Accident; analysis and prevention最新文献

{"title":"High-dimensional functional boundaries search for deviation-robust testing of autonomous driving system","authors":"Yunwei Li ,&nbsp;Siyu Wu ,&nbsp;Anran Wang ,&nbsp;Lan Yang ,&nbsp;Hong Wang ,&nbsp;Jun Li ,&nbsp;Chaosheng Huang","doi":"10.1016/j.aap.2025.108156","DOIUrl":"10.1016/j.aap.2025.108156","url":null,"abstract":"<div><div>Testing and evaluation are essential for verifying the safety of the intended function (SOTIF) of autonomous driving systems (ADS), which focuses on estimating the system’s functional boundaries through a limited set of tests to assess its safe operational range. To achieve this, a series of valuable safety-margin scenarios must be designed as test cases. However, scenario testing faces the dilemma of the curse of dimensionality and the requirements for test coverage. Consequently, the construction and selection of test cases become significant challenges. Moreover, due to the black-box nature of the system under test (SUT), surrogate models are often introduced during the scenario generation process, which can introduce model deviation relative to the actual system and potentially lead to ineffective test scenarios as well as incorrect estimation of system functional boundaries (SFB). To address these challenges, an efficient framework for generating high-dimensional safety-margin scenarios and tracking SFB of SUT is proposed, which utilizes a baseline surrogate model to generate a diverse and comprehensive library of safety-margin test scenarios through a multi-population genetic algorithm (MPGA). Additionally, a System Functional Boundary Tracking (SFBT) module is employed to compensate for the deviation between the baseline surrogate model and the actual SUT, thereby adaptively generalizing the library of critical scenarios to estimate its high-dimensional functional boundaries. This framework will potentially assist in the testing and validation of the Operational Design Domain (ODD) for ADS.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"221 ","pages":"Article 108156"},"PeriodicalIF":6.2,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144830506","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}

{"title":"Hazard analysis of an Automated Lane Keeping System using Systems-Theoretic Process Analysis","authors":"Mariat James Elizebeth,&nbsp;Siddartha Khastgir,&nbsp;Paul Jennings","doi":"10.1016/j.aap.2025.108171","DOIUrl":"10.1016/j.aap.2025.108171","url":null,"abstract":"<div><div>Systems-Theoretic Process Analysis (STPA) is an effective safety analysis technique that identifies how unsafe interactions among components within a complex system may result in accidents. This study aimed to evaluate the efficacy of STPA by applying it to an Automated Lane Keeping System (ALKS). The goal was to explore areas of potential risk in the system and make recommendations on how overall system safety could be improved. The STPA analysis of ALKS identified 87 Unsafe Control Actions (UCAs) based on interactions between the various components. An analysis of the UCAs revealed 537 causal factors (CFs), including software faults like flawed control algorithms and conflicting controls, sensor performance limitations, specification issues such as missing feedback signals, and errors in human–machine interaction, such as excessive dependence on the ALKS and drivers having incorrect expectations regarding ALKS operation. 1074 requirements were proposed to prevent or mitigate these causal factors, such as educating drivers about both the benefits and limitations of the ALKS to ensure safe use. The results highlighted the importance of communicating both the capabilities as well as the limitations of modern complex systems to the users to guarantee safety. This study, which is the first comprehensive application of STPA to ALKS, identified gaps with existing regulatory requirements for ALKS, and 87 recommendations were made to bridge these gaps. Our research has shown that this top-down, well-structured, and holistic method can especially be advantageous for regulators and policymakers to formulate requirements and policies to deploy and operate complex, innovative technologies, safely.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"221 ","pages":"Article 108171"},"PeriodicalIF":6.2,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144831625","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}

{"title":"The effect of data transformation on the severe event prediction in road traffic using extreme value theory","authors":"Zhankun Chen,&nbsp;Carl Johnsson,&nbsp;Carmelo D’Agostino","doi":"10.1016/j.aap.2025.108186","DOIUrl":"10.1016/j.aap.2025.108186","url":null,"abstract":"<div><div>Extreme Value Theory (EVT) is the state-of-the-art method for proactive prediction of accident frequency from traffic interactions on a microscopic scale. The main advantage of using EVT is to predict unobserved critical events based on one or more Surrogate Measures of Safety (SMoS) (single- or multivariate EVT) through a mathematical extrapolation of extreme interactions. Such interactions are quantitatively described by SMoS, which commonly measure the proximity of two road users, increasing the probability of a collision as the proximity decreases. Those events with a higher likelihood of turning into an accident are defined as severe interactions, and they are considered extremes and are used in the EVT model. Since EVT analysis focuses on the upper tail of the distribution, decreasing transformations are a prerequisite, without which it is impossible to model the extremes. However, prediction results depend on the shape of the indicators’ distributions. Some studies use simple transformations, such as negation, while others employ nonlinear methods that adjust the relationship between proximity and severity. In the present study, the theory of tail analysis has been used to rigorously formulate the effect of a set of conventional linear and nonlinear transformations of SMoS. The approach was tested on a Swedish dataset, and the effects of the transformations on the prediction of extreme events were evaluated based on an accident model built on local data and Empirical Byes correction. The novelty of this study is that one of the most fundamental concepts in traffic conflict theory, such as conflict-crash relationships, has been examined with mathematical interpretation. The results of this study can be further extended to become a standard procedure in modelling traffic conflicts using EVT.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"221 ","pages":"Article 108186"},"PeriodicalIF":6.2,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144826321","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}

{"title":"A model based on cyclist fall experiments which predicts the maximum allowable handlebar disturbance from which a cyclist can recover balance","authors":"Marco M. Reijne ,&nbsp;Frank H. van der Meulen ,&nbsp;Frans C.T. van der Helm ,&nbsp;Arend L. Schwab","doi":"10.1016/j.aap.2025.108159","DOIUrl":"10.1016/j.aap.2025.108159","url":null,"abstract":"<div><div>Falls are a significant cause of injury among cyclists, highlighting the need for effective fall prevention interventions. However, ex-ante evaluation of such interventions remains challenging for engineers designing safer infrastructure and bicycles, as well as for safety professionals developing training programs. This study proposes the Maximum Allowable Handlebar Disturbance (MAHD) — the largest external handlebar disturbance a cyclist can recover from — as a performance indicator for evaluating fall prevention interventions. While bicycle dynamics and cyclist control models have the potential to determine this indicator and simulate interventions, their application is currently limited by a lack of validation in predicting the MAHD and the narrow range of interventions that can be incorporated into existing cyclist control models. To address these limitations, we conducted controlled experiments with 24 participants of varying ages and skill levels, exposing them to impulse-like handlebar disturbances that resulted in both recoveries and falls. This dataset, which includes recorded cyclist falls, supports future validation of bicycle dynamics and control models in predicting the MAHD. In addition, using Bayesian Model Averaging, we identified key cyclist factors influencing the MAHD, with forward speed and cyclist balancing skill being critical predictors. Incorporating these predictors into cyclist control models can substantially improve their practical application. These insights were then used to develop a Bayesian multilevel logistic regression model to predict the MAHD for different types of cyclists. Our findings improve the potential for bicycle dynamics and control models to proactively evaluate cyclist fall prevention methods, contributing to safer cycling environments.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"221 ","pages":"Article 108159"},"PeriodicalIF":6.2,"publicationDate":"2025-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144781878","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}

{"title":"The validity of self-assessment predicts on-road driving performance beyond the effects of age and sex in older drivers with and without MCI","authors":"Daniel A. Schlueter,&nbsp;Kim L. Austerschmidt,&nbsp;Jessica Koenig,&nbsp;Maximilian Flieger,&nbsp;Julia Bergerhausen,&nbsp;Thomas Beblo,&nbsp;Martin Driessen,&nbsp;Max Toepper","doi":"10.1016/j.aap.2025.108172","DOIUrl":"10.1016/j.aap.2025.108172","url":null,"abstract":"<div><h3>Objectives</h3><div>Higher age is often seen as a key factor in the decline of driving skills. Moreover, there is some evidence that overestimation is related to both higher age and poorer on-road performance in older drivers. However, it is unknown how the extent of overestimation or underestimation affects on-road driving performance beyond age.</div></div><div><h3>Methods</h3><div>112 older drivers with and without mild cognitive impairment participated in this prospective on-road study. All participants underwent a standardized on-road driving assessment, neuropsychological testing, collection of driving-related data and different self-assessments. Statistical analyses included a hierarchical regression analysis to predict on-road driving performance by adding age and sex in the first step and the validity of self-assessment (VSA) in the second step. Correlation analyses focused on the association between VSA and cognitive and driving-related behavioral factors.</div></div><div><h3>Results</h3><div>Results revealed that the combination of age and sex significantly predicted on-road driving skills (<em>R²_adjusted</em> = 0.320). The inclusion of VSA led to a significant increase of explained variance in the criterion (<em>R²_adjusted</em> = 0.639). Moreover, the degree of overestimation correlated with higher age, lower cognitive performance and more risky driving behavior.</div></div><div><h3>Discussion</h3><div>Our results highlight the importance of the VSA for on-road driving performance beyond the effects of age and sex. Moreover, the VSA appears to decrease towards overestimation with increasing age and decreasing cognition and should thus be a focus of safety research.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"220 ","pages":"Article 108172"},"PeriodicalIF":6.2,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739513","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}

{"title":"Safety performance analysis of toll plaza diverging area based on an improved simulation platform for weak-constraint driving behaviors","authors":"Yi Fei ,&nbsp;Kejun Long ,&nbsp;Lu Xing ,&nbsp;Xin Pei ,&nbsp;Xi Li ,&nbsp;Lan Yao","doi":"10.1016/j.aap.2025.108177","DOIUrl":"10.1016/j.aap.2025.108177","url":null,"abstract":"<div><div>Toll plaza diverging area is a typical non-lane-based high-risk area characterized by frequent weaving and complex vehicle interactions. While observation-based approaches are effective for analyzing current safety conditions, they lack the flexibility in evaluating the safety impacts of infrastructure designs and traffic control strategies under future scenarios. To address this limitation, this study proposes a microsimulation-based approach to analyze the safety performance of toll plaza diverging areas by simulating the realistic conflict distributions under various traffic conditions. Based on the perception-decision-action (PDA) framework, the proposed approach improves the conflict simulation accuracy by more accurately modeling the weak-constraint driving behavior, including non-lane-based perception, dynamic toll lane selection, and car-following under weak-constraint conditions. Validated on real-world trajectory data from two distinct toll plaza diverging areas, the simulated conflict distributions by the PDA approach closely align with the observed data, while SUMO significantly underestimates the safety risks in diverging areas. Furthermore, a simulation platform is developed based on the PDA approach to quantitatively analyze the safety performance of toll plaza diverging areas under different diverging lengths and traffic volumes. Results indicate that insufficient diverging lengths increase severe conflicts, whereas excessively long diverging areas lead to inefficiencies without substantial safety benefits. This study provides novel insights into safety performance analysis in non-lane-based areas, offering a reliable simulation tool for optimizing management strategies in complex weaving scenarios.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"220 ","pages":"Article 108177"},"PeriodicalIF":6.2,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144722339","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}

{"title":"Dynamic decision-making in subway stations: A new model for stair/escalator choice and its impact on accident prevention","authors":"Huayan Shang ,&nbsp;Yan Yang ,&nbsp;Hai-Jun Huang ,&nbsp;Junzhu Mao","doi":"10.1016/j.aap.2025.108170","DOIUrl":"10.1016/j.aap.2025.108170","url":null,"abstract":"<div><div>Frequent escalator-related incidents in subway stations have prompted the authorities to promote the use of public stairs. In daily life, however, pedestrians instinctively prefer to take escalators rather than use stairs. How to better induce pedestrians to choose stairs? It is necessary to reveal the internal mechanism of pedestrian choice. In this paper, we propose a dynamic model of pedestrian flow assignment with hierarchical choices of various facilities in the station. The route choices of facilities are at the tactical level while the path choices of walking directions are at the operational level. A case study in Beijing is conducted to verify the model. It is shown that the lengths of escalators and stairs, escalator speed, and the pedestrian distribution have significant influences on pedestrians’ choice behavior. Long and fast escalators attract more pedestrians and lead to severe crowding at the entrance. Thus, escalator segmentation is suggested for safety. This study can help prevent accidents and manage crowds in busy subway stations.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"220 ","pages":"Article 108170"},"PeriodicalIF":5.7,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713471","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}

{"title":"Systematically modeling take-over performance: Considering the indirect effect of meteorological visibility mediated by drivers’ attention","authors":"Qingkun Li ,&nbsp;Zhenyuan Wang ,&nbsp;Wenjun Wang ,&nbsp;Guofa Li ,&nbsp;Jibo He ,&nbsp;Liang Ma ,&nbsp;Bo Cheng","doi":"10.1016/j.aap.2025.108174","DOIUrl":"10.1016/j.aap.2025.108174","url":null,"abstract":"<div><div>Drivers’ take-over performance in conditionally automated driving is simultaneously affected by multiple factors, making the involved causal relationships complex. Although existing studies have explored the mechanism, there is still a lack of models for comprehensively analyzing drivers’ take-over performance under diverse meteorological visibility and take-over time budget (TB) conditions. This study established a structural equation model to systematically investigate the complicated causal relationships among TB, meteorological visibility, drivers’ attention, and take-over performance. Based on a driving simulation experiment, we developed a measurement model of drivers’ attention and take-over performance via confirmatory factor analysis. We deconstructed take-over performance into three aspects: reaction time, control instability, and safety margin. Subsequently, we revealed the causal relationships among the above factors by using path analysis. Our results demonstrated the significant total effects of meteorological visibility on reaction time and safety margin, where the indirect effects are mediated by drivers’ attention. However, we found that meteorological visibility barely impacts the control instability aspect of take-over performance. Moreover, the direct effects of TB and drivers’ attention on take-over performance were substantial. This study reveals the complex mechanism of take-over performance under diverse conditions and provides a theoretical basis for enhancing the safety and user experience of conditionally automated vehicles.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"220 ","pages":"Article 108174"},"PeriodicalIF":5.7,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713463","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}

{"title":"Heterogeneous and differential treatment effect analysis of safety improvements on freeways using causal inference","authors":"Syed Zaier Zaidi ,&nbsp;Xuesong Wang ,&nbsp;Yesihati Azati ,&nbsp;Jiaqi Li ,&nbsp;Tianxiang Fan ,&nbsp;Mohammed Quddus","doi":"10.1016/j.aap.2025.108173","DOIUrl":"10.1016/j.aap.2025.108173","url":null,"abstract":"<div><div>Evaluating safety effectiveness of freeway design improvements is crucial for enhancing overall safety and confirming the efficacy of specific measures implemented. Limited research has addressed treatment heterogeneities that influence crash outcomes, and previous studies have often been susceptible to confounding biases, which may distort causal inference results. To mitigate confounding biases and establish reliable causal relationships between crashes and treatment interventions, this study employed a causal forest (CF) model to assess the safety efficacy of freeway exit improvements – including lane control, traffic signs, speed-limit signs, and crash attenuators – on freeways in Suzhou, China. We compared naïve and empirical Bayes before-after methods against the Average Treatment Effect (ATE) estimated by the CF approach. Geometric design and traffic operation characteristics were then considered in measuring the Heterogeneous Treatment Effects (HTE) of these improvements, with the aim of identifying road features where treatment benefits were most pronounced. Additionally, a Differential Treatment Effects (DTE) analysis within a causal framework was employed to estimate treatment effects on the residuals, uncovering more intricate and complex causal relationships. The study demonstrated that CF method provides more stable ATE estimates. An analysis of the distribution of the treatment effects revealed a diverse range of impacts, indicating both positive and negative outcomes. Significant variability in treatment effects was evident from heterogeneous testing results. Noteworthy outcomes from treating freeway exits were observed in areas with an Average Annual Daily Traffic (AADT) ranging from 12,000 to 28,000 vehicles per day, average speeds of 95 km/h and above, two or four lanes on each side, and an exit-only ramp configuration. These findings contribute to valuable technical insights for selecting and evaluating safety enhancement strategies on freeways.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"220 ","pages":"Article 108173"},"PeriodicalIF":5.7,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704434","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}

{"title":"Analysis of secondary risks induced by defensive braking in autonomous vehicles: a study based on stochastic distribution of drivers","authors":"Tingyu Liu ,&nbsp;Zhenyu Zhao ,&nbsp;Miaomiao Yang ,&nbsp;Tianyuan Han","doi":"10.1016/j.aap.2025.108176","DOIUrl":"10.1016/j.aap.2025.108176","url":null,"abstract":"<div><div>Defensive braking measures in autonomous vehicles effectively enhance driving safety but also raise concerns about the secondary risks they may pose, particularly the potential for rear-end collisions caused by following vehicles. Indeed, being rear-ended by human driven vehicles is already the most common type of accident involving autonomous vehicles. However, the uncertainty in driver following behavior makes it challenging to assess this risk directly. In response, this paper characterizes the stochastic distribution of drivers to simulate and evaluate the impact of defensive braking behavior on the likelihood of rear-end collisions. First, based on Risk Homeostasis Theory and the central limit theorem, we propose the hypothesis that the risk tolerance levels (RTL) of driver populations follow a normal distribution. This hypothesis is validated using the Waymo dataset, leading to the development of a Stochastic Following Model (SFM) that effectively represents the stochastic distribution of drivers. Subsequently, a comparison with the Intelligent Driver Model (IDM) reveals that the SFM not only accurately reflects the stochastic distribution of drivers in mixed traffic flow but also demonstrates its effectiveness in capturing the diversity of driving behaviors. Finally, through the design of simulation experiments across various scenarios using Monte Carlo methods, the results indicate that while brief defensive braking by autonomous vehicles does not significantly affect the collision probability of following vehicles compared to manually driven vehicles, continuous defensive braking behavior substantially increases the likelihood of being rear-ended. The proposed SFM captures the extensive diversity of drivers and the stochasticity of the following process, illustrating the uncertainties inherent in mixed traffic flow. This model may serve as a valuable reference for future studies on the safety characteristics of mixed traffic flows.</div></div>","PeriodicalId":6926,"journal":{"name":"Accident; analysis and prevention","volume":"220 ","pages":"Article 108176"},"PeriodicalIF":5.7,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144704435","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}