IATSS Research最新文献

{"title":"Conflict-based crash risk estimation of heterogeneous lane-changing traffic at the Panipat Toll Plaza (NH-44, India) using surrogate safety measures and UAV-based trajectory data","authors":"Parveen Kumar ,&nbsp;Debashis Ray Sarkar","doi":"10.1016/j.iatssr.2025.11.005","DOIUrl":"10.1016/j.iatssr.2025.11.005","url":null,"abstract":"<div><div>A gradual increase in the number of lanes and frequent lane-changing behaviour characterizes the approach of the toll plaza. These characteristics significantly increase the propensity for conflicts and collisions. This study aims to estimate the crash risk of heterogeneous lane-changing traffic at the approaching section of the toll plaza by analyzing vehicle trajectories. In this study, traffic data was collected from a toll plaza located on National Highway-44 in Haryana, India, using an Unmanned Aerial Vehicle (UAV). The vehicle trajectory data was retrieved using Data from Sky (DFS), a fully automated image processing software. The traffic crash risk was assessed using Extreme Value Theory (EVT) in conjunction with Lane Changing Time to Collision, a Surrogate Safety Measure (SSM) indicator. A comprehensive assessment of crash risk across vehicle categories indicates a negative relationship between vehicle size and conflict involvement, with larger vehicles such as trucks, buses, and Light Commercial Vehicles (LCVs) exhibiting a reduced likelihood of conflicts compared to two-wheelers and cars. Moreover, vehicle speed demonstrated a positive correlation with crash risk, indicating that higher average speeds are associated with an increased likelihood of crashes. The study is limited to a single morning peak-hour dataset and primarily covers motorized vehicles, as non-motorized traffic is prohibited on access-controlled highways. Additionally, the current video-classification technique could not differentiate between electric and conventional fuel-powered two-wheelers. These limitations should be considered while determining the scope and generalizability of the findings. The study findings are expected to assist engineers and toll plaza operators in selecting suitable traffic control measures to improve safety at the toll plaza.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 4","pages":"Pages 580-592"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predicting higher-risk crash factors and patterns using machine learning-association rule mining","authors":"Emmanel Kofi Gbey ,&nbsp;Charles Atombo ,&nbsp;Emmanuel Kofi Adanu ,&nbsp;William Agyemang","doi":"10.1016/j.iatssr.2025.11.006","DOIUrl":"10.1016/j.iatssr.2025.11.006","url":null,"abstract":"<div><div>Road traffic crashes remain a significant global public health concern, particularly in low- and middle-income countries, where fatalities and injuries disproportionately affect vulnerable road users. Despite efforts to improve road safety, crash severity levels are conventionally classified based on observable injury and fatality outcomes. This outcome-based approach oversimplifies the complexity of crash risk by ignoring latent hazards embedded in severity-based categories for non-fatal or minor crashes. This study addresses this gap by integrating Machine Learning (ML) and Association Rule Mining (ARM) to predict high-risk crashes and identify crash patterns respectively. Using nine years of historical crash data (2013−2021) from Ghana, the study employed Logistic Regression, Random Forest (RF), and XGBoost for high-risk crash prediction, followed by ARM to identify hidden patterns. RF outperformed the other models, achieving 71.4 % accuracy and a 90.3 % ROC AUC. The identified high-risk crashes depicted a mismatch between crashes classified as high severity and crashes identified as high-risk crashes. Crashes termed low severity dominated the set of crashes classified by the RF model as high-risk crashes. ARM revealed significant hidden patterns, such as rear-end collisions at signalized intersections and road width and non-impaired driving co-occur crashes under optimal environmental and behavioural driving conditions. The study demonstrates the value of combining ML and ARM for actionable insights. The findings emphasize that infrastructural design and driver behaviour both play important roles in high-risk crash outcomes, suggesting a need for holistic road safety strategies, including infrastructure redesign, enhanced traffic control measures, and public awareness campaigns to mitigate complacency in ideal driving conditions. Policymakers and traffic engineers are urged to adopt context-sensitive designs and prioritize non-junction segments, where road width significantly impacts crash risk.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 4","pages":"Pages 565-579"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145624048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling injury severity in HAZMAT truck-involved crashes: Accounting for heterogeneity in a developing country","authors":"Ehsan Jafari Nasab ,&nbsp;Abdoreza Sheikholeslami ,&nbsp;Jose Manuel Vassallo ,&nbsp;Amin Moeinaddini","doi":"10.1016/j.iatssr.2025.11.007","DOIUrl":"10.1016/j.iatssr.2025.11.007","url":null,"abstract":"<div><div>One of the types of crashes that has a high fatality rate is the Hazardous Material (HAZMAT) truck-involved crashes. Investigating the factors affecting the severity of HAZMAT truck-involved crashes can assist authorities in making more accurate evaluations of policies to increase road safety and reduce the injury severity of crashes involving these vehicles. In this study, the main goal is to investigate the factors that affect the severity of HAZMAT truck-involved crashes. Considering the heterogeneity of the injury severity of crashes can provide a more accurate assessment of the factors involved in those crashes. In this regard, by using the data of 482 HAZMAT truck-involved crashes in Iran and also by using a Random Parameter Ordered Logit (RPOL) model, the factors affecting the injury severity of those vehicle crashes and systematic and random heterogeneity have been investigated. According to the results of the model, crashes with multiple vehicles involved have a significant effect on the increasing the severity of HAZMAT truck-involved crashes. Furthermore, the presence of public vehicles in HAZMAT truck-involved crashes, and the driver's risk-taking in driving at high speed based on driving records has a significant effect on the decreasing severity of crashes. In addition, the results showed that there is an interaction effect between the variables of vehicle age and upside-down crashes on increasing the injury severity of the crashes. On the other hand, the results indicate that there is an interaction effect between the variables of front-to-front, front-to-back, and low heavy truck traffic on the road with the variable of the crash caused by HAZMAT truck on increasing the injury severity of the crashes. The results of the study confirm that there is random heterogeneity based on the normal distribution function for the mean of injury severity of HAZMAT truck-involved crashes.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 4","pages":"Pages 593-602"},"PeriodicalIF":3.3,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145684156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Temporal stability analysis of crash injury severity in school zones: A mixed logit modeling approach","authors":"Monire Jafari ,&nbsp;Michael Starewich ,&nbsp;Subasish Das ,&nbsp;Swastika Barua ,&nbsp;Reuben Tamakloe","doi":"10.1016/j.iatssr.2025.11.002","DOIUrl":"10.1016/j.iatssr.2025.11.002","url":null,"abstract":"<div><div>School zones present critical challenges where vehicular traffic intersects with vulnerable pedestrians, especially children. While previous studies have examined school zone crash risk and countermeasures, few have investigated how injury severity risk factors change over time especially before and during the COVID-19 pandemic leaving a gap in understanding the temporal stability of these influences. This study analyzes 3638 police-reported crashes in Louisianna school zones from 2018 to 2021 to identify factors influencing injury severity. Using a Random Parameters Logit Model with Heterogeneity in Means and Variances, the analysis accounts for unobserved heterogeneity and temporal changes, comparing pre-pandemic (2018–2019) and pandemic (2020−2021) periods. Results show that crashes near state highways significantly increase the likelihood of fatal, severe, or moderate injuries. In contrast, lower speed limits (≤ 25 mph), improved lighting conditions, and seasons such as summer and autumn correlate with reduced injury severity. Driver behaviors like failure to yield and weekday crashes increase possible injury risks. Temporal instability in risk factors highlights the need for regionally and temporally calibrated interventions. These findings support targeted safety measures such as traffic calming near high-speed roads, enhanced enforcement, and educational campaigns to reduce injury severity and improve safety for all road users in school zones.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 4","pages":"Pages 528-543"},"PeriodicalIF":3.3,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Gender and driving safety in Saudi Arabia: Challenging stereotypes with simulator evidence","authors":"Khurram Shahid Minhas,&nbsp;M.A. Dalhat,&nbsp;Abdulhamid Al-mojil","doi":"10.1016/j.iatssr.2025.11.003","DOIUrl":"10.1016/j.iatssr.2025.11.003","url":null,"abstract":"<div><h3>Introduction</h3><div>Females were granted the right to drive on public roads in Saudi Arabia (SA) in 2018. The country is undergoing significant policy transformation to promote inclusion, equity, and diversity. However, cultural perceptions and traditional misconceptions on female driving performance are still not fully addressed by scientific research.</div></div><div><h3>Method</h3><div>This driving simulator study involved a total of 100 participants, comprising 60 males and 40 females from Dammam, SA. It examines the influence of gender on crash frequency, violation patterns, and reaction times, while also assessing the impact of weather conditions.</div></div><div><h3>Results</h3><div>The findings indicate that male drivers exhibited slightly higher average crash frequency and loss of control incidents compared to female drivers, although females committed more stop-sign violations. Males also engaged in more aggressive maneuvers, such as sudden lane changes (0.70 vs. 0.28). Despite a longer average reaction time among female drivers (2.04 s vs. 1.80s, <em>p</em> = 0.032), gender was not a significant predictor of crash likelihood (<em>p</em> = 0.337). Instead, weather conditions emerged as a key factor, with rainy conditions significantly increasing crash rates and loss of control incidents.</div></div><div><h3>Conclusion</h3><div>While reaction time was associated with crash frequency, the study found no statistical evidence that gender independently influenced crash risk. These findings challenge traditional stereotypes regarding female driving performance in SA. Findings also show that female drivers are equally, if not more, capable than their male counterparts in many aspects of driving behavior.</div></div><div><h3>Practical application</h3><div>The research findings can serve as a reference to policymakers, traffic safety authorities, and licensing bodies toward promoting a gender-neutral approach in driver licensing and training programs. The results also support public awareness efforts aimed at reducing societal stigma by shifting the narrative from gender-based assumptions to evidence-based assessments of driving ability.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 4","pages":"Pages 544-554"},"PeriodicalIF":3.3,"publicationDate":"2025-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cross-cultural perspectives of vulnerable road user safety performance based on evidence from 39 countries","authors":"George Yannis ,&nbsp;Apostolos Ziakopoulos ,&nbsp;Dimitrios Nikolaou ,&nbsp;Konstantinos Kaselouris ,&nbsp;Mette Møller ,&nbsp;Dagmara Jankowska-Karpa ,&nbsp;Marie-Axelle Granié","doi":"10.1016/j.iatssr.2025.11.001","DOIUrl":"10.1016/j.iatssr.2025.11.001","url":null,"abstract":"<div><div>Pedestrians, cyclists, moped riders and motorcyclists are regarded as vulnerable road users (VRUs), as they face a heightened risk of injury in the event of a collision with a vehicle. The present study aims to provide a quantified update on VRUs safety performance by analyzing data from a broad-country sample. For this study, data was utilized from the third edition of the E-Survey on Road Users' Attitudes (ESRA3) survey, which was conducted in 2023, covering 39 countries from 5 continents. Specifically, the paper investigates the attitudes and opinions of pedestrians, cyclists, and moped riders and motorcyclists regarding (i) their safety perceptions of specific transport modes and (ii) various types of unsafe behavior (for instance, speeding, alcohol/drug consumption, helmet use, red light violations and others). Furthermore, a statistical analysis based on Self-Organizing Maps (SOMs) and clustering was conducted to meaningfully categorize VRU groups, enabling the quantification of each category and providing scientific documentation for more informed policymaking. Key findings include the fact that VRU safety perceptions and behaviors differ significantly across regions, with Europeans feeling safer overall, with older VRUs displaying fewer risky habits than younger ones. Cyclists often neglect helmet use in particular countries (Thailand, Bosnia), while drug and alcohol consumption while riding is notably high in specific countries as well (Ireland, Thailand, the Netherlands). SOM analysis reveals that most VRUs fall into low-risk behavior clusters, however, it is worth noting that respondents that engaged in a number of unsafe individual behaviors to smaller extents were classified as unsafe along with the more frequent offenders. For all VRU modes, statistical tests revealed that there is a statistically significant association between younger individuals and higher-risk cluster categorization. Finally, the paper provides recommendations for road safety stakeholders operating at different levels, which could be implemented in efforts to enhance VRUs road safety.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 4","pages":"Pages 502-527"},"PeriodicalIF":3.3,"publicationDate":"2025-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk perception of car drivers toward E-scooters and bicycles","authors":"Weiyi Li ,&nbsp;Miho Iryo-Asano ,&nbsp;Wael K.M. Alhajyaseen","doi":"10.1016/j.iatssr.2025.11.004","DOIUrl":"10.1016/j.iatssr.2025.11.004","url":null,"abstract":"<div><div>The increasing adoption of electric scooters (ESs) presents opportunities and challenges for urban transportation systems. ESs face unique integration challenges in Japan owing to the lack of bicycle infrastructure and recent regulatory shifts. Consequently, understanding how surrounding car drivers perceive ES risks in the current road environment is crucial for improving road safety. This study employed a web-based questionnaire survey targeting car drivers who regularly encountered ESs at least once a week. We analyzed the perceived level of danger and the frequency of hazardous behaviors associated with ES riders and cyclists. The results indicate that drivers perceive ES-related behaviors as significantly more dangerous than bicycle-related behaviors, despite observing the former less frequently. Age, risk experience, usage experience, and road geometry have been found to influence the perceived level of danger of hazardous behaviors. Car drivers perceive traffic violations by cyclists and ES riders at high frequencies and danger levels. Compared to drivers unfamiliar with using ESs, those familiar with using ESs perceive behaviors related to operational instability from ES riders more frequently—a pattern not observed for bicycles. Infrastructure plays a critical role in reducing the perceived level of danger: dedicated lanes and arrow markings on shared lanes reduce the perceived danger for both modes. This study contributes to identifying factors influencing risk perception among surrounding car drivers in the early stages of the spread of new mobility, when adoption is not yet sufficient and actual user maneuver surveys are difficult to conduct efficiently. Combining the factors identified in this study with future objective evaluations leads to the development of effective countermeasures.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 4","pages":"Pages 555-564"},"PeriodicalIF":3.3,"publicationDate":"2025-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145579262","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Framing automation of driving tasks: Effects on risk perception and consumers’ understanding of different levels of vehicle automation across four European countries","authors":"Ilse M. Harms ,&nbsp;Wouter Van den Berghe","doi":"10.1016/j.iatssr.2025.10.005","DOIUrl":"10.1016/j.iatssr.2025.10.005","url":null,"abstract":"<div><div>Framing is the process whereby people's perception is influenced by how information is presented. In the automotive sector, well-known frames concern the names for advanced driver assistance systems (ADAS) which suggest higher levels of automation (e.g., by including the word ‘pilot’). The current study focusses on the framing of messages about the system's capabilities and how they impact on drivers' mental model regarding the need to control their car.</div><div>A total of 3000 licensed drivers across four European countries participated in a survey with an embedded video, to provide insight in whether the framing of ADAS would affect consumers' willingness to take more risks in traffic and to compare their understanding of vehicle automation. Three levels of automation were distinguished: (1) assisted driving, a level of automation which supports the human driver without taking over control of the vehicle; (2) automated driving, at which level a vehicle takes over control of the vehicle within the limits of its operational design domain; (3) autonomous driving, when a vehicle is capable of driving itself under all circumstances. The effect of framing was studied by dividing respondents into two groups. The questions in the survey were the same for both groups, but the video was not. One group was shown a video stressing the increased comfort resulting from ADAS, i.e. the ‘Comfort condition’. The other group saw a video with the same factual content to explain the system's capabilities and limitations, but in which the importance of remaining responsible for and in control of driving was emphasised, i.e. the ‘Responsible condition’.</div><div>This study has shown that framing of messages about ADAS' system capabilities indeed impacts drivers' mental model of these systems. Participants exposed to the ‘Comfort’ frame indicated a tendency for higher risk-taking behaviour compared to participants in the ‘Responsible’ frame. Moreover, the study also showed that the ‘Comfort’ frame shifted people's mental model about their role as a driver towards that for a higher level of automation. A well-calibrated mental model is a prerequisite for the safe use of these systems on the road.</div><div>Given the findings of this study, the authors also propose a modification of the labels for the SAE levels of automation, distinguishing more clearly assisted, automated and autonomous driving.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 4","pages":"Pages 493-501"},"PeriodicalIF":3.3,"publicationDate":"2025-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145418738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive traffic signal control using deep reinforcement learning: A multi-objective approach for single and multi-intersection scenarios","authors":"Marwa Elharoun,&nbsp;Sherif M. El-Badawy,&nbsp;Elsayed Abd-Elazem Shwaly,&nbsp;Usama Elrawy Shahdah","doi":"10.1016/j.iatssr.2025.10.004","DOIUrl":"10.1016/j.iatssr.2025.10.004","url":null,"abstract":"<div><div>Traffic congestion in urban networks necessitates adaptive signal control systems that balance efficiency, safety, and environmental impact. While Deep Reinforcement Learning (DRL) has shown promise for traffic signal control (TSC), existing approaches often optimize single objectives or lack scalability for multi-intersection corridors. This study proposes a multi-objective DRL framework that simultaneously minimizes vehicle delays, traffic conflicts (using Time-to-Collision metrics), and CO₂ emissions. Six reward functions were designed and tested with three DRL algorithms (PPO, A2C, DQN) in synthetic and real-world intersections simulated in SUMO. Key results demonstrate that: (1) PPO outperformed A2C and DQN, achieving up to 21 % fewer conflicts and 7 % lower delays in high-traffic scenarios; (2) A safety-focused reward (Reward 3) reduced conflicts by 4–20 % compared to fixed-time controls in high-traffic scenarios, while multi-objective rewards (Rewards 5–6) balanced all targets effectively; and (3) Decentralized control for multi-intersection corridor reduced delays, conflicts, and emissions by 26.4 %, 26.9 %, and 12 %, respectively, surpassing centralized approaches. Real-world validation in Hangzhou, China, and Cologne, Germany, confirmed robustness, with 10–15 % delay reductions and 2.2–6.4 % lower emissions versus prior DRL models. This work advances adaptive TSC by integrating safety and sustainability into DRL optimization, offering scalable solutions for heterogeneous traffic networks.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 4","pages":"Pages 481-492"},"PeriodicalIF":3.3,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145364588","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Safety performance assessment of new AEB and AES for car-to-VRU collisions","authors":"Jordanka Kovaceva ,&nbsp;Carol Flannagan ,&nbsp;Peter Wimmer ,&nbsp;Christian Löffler ,&nbsp;Timm Gloger","doi":"10.1016/j.iatssr.2025.10.001","DOIUrl":"10.1016/j.iatssr.2025.10.001","url":null,"abstract":"<div><div>While overall crash statistics have been declining, collisions involving cyclists and pedestrians have not decreased at the same rate, particularly in urban areas. To enhance the safety of these vulnerable road users (VRUs), advanced driver assistance systems (ADAS) are being developed and introduced to the market. These systems aim to prevent or mitigate crashes by alerting drivers in critical situations and, if necessary, automatically applying braking or steering interventions.</div><div>This study evaluates the effectiveness of a new autonomous emergency braking and steering (AEB + S) system in reducing fatalities and serious injuries in car-to-VRU collisions on urban roads across Europe. A prospective safety performance assessment was conducted using virtual simulations.</div><div>The results indicate that AEB alone already prevents most crashes and VRU fatalities and serious injuries in urban VRU-crossing scenarios. The additional safety benefit of AEB + S compared to the baseline AEB system is relatively small—less than 1 % for VRU-crossing crash cases. However, AEB + S proves advantageous in scenarios where the VRU becomes visible too late for AEB alone to act, and an in-lane avoidance manoeuvre is feasible.</div><div>These findings provide valuable insights for policymakers and regulatory bodies in assessing the real-world benefits of emerging ADAS technologies.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 4","pages":"Pages 470-480"},"PeriodicalIF":3.3,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145364587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}