Accid Anal Prev [JOURNAL]
Sun
200 papers
A dynamic conflict-analysis framework for behaviour-centric safety evaluation of pedestrian-vehicle interactions at unsignalized crosswalks.
Muduli K, Ghosh I
Accid Anal Prev · 2026 Jun · PMID 41806799 · Publisher ↗
Pedestrian safety at unsignalized crosswalks remains a critical concern, particularly in heterogeneous traffic environments where formal right-of-way rules are often replaced by informal, real-time negotiations between p...
Pedestrian safety at unsignalized crosswalks remains a critical concern, particularly in heterogeneous traffic environments where formal right-of-way rules are often replaced by informal, real-time negotiations between pedestrians and drivers. Although surrogate safety measures are widely used to quantify interaction outcomes, they provide limited insight into how right-of-way negotiation evolves during pedestrian-vehicle encounters. To address this gap, this study proposes a behavior-oriented framework for analyzing pedestrian-vehicle negotiation dynamics at unsignalized crosswalks. The framework introduces a Negotiation Momentum (NM)-Sustained Dominance Duration (SDD) interaction space to capture both directional evolution of right-of-way and temporal stability of crossing advantage. These indicators are derived from a continuously defined Pedestrian Exit Buffer (PEB), estimated using a Dynamic Conflict Analysis Framework (DCAF) that models conflict geometry through road-user trajectories, heading angles, and representative vehicle dimensions. High-resolution trajectory data from four unsignalized crosswalks in India were used to classify interactions into ten behaviorally interpretable negotiation patterns. SDD thresholds were estimated using Extreme Value Theory, and a neutral NM band was defined to identify contested negotiation states. A multivariate linear mixed-effects model was then employed to examine safety implications of these patterns. Results indicate that safety margins are strongly shaped by negotiation structure: proactive yielding is associated with higher PET, TTC, and PEB values, whereas chaotic negotiation and pedestrian hesitation result in substantially reduced safety margins. The proposed framework provides a behaviorally grounded interpretation of pedestrian-vehicle interactions by explicitly linking safety outcomes with underlying right-of-way negotiation process, complementing conventional surrogate safety assessment at unsignalized crosswalks.
Driving anger and risky behaviour during commuting: The roles of time pressure and children's presence in a naturalistic study from China.
Wang J, Liu J, Shi Z … +2 more , Yang Z, Azadi H
Accid Anal Prev · 2026 Jun · PMID 41806798 · Publisher ↗
Driving anger is a key psychological factor contributing to risky driving behaviors and elevated crash risk. However, little is known about how situational commuting contexts-such as time pressure and the presence of chi...
Driving anger is a key psychological factor contributing to risky driving behaviors and elevated crash risk. However, little is known about how situational commuting contexts-such as time pressure and the presence of children-shape or moderate the anger-risk association, especially under similar traffic conditions. Drawing on Naturalistic Driving Study (NDS)data from involving 985 drivers in Harbin, China, this study exmaines how situational factors influence the emotion-behavior pathway during real-world commuting. Drivers' anger were assessed using the 18-item Driving Anger Scale (DAS) based on video-stimulated recall of their own commuting episodes, while risky behaviors were evaluated by 50 trained experts using in-vehicle video observations. Structural equation modeling (SEM) was employed to test three hypotheses across different commuting scenarios. Results indicate a significantly stronger association between anger and risky behavior during morning peak-hour commutes (β = 0.284), highlighting the amplifying role of time-related pressure. In contrast, the presence of children in the vehicle was associated with lower levels of anger and risky behavior (e.g., β = 0.126 during afternoon commutes), suggesting a situational buffering effect linked to parental responsibility. Overall, the findings demonstrates that situational contexts critically shape the anger-risk relationship, intensifying under time pressure during morning commutes while weakening when children are present. These results underscore the importance of situational moderators in driver emotion research and support policy efforts such as adaptive traffic control systems, identity-based safety campaigns, and in-car emotion monitoring technologies.
Optimizing followers' car-following behaviors using rear-facing eHMIs.
Gu F, Chen Y, Wang Z … +4 more , Wang Z, Li J, Sheng H, He D
Accid Anal Prev · 2026 Jun · PMID 41797070 · Publisher ↗
Rear-end collisions are closely related to car-following (CF) behaviors and account for a large proportion of road crashes. Existing countermeasures mainly enhance drivers' perception of the direct leading vehicle; howev...
Rear-end collisions are closely related to car-following (CF) behaviors and account for a large proportion of road crashes. Existing countermeasures mainly enhance drivers' perception of the direct leading vehicle; however, growing evidence suggests that CF decisions rely on information beyond the direct leading vehicle. Thus, expanding drivers' perceptual range by providing information of the indirect leading vehicle (i.e., vehicle ahead of the direct leading vehicle) may enhance CF safety. Unlike in-vehicle human-machine interfaces (HMIs) that rely on vehicle-to-vehicle (V2V) communications, external HMIs (eHMIs) without relying on V2V technologies are more feasible at this stage. However, no research has explored whether eHMIs can improve CF safety. Thus, four rear-facing eHMIs providing information regarding the indirect leading vehicle in CF events were designed, including Brake-eHMI showing only brake action of the indirect leading vehicle, Distance-eHMI and Headway-eHMI showing the relative distance and time headway between the indirect leading vehicle and direct leading vehicle, and Video-eHMI showing the live-stream video ahead of the direct leading vehicle. A field experiment with 30 participants was conducted to evaluate the impact of eHMIs on driving safety and efficiency in CF events. We found that, in general, indirect leading vehicle information could improve CF safety in chain-braking events by enabling quicker brake responses and increasing minimum time-to-collision, without overloading drivers in CF events. This research provides insights into the design of innovative vehicle systems that leverage smart vehicles' perception capabilities to enhance driving safety.
A method to enhance drivers' hazard perception based on psychological deception induction.
Zhang S, Gao Y, Zhang X … +3 more , Gu T, Jin H, Feng Z
Accid Anal Prev · 2026 Jun · PMID 41797069 · Publisher ↗
Drivers' hazard perception is a critical factor in road safety. However, existing interventions in driver safety education and training lack relevance and interactivity. Additionally, these interventions typically fail t...
Drivers' hazard perception is a critical factor in road safety. However, existing interventions in driver safety education and training lack relevance and interactivity. Additionally, these interventions typically fail to address the perception needs of potential hazards in complex traffic environment. This study investigated the effects of a psychological deception-induced intervention on drivers' hazard perception. A total of 45 drivers were recruited and randomly divided into a control group and two experimental groups (the informed false heart rate alerts group and the uninformed false heart rate alerts group). We collected and analyzed eye movement data, physiological data, and driving behavior data of drivers from all three groups across 6 scenarios using one-way ANOVA and Kruskal-Wallis tests. The results indicate that drivers in both experimental groups demonstrate enhanced hazard perception relative to the control group. Specifically, compared to the control group, drivers in both experimental groups exhibited longer average fixation durations, shorter time to first fixation, lower driving speed, smoother brake pedal force, and lower true heart rate in hazardous scenarios. These results suggest that the intervention supported earlier hazard detection and more rational responses. Furthermore, comparison between the two experimental groups revealed that the uninformed false heart rate alerts group showed greater improvement in attention allocation to hazards than the informed false heart rate alerts group. The study offers novel insights for enhancing road safety awareness and for designing future driver assistance systems.
Determinants of bicyclist injury severity in vehicle-bicycle crashes: Model specification and the assessment of temporal and age effects.
Alnawmasi N, Dzinyela R, Lord D … +1 more , Mannering F
Accid Anal Prev · 2026 Jun · PMID 41797068 · Publisher ↗
Bicyclist injury severity varies notably across age groups due to differences in riding experience, risk-taking behavior, physical vulnerability, and response times. This study explores the demographic and temporal heter...
Bicyclist injury severity varies notably across age groups due to differences in riding experience, risk-taking behavior, physical vulnerability, and response times. This study explores the demographic and temporal heterogeneity of bicyclist injury outcomes by examining crashes involving young, middle-aged, and older cyclists before, during, and after the COVID-19 lockdowns. Using detailed single-vehicle/single-bicycle crash data from Florida spanning 2019 to 2021, random parameters logit models with heterogeneity in means and variances of the random parameters were estimated, considering severe injury, minor injury, and no visible injury as possible injury outcomes. Likelihood ratio tests indicated significant temporal shifts of the model parameters across the three yearly time periods as well as age-related differences in model parameters. Considering a wide range of explanatory variables related to bicyclists, drivers, vehicles, roadways, and environmental conditions, the findings underscore the importance of proper model specification and reveal statistically significant variations in injury severity patterns across age groups and time periods. The findings also show that, in some instances, the commonality of parameters over time periods and age groups is statistically justified, giving additional insights into the determinants of injury severity and underscoring the importance of proper model specification.
Research on multi-level container security isolation operation strategy based on static game.
Wen J, Cao Y, Sun Y … +1 more , Wang F
Accid Anal Prev · 2026 Jun · PMID 41793843 · Publisher ↗
With the increasing pressure on rail transit passenger services, the introduction of cloud-edge collaborative computing technology into passenger service systems has emerged as a research hotspot in recent years. The key...
With the increasing pressure on rail transit passenger services, the introduction of cloud-edge collaborative computing technology into passenger service systems has emerged as a research hotspot in recent years. The key issue in applying cloud computing to passenger service systems lies in enhancing the security and reliability of applications/data within containers in cloud-edge computing environments. Since passenger service systems operate in open network environments, they are exposed to numerous security vulnerabilities and malicious cyber-attacks, potentially leading to system crashes or the leakage of critical data. To mitigate the severe impacts of such attacks, effective container security isolation policies must be implemented. Firstly, a multi-level container security isolation model is proposed, along with the design of rules for configuring model security policies. Subsequently, a static game model is utilized to dynamically adjust optimal security strategies. By integrating the wolf pack algorithm with the co-evolution algorithm, a wolf pack-co-evolution algorithm is devised to ascertain the optimal solution for the static game, thereby determining the optimal security strategy. Finally, simulation experiments demonstrate that the wolf pack-co-evolution algorithm can effectively solve for the Nash equilibrium in the multi-level container security isolation static game model, enabling dynamic adjustments to be made to security strategies. This approach ensures the security of both container subjects and objects while enhancing container computing efficiency.
Decoding the influencing factors of pedestrian-automated vehicle interaction in shared spaces: A multi-level path analysis approach.
Yang L, Dane G, Feng T … +1 more , Kemperman A
Accid Anal Prev · 2026 Jun · PMID 41785561 · Publisher ↗
In the near future, pedestrians will increasingly face automated vehicles (AVs) in urban environments, particularly in shared spaces. Ensuring safe and effective pedestrian-AV interactions requires a deeper understanding...
In the near future, pedestrians will increasingly face automated vehicles (AVs) in urban environments, particularly in shared spaces. Ensuring safe and effective pedestrian-AV interactions requires a deeper understanding of the factors that affect pedestrian behaviour. This study examines how environmental and individual factors influence pedestrians' perception and crossing behaviour in front of AVs in shared spaces. A virtual reality (VR) experiment with 60 participants was conducted to simulate diverse traffic scenarios, and both subjective and behavioural data were collected after each trial. Using multi-level path analysis, we modelled the direct and indirect effects of environmental factors (e.g., lane width, visual load, surface condition, time of day, traffic markings, traffic conditions) and individual factors (e.g., age, gender, educational level, personality) on perceived safety, comfort, legibility, trust and behavioural outcomes including crossing initial time, crossing duration and safety margin. The findings highlight that traffic markings and traffic conditions are the most influential factors, while educational level, transport modes, and personality traits also play a significant role. For example, the presence of zebra and yielding AV behaviours were associated with more positive perception and safer crossing behaviour. Participants with higher education levels and greater openness tended to show more supportive attitudes during interactions with AVs. In addition, perception served not only as an outcome but also as a mediator associating context and behaviour. The results provide valuable insights for enhancing the design of AV systems and shared spaces to improve pedestrian safety and trust.
Urban high-risk scenarios for automated vehicle safety testing: A generation and generalization method based on accident data.
Chu Y, Wang C, Ma M … +3 more , Zhao G, Miao Z, Wang W
Accid Anal Prev · 2026 Jun · PMID 41785560 · Publisher ↗
To improve the effectiveness of automated vehicles (AVs) safety testing and address key issues including distribution bias in road data collection and insufficient coverage of high-risk events, this study adopts a genera...
To improve the effectiveness of automated vehicles (AVs) safety testing and address key issues including distribution bias in road data collection and insufficient coverage of high-risk events, this study adopts a generation and generalization method to establish high-risk scenarios based on the AV Testing - High-Risk City Accident Dataset (AVT-HRCAD). Firstly, Cramer's V coefficient and eta squared coefficient are employed to identify risk variables that significantly affect accident severity. Secondly, the K-medoids clustering algorithm, iteratively optimized based on Gower distance, generates baseline risk scenarios. Ultimately, a Risk Index (RI) measures risk levels, while the NRPE criterion-assessing Number, Risk, P-value, and Effect-is intended to evaluate and generalize test situations. Principal findings indicate: Nine, seven, and seven key risk variables were identified for expressways, intersections, and road segments, respectively. Ego behavior, target type, collision angle, and lighting conditions consistently emerged as consistently significant risk factors across all three road types. Scenario generalization effectively addressed low-sample/high-severity variables (e.g., three-wheelers), broadening 18 baseline risk scenarios into general-risk, high-frequency-risk, and long-tail high-risk scenarios. A total of 93 urban high-risk test scenarios were established to assess AV capabilities in risk avoidance (across different vehicle types and collision angles), safety distance determination, and distance maintenance. This method provides a more authentic and valuable testing platform for comprehensive AV safety evaluation.
Multi-level signal-vehicle cooperative control to improve safety and efficiency for arterial intersections in mixed-autonomy traffic.
Zhang G, Li F, Lee JJ … +5 more , Huang H, Zhou Z, Li Y, Wang B, Chang F
Accid Anal Prev · 2026 Jun · PMID 41780114 · Publisher ↗
Cooperative control of traffic signals and connected autonomous vehicles (CAVs) has shown significant promise in improving safety and efficiency at isolated intersections. Nevertheless, extending such strategies to arter...
Cooperative control of traffic signals and connected autonomous vehicles (CAVs) has shown significant promise in improving safety and efficiency at isolated intersections. Nevertheless, extending such strategies to arterial intersections introduces considerable complexity, requiring seamless coordination across multiple intersections and the dynamic control of heterogeneous traffic flows. This paper proposes a Multi-Level Signal-Vehicle Cooperative Control (ML-SVCC) system that integrates multi-agent reinforcement learning (MARL)-based traffic signal control (TSC) and CAV speed advisories to optimize safety and efficiency across the arterial network. In the proposed system, each intersection is modeled as a local agent that uses context-specific traffic conditions as state inputs and performance metrics as the reward function. A global agent, operating within a distributed framework, evaluates the collective performance of all local agents and refines their models to ensure coordinated control. By providing additional rewards, the central agent refines the local agents' models, ensuring coordinated and effective traffic control throughout the network. Additionally, the system features a speed control module embedded in CAVs that adjusts vehicle speeds to align with signal timings, promoting smooth and efficient traffic flow across the arterial network. Simulation results in a real-world arterial setting in Changsha City, China, show that the proposed system reduces traffic conflicts by 42%-54% and delays by 25%-57%, outperforming the traditional TSC, the MARL-based TSC, and the Green Light Optimal Speed Advisory. Furthermore, the system minimizes vehicle stops and the frequency of acceleration and deceleration, demonstrating robust performance as CAV penetration rates increase.
Accident characteristics of professional versus regular two-wheeler riders in France and the UK: insights from national crash databases.
Wei W, Ma Z, Shen J … +3 more , Deng G, Vernet C, Thollon L
Accid Anal Prev · 2026 Jun · PMID 41774968 · Publisher ↗
Two-wheeler (TW) use for delivery has expanded rapidly, yet the safety of these professional riders remains understudied. This study compared crash characteristics of professional and regular TW riders in France and the...
Two-wheeler (TW) use for delivery has expanded rapidly, yet the safety of these professional riders remains understudied. This study compared crash characteristics of professional and regular TW riders in France and the UK (2019-2023) using national crash databases, combining descriptive epidemiology and logistic regression. Professional riders were younger (median age: 31 vs. 33 and 34 for regular riders in France and the UK, respectively) and predominantly male (93.8% in France; 89.7% in the UK). They more often used light motorized TWs (59.1% in France; 56.0% in the UK) in urban, lower-speed environments. Crash timing reflected delivery activity, peaking on Fridays and during midday and evening hours in France, whereas patterns were more dispersed in the UK. Injury severity also differed: professional riders sustained slight injuries more often than regular riders (France: 74.7% vs. 54.5%; UK: 82.3% vs. 69.1%) and had higher odds of slight injury (France: 4.91; UK: 2.95). These patterns are likely related to younger age, lighter vehicle use, and greater protective gear adherence. Cross-country contrasts were also evident, with slight injuries more common in both rider groups in the UK, likely reflecting greater pedal cycle use and broader implementation of low-speed zones. Professional riders represent a distinct high-exposure group with specific crash patterns both relative to regular riders and across countries. Tailored safety measures are needed, including enforcement of protective equipment, safer management of 30-50 kph and 20-30 mph urban zones, and time-specific awareness campaigns around delivery peaks.
Inferring crowd crush accidents in typical high-density pedestrian movement zones via the vision-trajectory fusion neural network.
Thomas Xie CZ, Zhang H, Zhang Y … +3 more , Yang X, He Z, Tian Y
Accid Anal Prev · 2026 Jun · PMID 41774967 · Publisher ↗
Pedestrian walking constitutes an indispensable mode of daily travel, yet recurrent high-density crowd gatherings in relevant facilities, e.g., holiday surges at railway stations, are widely recognized as high risk facto...
Pedestrian walking constitutes an indispensable mode of daily travel, yet recurrent high-density crowd gatherings in relevant facilities, e.g., holiday surges at railway stations, are widely recognized as high risk factors that can precipitate crowd crush accidents. To facilitate effective prevention, this study provides a foundational step by enabling precise inference of spatio-temporal crowd evolution characteristics in representative high-density movement zones via accurate pedestrian trajectory prediction. Technically, we develop a dual-modal data-driven framework, i.e., the Vision-Trajectory Cross Fusion Crowd Prediction Neural Network (VT-CrowdNet), which integrates an enhanced graph-learning module for structured trajectory modeling, an extended vision transformer for bird's-eye surveillance feature extraction, and an adapted cross-attention residual fusion mechanism for dual-modal integration, thereby enabling high-fidelity forecasting of individual trajectories that underpin subsequent multi-metric accident inference. The latter is conducted using region-scale indicators capturing crowd danger and transit efficiency, as well as global-scale metrics reflecting collective movement fluidity. Experiments are first conducted to evaluate VT-CrowdNet, alongside classical and state-of-the-art baselines, on microscopic trajectory prediction across representative high-density crowd movement zones, including unidirectional and bidirectional corridors, as well as the four-directional intersection. After validating VT-CrowdNet's performance at the microscopic level, the most complex zone, namely, the four-directional intersection, characterized by frequent and heterogeneous pedestrian interactions, is further selected to assess the model's capability in inferring spatio-temporal patterns of crowd crush risk at both regional and global scales. Results demonstrate that VT-CrowdNet not only achieves superior microscopic trajectory prediction across all movement zones but also consistently exhibits leading performance in inferring crowd crush related spatio-temporal characteristics. Two key insights emerge: i) under a dual-modal framework, performance consistently improves only when imagery and structured data are effectively aligned, whereas modal misalignment can adversely affect accuracy; ii) relatively accurate trajectory prediction does not necessarily ensure reliable inference of crowd crush characteristics and may mislead the management and intervention of the pedestrian traffic flow if based on erroneous outputs.
Human-machine shared driving for vehicle collision avoidance based on Hamilton-Jacobi reachability.
Zhao S, Zhang J, Zhou R … +4 more , Masoud N, Li J, Huang H, Zhao S
Accid Anal Prev · 2026 Jun · PMID 41764865 · Publisher ↗
Human-machine shared collision avoidance in critical collision scenarios aims to aid drivers' collision avoidance through intervening only when necessary. Existing methods count on replanning collision-free trajectories...
Human-machine shared collision avoidance in critical collision scenarios aims to aid drivers' collision avoidance through intervening only when necessary. Existing methods count on replanning collision-free trajectories and imposing human-machine tracking, which usually interrupts the driver's intent and increases the risk of conflict. This paper introduces a Reachability-Aware Reinforcement Learning (RL) framework for shared control, guided by Hamilton-Jacobi (HJ) reachability analysis. Machine intervention is activated only when the vehicle approaches the boundary of the Collision Avoidance Reachable Set (CARS), thereby preventing the system from entering states where collision is theoretically unavoidable. First, we precompute the reachability distributions and the CARS by solving the Bellman equation using offline data. To reduce human-machine conflicts, we develop a driver model for sudden obstacles and propose an authority allocation strategy considering key collision avoidance features. Finally, we train a RL agent to reduce human-machine conflicts while enforcing the hard constraint that prevents the system from entering the CARS. The proposed method was tested on a real vehicle platform. Results show that the controller intervenes effectively before reaching the CARS boundary to prevent collisions while maintaining improved original driving task performance. Robustness analysis further supports its flexibility across different driver attributes.
How does the connected AR-HUD warning system affect lane-changing strategies during freeway abandoned object events: A survival analysis approach.
Zhang Y, Zhao X, Bian Y … +3 more , Huang J, Yao Y, Yu D
Accid Anal Prev · 2026 Jun · PMID 41764864 · Publisher ↗
In the connected environment, Head-Up Displays (HUD) and Augmented Reality Head-Up Displays (AR-HUD) are anticipated to enhance driver performance by presenting warning information within the driver's line of sight. Howe...
In the connected environment, Head-Up Displays (HUD) and Augmented Reality Head-Up Displays (AR-HUD) are anticipated to enhance driver performance by presenting warning information within the driver's line of sight. However, in freeway abandoned object events characterized by high suddenness and difficulty in advance prediction, it remains unclear whether both can effectively assist drivers in formulating optimal lane-changing strategies. This study aims to explore the impact mechanism of HUD and AR-HUD on drivers' lane-changing strategies in this scenario, and to identify the key factors affecting their effectiveness. To this end, a driving simulation platform was used to construct a scenario of connected freeway abandoned object event and design three warning systems (Baseline/HUD/AR-HUD). A total of 35 subjects' driving behavior data were collected through driving simulation experiments. Hazard perception time (HPT), lane-changing maneuver time (LMT), and time to collision (TTC) were selected as key indicators for lane-changing strategy from the perception and decision stage, risk-avoidance manipulation stage, and risk-avoidance result stage, respectively. Survival analysis, including Kaplan-Meier (KM) and Accelerated Failure Time (AFT) methods, were used to analyze the differences in HPT, LMT, and TTC among three warning systems (Baseline/HUD/AR-HUD) and to explore the effects of initial speed and driver attributes (gender, age, driving experience, and occupation) on lane-changing strategies in different warning system groups. The consistent results of KM and AFT indicate that in freeway abandoned object events, HUD did not show significant advantages compared to Baseline, while AR-HUD helped drivers achieve optimal lane-changing strategies. Specifically, the AR-HUD warning system can help drivers identify suddenly falling objects more quickly, perform low-speed and smooth lane-changing maneuvers, and significantly improve the final TTC. Additionally, AFT results further reveal that the effectiveness of the HUD system exhibited higher instability and stronger dependency on individual driver attributes, while AR-HUD demonstrated more consistent and robust effects across different driver groups. In particular, compared to the Baseline and HUD, the AR-HUD warning system reduced the differences in HPT among drivers with varying initial speeds and ages. While professional drivers maintain a tendency to perform faster lane-changing maneuvers in both the HUD and AR-HUD groups, both warning systems effectively prolonged their lane-changing maneuver time, with AR-HUD exhibiting a particularly pronounced effect. The HUD warning system has an adverse effect on the collision avoidance safety of drivers with high driving experience. In contrast, AR-HUD positively influenced drivers across all levels of driving experience, although drivers with low driving experience and high initial speeds still exhibited relatively lower TTC. The research results can provide references for the extended application of the AR-HUD warning system and the optimized design of the human-machine interaction system in intelligent connected vehicles.
Graduated drivers licensing and traffic injury-attributable emergency department visits in Alberta, an interrupted time series study.
Benny C, Belton KL
Accid Anal Prev · 2026 Jun · PMID 41762447 · Publisher ↗
BACKGROUND: Graduated drivers licensing (GDL) programs are being simplified across Canada. In April 2023, Alberta removed advanced road testing for full (Class 5) licenses and lifted previous restrictions on alcohol use,...
BACKGROUND: Graduated drivers licensing (GDL) programs are being simplified across Canada. In April 2023, Alberta removed advanced road testing for full (Class 5) licenses and lifted previous restrictions on alcohol use, nighttime driving, and passengers for learners (Class 7). As of June 25, 2023, ∼700,000 drivers gained full licensure without advanced testing. New Alberta drivers are younger, less restricted, and have higher motor vehicle collision (MVC) rates than other provinces. MATERIALS & METHODS: We used interrupted time series analysis with publicly available data from January 2022 to January 2025. Negative binomial regression was used to estimate immediate and longer-term effects of the policy change on emergency department (ED) visits due to MVCs, adjusting for age, gender, and seasonality, with subgroup analyses by road user type. RESULTS: Following the changes to GDL programming, drivers and passengers experienced modest increases in visit rates immediately after the intervention (driver IRR: 1.05, 95% CI: 1.00-1.11; passenger IRR: 1.11, 95% CI: 1.02-1.21). Motorcycle drivers showed larger increases, though estimates for motorcycle passengers were imprecise due to small sample size (motorcycle driver IRR: 1.40, 95% CI: 1.09-1.78; motorcycle passenger IRR: 1.49, 95% CI: 0.81-2.73). DISCUSSION: Removing GDL restrictions in Alberta led to immediate increases in MVC-related ED visits, particularly among motorcycle users, younger age groups, and males. Minimal ongoing trends suggest the effects were largely immediate and no statistically significant lasting impacts are noted. These findings highlight potential safety risks from relaxing licensing restrictions and the need for targeted interventions for high-risk groups as other provinces consider similar policy changes.
A driving visibility index for evaluating urban road driving safety based on point cloud data.
Zhang Z, Yuan Y, Huang H … +3 more , Wang Y, Li J, Wu B
Accid Anal Prev · 2026 Jun · PMID 41762446 · Publisher ↗
Road traffic safety assessment is critical for mitigating traffic accidents, safeguarding human life and property, and fostering socioeconomic development. Existing methods, which rely on the statistical analysis of hist...
Road traffic safety assessment is critical for mitigating traffic accidents, safeguarding human life and property, and fostering socioeconomic development. Existing methods, which rely on the statistical analysis of historical traffic accidents and conflicts as well as the evaluation of road design parameters, play a pivotal role in assessing road traffic safety. Driving visibility acts as a critical indicator of the driver's field of view and serves as a significant supplement to these methods. Consequently, this study proposes a method for quantifying 3D driving visibility utilizing LiDAR point cloud data. The approach establishes a computational framework for 3D visible space from the driver's perspective and introduces a novel Driving Visibility Index (DVI) to enable visibility-based safety evaluation. The proposed method consists of three primary components: road point cloud acquisition and preprocessing, driving visibility field computation, and DVI computation. We validated the proposed method along Yixian Avenue at Sun Yat-sen University's Zhuhai Campus, generating a driving safety map. The results revealed that the overall DVI for bidirectional travel on Yixian Avenue ranges from 0.2 to 0.6, indicating suboptimal safety conditions. Further comparative analysis with field-collected data subsequently confirmed the robustness of our proposed method. The proposed method's objective and intuitive quantification of 3D visible space from the driver's perspective provides a novel basis for traffic management, with significant applications spanning road design, traffic facility layout, and the validation of intelligent transportation networks.
Systematic review of weaving area safety: Assessment, behavior, and countermeasures.
Gao D, Lee JJ, Mao S
Accid Anal Prev · 2026 Jun · PMID 41747511 · Publisher ↗
Ensuring safety in road weaving areas remains a critical challenge for modern highway networks due to their inherent operational complexity. These areas serve as vital nodes for traffic exchange but are characterized by...
Ensuring safety in road weaving areas remains a critical challenge for modern highway networks due to their inherent operational complexity. These areas serve as vital nodes for traffic exchange but are characterized by intense mandatory lane changes and traffic turbulence, making them persistent hotspots for crashes and congestion. To consolidate the vast and evolving body of research on this topic, this study conducts a systematic review of road weaving area safety in accordance with the PRISMA methodology. Based on a final corpus of 83 studies published between 2004 and 2025, the literature is synthesized using a four-part thematic framework: Crash Analysis, Traffic Conflict Analysis, Driving Behavior Analysis, and Safety Improvement Strategies and Interventions. The synthesis reveals that weaving area safety is an emergent property of a complex system, governed by a causal feedback loop linking static geometry, dynamic traffic flow, and microscopic driver behavior. A dominant behavioral pattern identified is the tendency for drivers to front-load mandatory lane changes, concentrating turbulence at the segment entrance and leading to underutilization of downstream infrastructure. The review traces a clear evolution in the research paradigm from reactive, crash-based analysis to proactive, conflict-based prediction. This shift has been enabled by advancements in data acquisition and analytical methods, which have fundamentally redefined how risk is conceptualized and measured. Correspondingly, safety interventions have progressed through a clear hierarchy of control, from static geometric design, through reactive active traffic management and proactive cooperative intelligent transport systems advisories, to fully cooperative systems for Connected and Automated Vehicles (CAVs). Finally, the study outlines critical future research directions, highlighting the need for human-centered risk modeling, the validation of surrogate safety measures in mixed-autonomy environments, and the development and testing of robust cooperative control strategies for CAVs.
Real-world driving behaviors in individuals with homonymous visual field loss: insights from a naturalistic driving study.
Choe S, Baker P, Park TS … +6 more , Bittner AK, Simpson D, Hanson KS, Lin RJ, Yoshinaga PD, Bowers AR
Accid Anal Prev · 2026 Jun · PMID 41747510 · Full text
BACKGROUND: Drivers with homonymous visual field loss (HVFL) have complete loss of vision in one-quarter or one-half of the visual field on the same side of both eyes. Prior research investigating the effects of HVFL on...
BACKGROUND: Drivers with homonymous visual field loss (HVFL) have complete loss of vision in one-quarter or one-half of the visual field on the same side of both eyes. Prior research investigating the effects of HVFL on driving has used self-reports, simulated driving or on-road tests in an unfamiliar vehicle. Here, for the first time, we use naturalistic driving to examine driving patterns and safety of HVFL compared to normal vision (NV) drivers in their daily driving. METHODS: Using recording devices mounted in participants' own vehicles, we monitored 16 HVFL and 16 age-matched NV drivers continuously over 1-6 months in three U.S. regions. GPS data quantified weekly driving exposure (mileage, time, and driving days), avoidance behaviors (highway, long-distance, nighttime driving), safety-related events (hard braking, acceleration, speeding), route familiarity, and time-of-day driving patterns. Self-reported exposure and avoidance were collected at baseline. RESULTS: HVFL drivers showed qualitatively reduced driving exposure but similar frequencies of safety-related events and similarly high proportions of familiar road use compared to NV drivers. HVFL drivers showed a temporal shift toward earlier driving hours, reducing late afternoon and evening driving under low-light conditions. Notably, the HVFL group showed significant discrepancies between self-reported and objectively measured mileage and avoidance behaviors such as nighttime or highway driving. CONCLUSIONS: Despite their visual impairment, HVFL drivers exhibited real-world driving behavior comparable to NV drivers for hard braking, acceleration and speeding, extending previous road-test findings. The observed mismatch between self-reports and objective driving metrics underscores the value of naturalistic observation and the necessity for multi-method assessment frameworks in driving evaluations.
Understanding the risk factors of driving dilemmas at urban tunnel exits adjoining diverging areas: A naturalistic study.
He S, Du Z, Wong YD … +2 more , Ding X, Wu P
Accid Anal Prev · 2026 Jun · PMID 41740451 · Publisher ↗
The complex driving environment at urban tunnel exits adjoining diverging areas often leads drivers to experience hesitation and uncertainty in decision-making, referred to as the driving dilemma, which can result in inc...
The complex driving environment at urban tunnel exits adjoining diverging areas often leads drivers to experience hesitation and uncertainty in decision-making, referred to as the driving dilemma, which can result in incorrect route choices and traffic violations, thereby increasing driving risks in this area. This study aims to provide a comprehensive understanding of the driving dilemma at urban tunnel exits adjoining diverging areas. Sixty-four subjects participated in a real vehicle test conducted in a typical urban tunnel in China. Significant pupil dilation was used as the criterion for identifying the driving dilemma. Subsequently, sensitive physiological and psychological indicators during dilemma episode were analyzed, and risk factors were examined using a Generalized Linear Mixed Model (GLMM). The results showed that although the white-hole effect typically causes pupil constriction, this tendency to constrict was suppressed during the driving dilemma, leading to relative pupil dilation. The driving dilemma was found to be common in these scenarios, with 46 out of 64 subjects exhibiting dilemma. Visual indicators such as fixation duration, saccade frequency, and saccade velocity, along with physiological measures including SDNN, RMSSD, LF/HF, and SampEn, were identified as sensitive markers of dilemma. These findings suggest that during dilemma, drivers experience reduced visual information processing capacity, decreased visual search efficiency, psychological instability, and increased mental stress. GLMM analysis revealed that both individual driver characteristics and external environmental factors significantly influenced the driving dilemma. Older drivers and those unfamiliar with the route were more prone to dilemma and exhibited higher dilemma intensity, whereas no significant gender differences were observed. Additionally, complex driving tasks and the absence of navigator support increased both the likelihood and intensity of driving dilemma. In essence, this study reveals the mechanisms of occurrence and individual differences in driving dilemma at urban tunnel exits adjoining diverging areas. It enriches the understanding of cognitive and physiological loads experienced by drivers in complex tunnel scenarios.
Analysis of duration between crashes among repeatedly crash-involved drivers using alternate unobserved-heterogeneity modeling approaches.
Song D, Feng J, Liu Y … +4 more , Yang Y, Zhi D, Ran B, Jiang D
Accid Anal Prev · 2026 Jun · PMID 41740450 · Publisher ↗
Repeatedly crash-involved drivers, due to their short inter-crash durations and high crash frequencies, represent a critical risk to public safety. Identifying the significant factors influencing crash recurrence is ther...
Repeatedly crash-involved drivers, due to their short inter-crash durations and high crash frequencies, represent a critical risk to public safety. Identifying the significant factors influencing crash recurrence is therefore of fundamental importance for reducing crash frequency. Using traffic accident records from a city in Inner Mongolia, China, from 2014 to 2023, we analyze drivers involved in two or more crashes and examine the factors influencing their inter-crash durations. To address unobserved heterogeneity, two alternate modeling approaches are applied: a correlated random-parameters survival model with mean heterogeneity and a latent-class survival model based on class probability functions. Both models effectively capture multilayered unobserved heterogeneity of the crash data. The correlated random-parameters model identifies heterogeneous effects for spring and novice drivers, with a strong correlation between random parameters (0.746, p < 0.001) significantly influencing crash intervals. Other factors-such as previous PDO crashes, young drivers, truck driving, hilly terrain, median barrier, wet roads, and darkness with lights unlit-exert significant but homogeneous effects. The latent class survival analysis model identifies two distinct latent classes (Latent Class 1 with class membership probability of 0.577 and Latent Class 2 with class membership probability of 0.423) at a 0.001 significance level. And substantial differences are observed in the effects of explanatory variables on accident recurrence intervals across the classes. For instance, previous PDO crashes shorten recurrence durations in Class 1 (-0.789) but lengthen them in Class 2 (0.788); similarly, the wet-road indicator reduces recurrence in Class 1 (-0.815) yet increases it in Class 2 (1.040). Furthermore, estimation results from both heterogeneity-based models indicate that most fixed-effect variables share consistent directional signs, However, the average effect size differs substantially. For example, the effect of the Low visibility indicator is 1.199 in the random-parameters model compared to 0.189 in Class 2 of the latent-class model, while darkness with lights unlit yields -0.526 and -0.250 (Class 2), respectively. By applying two advanced econometric modeling approaches, this study offers a novel theoretical perspective on capturing heterogeneity in inter-crash durations among repeatedly crash-involved drivers. Meanwhile, the key determinants identified through these models provide a robust scientific foundation for developing precision risk-intervention strategies, thereby supporting more targeted behavioral interventions for high-risk driver groups.
Association between prehospital time and injury severity in traffic crash patients.
Hsu LM, Kuo CM, Chen CL … +6 more , Chan CW, Ko SY, Ma HP, Oviedo-Trespalacios O, Chen C, Pai CW
Accid Anal Prev · 2026 Jun · PMID 41722204 · Publisher ↗
This study aimed to examine the association between on-scene time and trauma severity, with particular attention to differences across age groups and anatomical injury regions among patients injured in traffic crashes. W...
This study aimed to examine the association between on-scene time and trauma severity, with particular attention to differences across age groups and anatomical injury regions among patients injured in traffic crashes. We conducted a retrospective cohort study by linking emergency medical services (EMS) prehospital records with hospital-based trauma registry data from a single Level 1 trauma centre in metropolitan Taipei between 2016 and 2022. Traffic crash patients transported by EMS were included. Prehospital time was disaggregated into response time, on-scene time, and transport time. Injury severity was assessed using the Injury Severity Score (ISS), with ISS ≥ 9 defined as severe injury. Multivariable logistic regression models were used to evaluate associations between prehospital time components and injury severity. Additional analyses were stratified by age group and anatomical injury region. Among 5,022 patients, 1,858 (37.0%) sustained severe injuries. Longer on-scene time was strongly associated with higher injury severity; each additional minute on scene was associated with a 10.1% increase in the odds of severe injury (adjusted odds ratio [AOR] = 1.101; 95% CI, 1.085-1.117). Older age, poor consciousness, pedestrian involvement, and late-night crashes were also associated with severe injury. Age- and region-stratified analyses demonstrated consistent associations between longer on-scene time and higher severity (AIS ≥ 3) for head, thoracic, abdominal, and extremity injuries, with more pronounced associations among older adults. Longer on-scene time is closely associated with trauma severity and likely reflects greater injury complexity and patient acuity rather than a direct causal effect. Given the observational nature of this study, the findings should be interpreted cautiously and may be influenced by reverse causation and confounding by indication. These results highlight the importance of early severity recognition, appropriate triage, and minimizing avoidable delays while ensuring essential life-saving interventions in prehospital trauma care.
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