ACCIDENT ANALYSIS AND PREVENTION事故分析与预防
ACCIDENT ANALYSIS AND PREVENTION(英文缩写 ACCIDENT ANAL PREV),ISSN 0001-4575,eISSN 1879-2057,中文译名:事故分析与预防 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-09-28 至 2026-09-28，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 6.376 | Q1 |
| 2022 | 5.900 | Q1 |
| 2023 | 5.700 | Q1 |
| 2024 | 6.200 | Q1 |
| 2025 | 7.400 | Q1 |
ACCIDENT ANALYSIS AND PREVENTION 最新收录文献
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1. Experimental investigation on developing human-centric AEB based on drivers' collision-avoidance capability in safety-critical scenarios.
PMID:日期:2026-10-01Advanced Driving Assistance Systems (ADAS) can mitigate traffic accidents by issuing warnings or executing automated interventions in human-vehicle shared driving systems. However, their adaptability to human drivers remains limited, leading to inadequate coordination, increased collision risk, and potentially severe occupant injuries in safety-critical scenarios. This limitation stems from insufficient integration of drivers' inherent collision-avoidance behaviors into system design. Existing research lacks quantitative methods for assessing how drivers exhibit varying collision-avoidance capabilities across different automation levels. To address these gaps, we designed three types of safety-critical highway scenarios and conducted a simulator-based experiment to collect collision-avoidance data across different automation levels. Analyzing 45 drivers (mean age: 27.9 ± 5.1 years; mean driving experience: 7.8 ± 3.3 years; mean annual mileage: 6,890 km) across 2,605 scenarios, we quantified collision-avoidance capability using naturalistic behaviors and collision rates. Independent validation showed that collision risk increased by 59.7 percentage points when scenario urgency exceeded the derived collision-avoidance capability boundary. On this basis, we developed an a capability-based Autonomous Emergency Braking (AEB) concept with graded braking thresholds anchored to the empirically derived driver capability boundary. Results demonstrate that, compared with conventional AEB, the capability-based system achieves a 17.2% reduction in collision rates and mitigates average occupant injury severity by 10%. Furthermore, the system enhances operational reliability by decreasing nuisance intervention rates by 24.4%. This study demonstrates the feasibility of adapting AEB intervention timing based on driver capabilities, providing methodological insights that could inform the future design of broader human-centric ADAS and address the takeover challenge in shared driving.
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2. A consequence-aware driving risk field framework with data-driven calibration for high-risk scenario identification.
PMID:日期:2026-10-01Driving risk is a dynamically evolving process arising from the coupled effects of traffic interactions, the road environment, and driving behavior. Existing traffic risk assessment methods largely rely on crash outcomes or localized surrogate safety measures, making it difficult to obtain a unified risk representation that is consistent with crash consequences across different driving states. This paper proposes a driving risk field modeling framework that incorporates constraints imposed by crash consequences. By integrating scenario-level risk factors with vehicle-specific risk characteristics, the proposed approach provides an instantaneous risk score for a given driving state and supports the identification and ranking of high-severity crash scenarios conditional on crash occurrence. To improve the interpretability and internal consistency of the model, this paper develops a parameter calibration method using real-world crash data and microscopic traffic flow simulation data. The key parameters of the risk field are then systematically optimized via a differential evolution algorithm. Experimental results show that the constructed kinetic field captures both distance decay and velocity amplification effects. The composite driving risk metric exhibits a stable unimodal distribution on the logarithmic scale. After data-driven calibration, the proposed Driving Risk Field model improved regression-error-related metrics and showed competitive capability in identifying and ranking high-severity crash samples compared with the XGBoost baseline. Meanwhile, the differences in risk-field distributions across weather conditions and road types indicate that the model can reflect the influence of different scenario factors on risk scores at the internal response level. The findings provide a unified and interpretable modeling paradigm for crash-consequence-calibrated high-risk scenario scoring, supporting risk-scenario screening and traffic safety analysis.
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3. Cultural and skill-based influences on driver behaviors: a cross-national comparison between Belgium and Türkiye.
PMID:日期:2026-10-01Driver behavior is an important contributing factor in road crashes. It is influenced by various factors. Cultural orientations, such as individualism and collectivism, shape attitudes toward traffic rules and drivers' risk-taking behaviors. However, their interaction with perceived driving skills and national context has received limited attention. The present study examined how individualism-collectivism relates to driver behavior and whether these relationships are moderated by driving skills across two national contexts. Participants completed the questionnaires assessing cultural orientations, driving skills, and driver behaviors. A total of 527 drivers from Türkiye (M = 33.36, SD = 9.61; 44.2% female) and 326 drivers from Belgium (M = 29.35, SD = 12.29; 47.5% female) participated in the study. Moderated moderation analyses were conducted to examine the interactions between cultural orientations, driving skills, and country on driver behaviors. The findings showed that individualism was positively associated with driving violations in both countries. However, this relationship varied depending on perceptual-motor skills and country. In Türkiye, individualism was positively associated with violations across all levels of perceptual-motor skills. In Belgium, individualism predicted violations only among drivers who perceived their perceptual-motor skills as higher. In addition, collectivism was associated with fewer violations only among Belgian drivers with high perceptual-motor skills. There were no significant interaction effects for errors or positive driver behaviors. Overall, the findings show the importance of considering cultural orientations and driving skills together when examining driving behavior across different traffic contexts.
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4. A multi-scale road segmentation approach to assess MAUP effects on crash frequency and hotspot analysis.
PMID:日期:2026-10-01Road traffic crashes remain a major global safety concern, and segment-level crash analysis plays a critical role in identifying high-risk locations. However, such analyses are highly sensitive to spatial unit definitions, giving rise to the Modifiable Areal Unit Problem (MAUP). Existing studies predominantly rely on fixed or single-scale segmentation, which limits their ability to capture scale-dependent effects and may bias both model estimation and hotspot identification. To address this issue, this study proposes a hybrid multi-scale road segmentation framework that integrates roadway homogeneity with crash distribution characteristics. The framework employs a Poisson likelihood ratio test and leave-one-out cross-validation (LOOCV) to generate adaptive segmentation schemes, and evaluates MAUP effects through crash distribution analysis, negative binomial modeling, and external validation. The results show that segmentation choice materially affects statistical representation, model estimation, and predictive performance. Both the scale effect and the zoning effect of MAUP are found to influence crash modeling and hotspot-related inference, although their impacts are not identical. External validation reveals substantial performance differences among segmentation schemes, with Seg-6 showing the strongest predictive performance within the original parameter set; the sensitivity analysis further indicates that this result is locally robust within the evaluated parameter neighborhood. Major crash concentration patterns remain broadly stable across segmentation schemes, whereas minor local variations are more segmentation-sensitive. These findings show that segmentation should be treated as an explicit analytical design issue rather than a neutral preprocessing step, and provide a systematic basis for evaluating MAUP effects in segment-level traffic safety analysis.
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5. Drivers' neglect of cyclists in right-turns-a matter of rule knowledge rather than a lack of attention.
PMID:日期:2026-10-01Right-hook crashes in right-hand traffic where cyclists going straight are struck by right-turning vehicles pose a major safety concern. This study aims to establish to which extent such conflicts may stem from non-driving-related tasks (NDRT), low saliency of cyclists (covertness), or drivers' insufficient knowledge of applicable rules. Forty-four drivers participated in a fixed-base driving simulator study using an extended reality (XR) setup with integrated eye tracking. Participants were stratified by urban cycling experience (cyclist-drivers vs. drivers) and self-reported driving style (cautious vs. assertive). Each drove an urban route including 12 right-turn-on-yield scenarios, with and without NDRT. Observed visual sampling was combined with a questionnaire-based rule knowledge assessment to examine whether scanning failures were due to workload or lack of rule knowledge. NDRT engagement primarily reduced default glances while glances to relevant areas (Left, Right, Over Shoulder) were preserved. Over-the-shoulder checks were rare overall. In 85 % of right-turns, no such glance occurred before turning, regardless of NDRT status. Rule knowledge mirrored these patterns, with drivers being more likely to correctly indicate the requirement to yield to salient crossing traffic streams of cars (96 % correct) or cyclists and pedestrians (81 % correct) than non-salient crossing bicycle or pedestrian traffic (46 % correct). Drivers with cycling experience scored slightly better overall but still missed nearly half of the non-salient yielding requirements. The findings indicate that gaps in rule knowledge contribute to failures to check for cyclists. Countermeasures should prioritise systemic interventions, complemented by education, rather than solely relying on behaviour-focused measures.
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6. Automatic detection of emergency Maneuvers, crashes, and strong jolts in naturalistic riding data from e-bicycles and e-scooters.
PMID:日期:2026-10-01This study develops and validates a smartphone-based framework for automatically detecting emergency maneuvers, strong jolts, and crashes involving electric scooters and electric bicycles. Detection criteria were established through controlled track experiments and subsequently evaluated using data collected during a naturalistic riding study involving 119 participants and more than 26,000 km and 1,600 h of riding, combining accelerometer, gyroscope, GPS, and video recordings. Threshold-based detection criteria were defined using variables selected for their physical relevance and ability to discriminate between target and non-target situations. Hard braking, sharp turns, strong jolts, and crash-related events were identified using combinations of acceleration, jerk, rotational dynamics, and post-event vehicle motion. Video review showed that 74% of hard-braking detections corresponded to harsh-braking maneuvers, 64% of sharp-turn detections reflected genuine avoidance maneuvers, and 91% of strong-jolt detections were associated with infrastructure features. Video verification of collision candidates confirmed several reported and previously unreported impacts, including collisions with other road users and single-vehicle falls. Application of the framework to the naturalistic dataset revealed marked differences between vehicle types. E-scooter users experienced higher rates of hard braking and strong jolts than e-bicycle users, reflecting behavioral differences and vehicle characteristics. Illustrative mapping examples showed that detected events and rider-reported hazardous situations could occur in close proximity, suggesting opportunities for future spatial analyses of micromobility safety. Although additional validation on larger crash datasets is required, the results demonstrate that threshold-based approaches can provide meaningful indicators of rider safety, support large-scale monitoring of micromobility risks, and contribute to infrastructure and transport-safety assessment.
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7. Attention-switching car-following behavior modeling under variable speed limits: Explaining structural homogeneity and situational heterogeneity.
PMID:日期:2026-10-01Drivers in variable speed limit (VSL) environments continuously balance following the leader and complying with the posted speed limit, yet existing car-following models treat the desired speed as fixed and cannot represent this state-dependent attention allocation. Moreover, whether VSL induces structural changes in car-following behavior or primarily triggers situational adaptation remains underexplored. This study addresses both challenges using wide-area trajectory data from the Shanxi Wuyu Freeway under three VSL conditions (60, 80, and 100 km/h) at Level of Service A-B. A dual-dimension behavioral homogeneity framework reveals that car-following behavior remains structurally homogeneous across scenarios with no discrete driver subtypes. On this basis, an Attention-Switching Car-Following Model (AS-CFM) is proposed that introduces a continuous attention weight λ as a function of time headway (THW), simultaneously controlling a dynamic desired speed and an adaptive headway within an Intelligent Driver Model (IDM)-type acceleration framework, enabling smooth transitions between leader-following and speed-limit compliance. Calibration on 1136 events shows a 4.3 % per-event RMSE reduction relative to the IDM, while leave-one-scenario-out cross-validation demonstrates a 15.1 % average reduction in prediction error relative to the IDM under unseen VSL scenarios. Within-event attention dynamics further indicate that the observed variability is primarily situational rather than dispositional, with λ dynamically buffering scenario-sensitive parameters during close-following conditions. These findings suggest that a unified attention-switching framework offers a parsimonious and transferable approach to car-following modeling across VSL regimes, providing a mechanistic account of how drivers allocate attention under dynamic speed regulation and a more robust behavioral foundation for simulation-based VSL evaluation.
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8. How pedestrians react to imminent vehicle threats: a virtual reality study in safety-critical scenarios.
PMID:日期:2026-10-01As vulnerable road users, pedestrians face a high collision risk in safety-critical traffic scenarios. When faced with approaching vehicles, pedestrians need to balance their desire to cross the road with the demand for safety, resulting in either normal walking or avoidance behaviors. Such uncertain decision affects the occurrence of collisions. Therefore, it is important to understand pedestrian decisions so that highly automated vehicles (HAVs) can better develop safe interaction strategies. To study these decisions under controlled conditions, we designed an immersive virtual reality (VR) experiment where participants encountered traffic scenarios with different spatiotemporal pressures. The experiment observed three distinct decision modes under increasing spatiotemporal pressures: a no-risk mode in which pedestrians predominantly cross normally, a game mode showing a mix of crossing and avoidance, and a life-saving mode dominated by avoidance responses. Based on these decision modes, we proposed a regression model to predict pedestrian decisions. The model achieved an average precision of 0.87 and 0.82 for predicting whether and how pedestrian avoid. Finally, real pedestrian-vehicle conflict data were used to validate the effectiveness of the experimental results. This investigation observes pedestrians' decision modes in various urgent scenarios and presents a decision model based on pedestrians' decision modes, reflecting their interaction logic with hazardous vehicles in traffic scenarios. We expect that the observed decision modes can help develop the safety algorithms of HAVs to achieve safe interactions with pedestrians on roads.
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9. Effects of navigation modalities on driving performance under different cognitive load levels: an evaluation based on wearable glasses.
PMID:日期:2026-10-01The use of traditional navigation devices while driving leads to frequent gaze shifts, which is an important risk factor for distraction-related accidents. To fundamentally reduce the risk of visual distraction, non-visual auditory and tactile navigation are considered promising alternatives. Among these, wearable glasses, due to their head-mounted nature, facilitate the integration of multimodal cues on a single platform and may serve as an ideal solution for non-visual navigation. However, drivers often operate under varying levels of cognitive load, and the effects of auditory navigation, tactile navigation, and auditory-tactile navigation on driving performance under different cognitive load conditions remain unclear. Therefore, this study aims to investigate the effects of navigation modality (auditory navigation, tactile navigation, auditory-tactile navigation) and cognitive load level (no load, with load) on driving performance. A simulated driving study was conducted with a total of 36 participants. The results showed that, in terms of vehicle control, auditory navigation and auditory-tactile navigation outperformed tactile navigation in controlling both lateral and longitudinal maximum acceleration. Regarding secondary task performance, auditory-tactile navigation achieved the highest 1-back task accuracy, whereas auditory navigation resulted in the lowest accuracy. Regarding preference, auditory navigation was most preferred in the absence of cognitive load, while auditory-tactile navigation gained the highest preference when cognitive load was present. Overall, auditory-tactile navigation demonstrated better overall adaptability under cognitive load conditions. This finding provides empirical evidence for the design and evaluation of accident-prevention-oriented wearable navigation systems.
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10. Drivers have constrained cognitive resources under cognitive and visual distraction: Safety implications for transitions of control from vehicle automation.
PMID:日期:2026-10-01The objective of this study was to evaluate the effect of both cognitive and visual distraction on drivers' gaze behaviour and takeover performance during an SAE Level 2 automated drive. A driving simulator study was conducted where drivers needed to take over control during a safety critical scenario i) while engaged in an auditory version of the 2-back task (cognitive distraction), ii) during ambient occlusion of the driving scene (visual distraction) or iii) a combination of both. In line with previous studies, results showed that, under the 2-back task, drivers showed a lower horizontal dispersion of gaze for scanning the environment. In the ambient occlusion condition, drivers compensated for the temporary absence of the driving scene by dispersing their gaze vertically and towards offroad areas of the environment. In terms of their takeover performance, the results found no significant differences between cognitive and visual distraction manipulations alone. However, drivers' performance was significantly worse, when both manipulations were combined. The findings suggest that both visual and cognitive distraction may tax drivers' cognitive resources and consequently impact their takeover performance. This finding is relevant for future development of driver monitoring systems, which should consider the impact of cognitive load on drivers' performance, even if their eyes are facing towards the road.