomous vehicles from spatio-temporal probabilistic occupancy heatmaps","authors":"Han Wang , Yuneil Yeo , Antonio R. Paiva , Jack P. Goodman , Jean Utke , Maria Laura Delle Monache","doi":"10.1016/j.aap.2025.108226","DOIUrl":"10.1016/j.aap.2025.108226","url":null,"abstract":"<div><div>Accurately assessing collision risk in dynamic traffic scenarios is a crucial requirement for trajectory planning in autonomous vehicles (AVs) and enables a comprehensive safety evaluation of automated driving systems. To that end, this paper presents a novel probabilistic occupancy risk assessment (PORA) metric. It uses spatiotemporal heatmaps as probabilistic occupancy predictions of surrounding traffic participants and estimates the risk of a collision along an AV’s planned trajectory based on potential vehicle interactions. The use of probabilistic occupancy allows PORA to account for the uncertainty in future trajectories and velocities of traffic participants in the risk estimates. The risk from potential vehicle interactions is then further adjusted through a Cox model, which considers the relative motion between the AV and surrounding traffic participants. We demonstrate that the proposed approach enhances the accuracy of collision risk assessment in dynamic traffic scenarios, resulting in safer vehicle controllers, and provides a robust framework for real-time decision-making in autonomous driving systems. From evaluation in Monte Carlo simulations, PORA is shown to be more effective at accurately characterizing collision risk compared to other safety surrogate measures.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"222 ","pages":"Article 108226"},"PeriodicalIF":6.2,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

What does the research tell us about contributory factors related to inattention and driving in rural areas? A systematic review 这项研究告诉我们，在农村地区，与注意力不集中和开车有关的因素是什么？系统回顾。

IF 6.2 1区工程技术

Accident; analysis and prevention Pub Date : 2025-09-18 DOI: 10.1016/j.aap.2025.108246

Lisa Buckley, Verity Truelove, Steven Love

{"title":"What does the research tell us about contributory factors related to inattention and driving in rural areas? A systematic review","authors":"Lisa Buckley, Verity Truelove, Steven Love","doi":"10.1016/j.aap.2025.108246","DOIUrl":"10.1016/j.aap.2025.108246","url":null,"abstract":"<div><div>Inattentive driving, such as visual-manual distraction, cognitive and affective based inattention, and impaired attention, poses a significant risk to traffic safety. Rural environments provide unique challenges for attention when driving, presenting an important area for research. As such, this study conducted a systematic review to synthesise research that explores the factors associated with inattentive driving and/or related motor vehicle crashes and injuries in rural areas. To be eligible for inclusion, studies were required to include analyses that identified a factor/s associated with driving and inattention in rural areas. Studies were excluded if they were conducted outside of high-income countries and were focused on commercial or occupational driving. Databases that were searched included PubMed, PsycNET, SCOPUS, and TRID, as well as reference lists of relevant systematic reviews that had a focus on inattention and driving. Of the 5142 original research articles that were identified, 23 papers met the eligibility criteria. The inattentive factors that were covered primarily included phone use, fatigue or drowsy driving, or distraction more broadly. Key contributory factors to inattentive driving and/or crashes across rural, regional and remote environments included road characteristics, driver characteristics, built environments and environment conditions. The findings also highlight the limited research in this area outside of crash-related data, with numerous future directions proposed. Given the heterogeneity and variety of factors that contribute to inattentive driving and crashes across distinct rural environments, more nuanced approaches for preventing inattentive driving in these areas is required. As such, stakeholders could consider performing comprehensive assessments of the unique circumstances associated with specific environments when considering interventional approaches to this issue.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"222 ","pages":"Article 108246"},"PeriodicalIF":6.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Quantifying uncertainties in data and model: a prediction model for extreme rainfall events with application to Beijing subway 数据与模型的不确定性量化——北京地铁极端降水事件预测模型的应用。

IF 6.2 1区工程技术

Accident; analysis and prevention Pub Date : 2025-09-18 DOI: 10.1016/j.aap.2025.108238

Liang Mu , Yurui Kang , Zixu Yan , Xiaobao Yang , Guangyu Zhu

{"title":"Quantifying uncertainties in data and model: a prediction model for extreme rainfall events with application to Beijing subway","authors":"Liang Mu , Yurui Kang , Zixu Yan , Xiaobao Yang , Guangyu Zhu","doi":"10.1016/j.aap.2025.108238","DOIUrl":"10.1016/j.aap.2025.108238","url":null,"abstract":"<div><div>Extreme rainfall is the primary cause of flooding at subway stations, and accurate prediction of rainfall volumes is essential for early flood warning systems. While previous research mostly focuses on point-by-point predictions based on rainfall spatiotemporal characteristics, it frequently ignores the uncertainties associated with rainfall data and predictive models, leading to unreliable rainfall forecasts. To address these limitations, we introduce a new model for predicting probability density (PD-STGCN) that systematically integrates data and model uncertainty quantification. This model provides both point predictions (PP) and probability density predictions (PDP) for extreme rainfall events. We specifically combine Monte Carlo Dropout (MC Dropout) and prediction variance into a Spatiotemporal Graph Convolutional Network (STGCN) architecture to quantify uncertainties in both the model and the data, and then build a new loss function to train the model based on the quantification results. Additionally, based on the sample set obtained by the trained model, and Gaussian Kernel Density Estimation (KDE) is used to calculate the rainfall probability density function (PDF) at the predicted moments. Validation using two distinct extreme rainfall events in Beijing shows that our proposed model outperforms various benchmark models in both tasks for point prediction and probability density prediction. These findings provide urban flood management with a novel predictive tool that combines high accuracy with strong reliability.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"222 ","pages":"Article 108238"},"PeriodicalIF":6.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Counterfactual evaluation of heavy vehicle safety policies on fatal crash rates using recursive discrete polynomial grey models 基于递归离散多项式灰色模型的重型车辆安全政策对致命碰撞率的反事实评价。

IF 6.2 1区工程技术

Accident; analysis and prevention Pub Date : 2025-09-18 DOI: 10.1016/j.aap.2025.108245

Yanqi Lian , Shamsunnahar Yasmin , Jaeyoung Jay Lee , Shimul Md Mazharul Haque

{"title":"Counterfactual evaluation of heavy vehicle safety policies on fatal crash rates using recursive discrete polynomial grey models","authors":"Yanqi Lian , Shamsunnahar Yasmin , Jaeyoung Jay Lee , Shimul Md Mazharul Haque","doi":"10.1016/j.aap.2025.108245","DOIUrl":"10.1016/j.aap.2025.108245","url":null,"abstract":"<div><div>Heavy vehicles play a crucial role in freight transportation. Yet, their crash risks and economic burdens necessitate a thorough investigation of long-term crash trends and an evaluation of safety policies targeting heavy vehicles. The intervention time series method, widely used in policy evaluation without the control group, is limited by its lack of causal inference and reliance on predefined effect assumptions. Thus, this study proposes a counterfactual causal framework using a recursive discrete polynomial time grey model to estimate the causal effects of multiple persistent road safety policies within a single time series. Specifically, the framework defines causal effects as contrasts between potential outcomes. The recursive discrete polynomial time grey model, capable of handling small sample sizes and capturing both linear and nonlinear trends, is introduced for counterfactual outcome prediction in traffic safety policy evaluation. The residual-based nested bootstrap resampling method is adopted to compute the confidence intervals of the estimated causal effects. The proposed framework is demonstrated using the annual fatal crash rates involving heavy vehicles per billion vehicle kilometers traveled from 1989 through 2023 in Queensland, Australia. Three major safety policies targeting heavy vehicles over those years are evaluated: Heavy Vehicle Fatigue Management Laws, Heavy Vehicle Speed Compliance Legislation, and Heavy Vehicle National Law. The findings indicate that these policies have significantly reduced the fatal crash rates involving heavy vehicles, although their effects exhibit temporal fluctuations. Nevertheless, without implementing new and innovative safety policies, the fatal crash rate involving heavy vehicles is likely to increase, underscoring the urgent need for continued policy advancements to enhance the safety of freight transportation systems.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"222 ","pages":"Article 108245"},"PeriodicalIF":6.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Two-step deep reinforcement learning for traffic signal control to improve pedestrian safety using connected vehicle data 基于车联网数据的交通信号控制两步深度强化学习提高行人安全。

IF 6.2 1区工程技术

Accident; analysis and prevention Pub Date : 2025-09-17 DOI: 10.1016/j.aap.2025.108161

A. Dian Ren , B. Gongquan Zhang , C. Fangrong Chang , D. Helai Huang

{"title":"Two-step deep reinforcement learning for traffic signal control to improve pedestrian safety using connected vehicle data","authors":"A. Dian Ren , B. Gongquan Zhang , C. Fangrong Chang , D. Helai Huang","doi":"10.1016/j.aap.2025.108161","DOIUrl":"10.1016/j.aap.2025.108161","url":null,"abstract":"<div><div>The primary goal of traffic signals control (TSC) is to enhance safety and protect all traffic participants. However, there exists enhancement such as increasing safety for vulnerable road users (VRUs), especially pedestrians. This study proposes a novel two-step traffic signal control framework based on deep reinforcement learning (TSDRL-TSC) to improve pedestrian safety and overall traffic efficiency at intersections. Based on advanced communication technologies of connected vehicles (CV), the TSDRL-TSC acquires the data from real-time traffic conditions and dynamically adjusts traffic signals, aiming to minimize traffic conflicts and delays of pedestrians and vehicles. In the first step, TSDRL-TSC decides whether to use traditional four-signal phases or a modified version considering the protected/prohibited right turn (PPRT) strategy based on pedestrian conditions. In the second step, TSDRL-TSC optimizes the specific control scheme through deep reinforcement learning techniques, selecting the optimal signal phases/actions for the current intersection state to obtain long-term reward returns. The reward function considers the safety and efficiency of all traffic participant, designed to balance the requirement for pedestrian safety, pedestrian efficiency, and vehicle throughput. Simulation experiments at a representative six-lane bidirectional intersection in Changsha City validate the effectiveness of the proposed method. Results demonstrate that (1) TSDRL-TSC significantly reduces pedestrian-vehicle conflicts, jaywalking incidents, and total delays compared to adaptive traffic signal control and PPRT control; (2) TSDRL-TSC presents the potential as a robust solution to enhance pedestrian safety and traffic efficiency for complex urban traffic management.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"222 ","pages":"Article 108161"},"PeriodicalIF":6.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145084867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Do older drivers (65+) exhibit significant impairments in hazard prediction and attentional processes? 年龄较大的司机（65岁以上）是否在危险预测和注意力过程中表现出明显的损伤？

IF 6.2 1区工程技术

Accident; analysis and prevention Pub Date : 2025-09-17 DOI: 10.1016/j.aap.2025.108182

Daniel Salazar-Frías , Sonia Ortiz-Peregrina , Francesco Martino , José-J. Castro-Torres , Jorge Clavijo-Ruiz , Cándida Castro

{"title":"Do older drivers (65+) exhibit significant impairments in hazard prediction and attentional processes?","authors":"Daniel Salazar-Frías , Sonia Ortiz-Peregrina , Francesco Martino , José-J. Castro-Torres , Jorge Clavijo-Ruiz , Cándida Castro","doi":"10.1016/j.aap.2025.108182","DOIUrl":"10.1016/j.aap.2025.108182","url":null,"abstract":"<div><div>This study pioneers the use of the Hazard Prediction-Orienting Test to examine attentional capture in older drivers (aged 65+). Participants watched short, naturalistic driving videos and were asked to predict what would happen next after the video cut to black just as a developing traffic hazard that would require a behavioral response (e.g., slowing down or changing lanes to avoid a collision) began to emerge. Each trial included three multiple-choice options, with the correct answer corresponding to the developing hazard. Attentional orienting was manipulated through three conditions: simple trials (one developing hazard); valid trials (two hazards: one potential, which does not require driver action, and another developing located nearby); and invalid trials (two hazards: one potential and another developing located at a distance). A total of 141 experienced drivers, grouped by age (middle-aged, young-senior, and elderly) completed the test. A 3 × 3 mixed-effects ANOVA revealed significant main effects by age group and trial type, as well as a significant interaction. Elderly drivers showed the greatest performance decline, specifically under complex hazard conditions (both valid and invalid trials). These results were supported by significant correlations with neuropsychological assessments, including the Trail Making Test, the Useful Field of View (UFOV), and visual function measures such as visual acuity. Furthermore, mediation analysis revealed that the effect of age on hazard prediction in invalid trials was significantly mediated by selective attention, as measured by UFOV subtest 3. These findings suggest that for drivers over 65, both hazard prediction and attentional performance decline to levels comparable to those of inexperienced drivers in our previous study. The test shows promise as a functional assessment tool for identifying age-related declines relevant to traffic safety.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"222 ","pages":"Article 108182"},"PeriodicalIF":6.2,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145084727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0