Pub Date : 2025-10-01DOI: 10.1016/j.iatssr.2025.09.007
Misako Yamagishi
Driving tracking, or the observation of actual and naturalistic driving, is an effective approach for understanding and assessing the driving behaviors of older drivers. However, limited information is available regarding the effects of data collection duration on the characteristics of driving behavior. This study examined how different data collection durations (2 weeks and 1, 3, 6, and 12 months) influence older drivers' long-term driving behavior, specifically rapid deceleration events (RDEs). Analysis of the varying durations revealed common tendencies related to low-mileage bias (LMB) as well as differences in the likelihood of RDE occurrence. These factors were incorporated into predictive models, with values estimated using negative binomial regression across the different data collection durations. The results indicated that the characteristics of driving behavior differ between short-term (2 weeks and 1 month) and long-term (3, 6, and 12 months) data collection. Finally, this study provides insights into establishing a methodology for tracking driving behavior in older adults.
{"title":"Collection duration of driving tracking data of older drivers","authors":"Misako Yamagishi","doi":"10.1016/j.iatssr.2025.09.007","DOIUrl":"10.1016/j.iatssr.2025.09.007","url":null,"abstract":"<div><div>Driving tracking, or the observation of actual and naturalistic driving, is an effective approach for understanding and assessing the driving behaviors of older drivers. However, limited information is available regarding the effects of data collection duration on the characteristics of driving behavior. This study examined how different data collection durations (2 weeks and 1, 3, 6, and 12 months) influence older drivers' long-term driving behavior, specifically rapid deceleration events (RDEs). Analysis of the varying durations revealed common tendencies related to low-mileage bias (LMB) as well as differences in the likelihood of RDE occurrence. These factors were incorporated into predictive models, with values estimated using negative binomial regression across the different data collection durations. The results indicated that the characteristics of driving behavior differ between short-term (2 weeks and 1 month) and long-term (3, 6, and 12 months) data collection. Finally, this study provides insights into establishing a methodology for tracking driving behavior in older adults.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 3","pages":"Pages 410-417"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221511","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}
This study empirically analyzed the determinants of traffic accident risk, highlighting the average travel speed, using nationwide data for trunk highways and expressways in Japan. Negative binomial regression models were established using data describing traffic accidents on 86,835 trunk-highway links, 84,091 trunk-highway intersections, and 4322 expressway links occurring from 2019 to 2021. The results indicated that the average travel speed had a significantly negative association with the annual frequency and rates of traffic accidents regardless of the road type, road median presence, or area characteristics. Furthermore, the speed limit was positively associated with the traffic accident risk on trunk highways, while it was negatively associated with the traffic accident risk on expressways. Finally, the presence of road median reduced the traffic accident risk, and more urbanized areas exhibited a higher risk of traffic accidents than less urbanized areas. Policy implications of these findings include the mitigation of trunk-highway traffic congestion to reduce the traffic accident risk and the potential benefit of increasing the speed limit on traffic safety in expressways.
{"title":"Average travel speed and traffic accident risk: Evidence from nationwide data for trunk highways and expressways in Japan","authors":"Shinya Yamada , Ayanori Sakashita , Takayoshi Tsuchiya , Hironori Kato","doi":"10.1016/j.iatssr.2025.09.006","DOIUrl":"10.1016/j.iatssr.2025.09.006","url":null,"abstract":"<div><div>This study empirically analyzed the determinants of traffic accident risk, highlighting the average travel speed, using nationwide data for trunk highways and expressways in Japan. Negative binomial regression models were established using data describing traffic accidents on 86,835 trunk-highway links, 84,091 trunk-highway intersections, and 4322 expressway links occurring from 2019 to 2021. The results indicated that the average travel speed had a significantly negative association with the annual frequency and rates of traffic accidents regardless of the road type, road median presence, or area characteristics. Furthermore, the speed limit was positively associated with the traffic accident risk on trunk highways, while it was negatively associated with the traffic accident risk on expressways. Finally, the presence of road median reduced the traffic accident risk, and more urbanized areas exhibited a higher risk of traffic accidents than less urbanized areas. Policy implications of these findings include the mitigation of trunk-highway traffic congestion to reduce the traffic accident risk and the potential benefit of increasing the speed limit on traffic safety in expressways.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 3","pages":"Pages 425-435"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145267731","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}
Pub Date : 2025-10-01DOI: 10.1016/j.iatssr.2025.09.005
Ron Schindler , Giulio Bianchi Piccinini , Laurent Decoster
Advanced emergency braking systems (AEBS) aim to address rear-end collisions, which are the most common crash type involving heavy good vehicles. Although previous studies have investigated the safety benefits introduced by AEBS, there is a lack of research exploring drivers' behaviour before and after AEBS interventions. In this paper, we analyzed 6-s long event-triggered naturalistic driving data, collected from heavy goods vehicles every time an AEBS braking intervention occurred, either as preliminary mitigation braking (pMB) or full mitigation braking (MB). The analyses focused on rear-end critical situations in which the drivers did not brake before a collision warning (CW) or a mitigation braking was triggered by the system. The rear-end critical situations encompassed scenarios where the lead vehicle was the same for the whole duration of the event.
The results show that full mitigation braking are rare events, occurring in approximately 5 % of the complete dataset. Besides, drivers of heavy goods vehicles are in 75 % of the cases already braking before the intervention of CW. Analyzing in detail a restricted number of interventions from CW and MB, it was found that drivers are keeping headway shorter than 1 s in 44.4 % and 53.6 % of the cases respectively. The annotations performed on the restricted dataset indicate that the drivers were “out of the loop” in 57.3 % of CW interventions and 65 % of MB interventions. However, this finding should be taken with caution, due to the lack of video recordings: in fact, the lack of a fast drivers' response could also be an indication of overtrust in the system or a sign of the drivers assessing the situation as not enough critical to require a braking. Further naturalistic driving studies with increased data frequency and availability of video data are recommended to investigate deeper on this matter.
{"title":"An investigation of truck drivers' behaviour before and during real-world advanced emergency braking system interventions","authors":"Ron Schindler , Giulio Bianchi Piccinini , Laurent Decoster","doi":"10.1016/j.iatssr.2025.09.005","DOIUrl":"10.1016/j.iatssr.2025.09.005","url":null,"abstract":"<div><div>Advanced emergency braking systems (AEBS) aim to address rear-end collisions, which are the most common crash type involving heavy good vehicles. Although previous studies have investigated the safety benefits introduced by AEBS, there is a lack of research exploring drivers' behaviour before and after AEBS interventions. In this paper, we analyzed 6-s long event-triggered naturalistic driving data, collected from heavy goods vehicles every time an AEBS braking intervention occurred, either as preliminary mitigation braking (pMB) or full mitigation braking (MB). The analyses focused on rear-end critical situations in which the drivers did not brake before a collision warning (CW) or a mitigation braking was triggered by the system. The rear-end critical situations encompassed scenarios where the lead vehicle was the same for the whole duration of the event.</div><div>The results show that full mitigation braking are rare events, occurring in approximately 5 % of the complete dataset. Besides, drivers of heavy goods vehicles are in 75 % of the cases already braking before the intervention of CW. Analyzing in detail a restricted number of interventions from CW and MB, it was found that drivers are keeping headway shorter than 1 s in 44.4 % and 53.6 % of the cases respectively. The annotations performed on the restricted dataset indicate that the drivers were “out of the loop” in 57.3 % of CW interventions and 65 % of MB interventions. However, this finding should be taken with caution, due to the lack of video recordings: in fact, the lack of a fast drivers' response could also be an indication of overtrust in the system or a sign of the drivers assessing the situation as not enough critical to require a braking. Further naturalistic driving studies with increased data frequency and availability of video data are recommended to investigate deeper on this matter.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 3","pages":"Pages 418-424"},"PeriodicalIF":3.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145221512","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}
Pub Date : 2025-09-23DOI: 10.1016/j.iatssr.2025.09.004
Uta Meesmann , Carlos Pires , Naomi Wardenier , Mario Cools
This study investigates cross-national differences in Traffic Safety Culture (TSC) by examining self-reported mobile phone use while driving across 31 countries. Using data from the third edition of the E-Survey of Road Users' Attitudes (ESRA3), collected in 2023, this research explores how socio-cognitive constructs, including norms, perceived behavioural control (PBC), attitude, and intention, influence drivers' mobile phone use while driving. Linear regression models are applied at both cross-national and national levels to understand the predictive strength of these constructs. Results indicate that socio-cognitive beliefs significantly explain variations in self-reported mobile phone use while driving, accounting for 37–63 % of the observed variance. Norms emerge as the strongest predictor, followed by PBC, attitude, and intention, with substantial differences in effect size across countries. These findings underscore the role of cultural and psychological factors in shaping unsafe driving behaviours, offering insights for tailored interventions that address specific socio-cognitive aspects of high-risk drivers, which can be used to design road safety campaigns or education programs more effectively.
{"title":"Exploring cross-national variations in traffic safety culture: Insights into mobile phone use and shared beliefs across 31 countries","authors":"Uta Meesmann , Carlos Pires , Naomi Wardenier , Mario Cools","doi":"10.1016/j.iatssr.2025.09.004","DOIUrl":"10.1016/j.iatssr.2025.09.004","url":null,"abstract":"<div><div>This study investigates cross-national differences in <em>Traffic Safety Culture</em> (TSC) by examining self-reported mobile phone use while driving across 31 countries. Using data from the third edition of the E-Survey of Road Users' Attitudes (ESRA3), collected in 2023, this research explores how socio-cognitive constructs, including <em>norms</em>, <em>perceived behavioural control</em> (PBC), <em>attitude</em>, and <em>intention,</em> influence drivers' mobile phone use while driving. Linear regression models are applied at both cross-national and national levels to understand the predictive strength of these constructs. Results indicate that socio-cognitive beliefs significantly explain variations in self-reported mobile phone use while driving, accounting for 37–63 % of the observed variance. <em>Norms</em> emerge as the strongest predictor, followed by <em>PBC</em>, <em>attitude</em>, and <em>intention</em>, with substantial differences in effect size across countries. These findings underscore the role of cultural and psychological factors in shaping unsafe driving behaviours, offering insights for tailored interventions that address specific socio-cognitive aspects of high-risk drivers, which can be used to design road safety campaigns or education programs more effectively.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 3","pages":"Pages 399-409"},"PeriodicalIF":3.3,"publicationDate":"2025-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118887","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}
Road crashes are a complex phenomenon affected by several parameters that can be categorized into three distinct aspects: road users, vehicles, and road infrastructure. Effective infrastructure enhances safety, accessibility and transportation efficiency. The objective of this paper is to investigate trends in road infrastructure usage and safety perceptions among car drivers and vulnerable road users across different types of roads worldwide. For the study, data from the third edition of the E-Survey on Road Users' Attitudes (ESRA3), conducted in 2023 and covering 39 countries from 5 continents, were utilized. The results revealed that car drivers in Europe have the highest usage of inter-city motorways, while America leads in using thoroughfares and high-speed roads within cities. Moreover, in Europe, rural roads and roads connecting towns and villages are heavily utilized. Moped riders and motorcyclists frequently use urban thoroughfares, especially in America and Europe, whereas cyclists and pedestrians show the highest usage of urban roads with dedicated infrastructure, such as cycle lanes and sidewalks, respectively. Car drivers generally perceive inter-city motorways as relatively safe, while moped riders and motorcyclists perceive thoroughfares within cities as safer in America, compared to Asia-Oceania. Similarly, cyclists express higher safety perceptions on urban roads with cycle lanes, particularly in Europe, and pedestrians consistently feel safest on urban streets and roads with sidewalks. Furthermore, moderate to weak linear relationships were discovered between the perceived safety of road infrastructure and road fatality rates, as well as between the perceived safety of road infrastructure and Gross Domestic Product. Lastly, recommendations for enhancing infrastructure safety, such as road maintenance and upgrades, are provided.
{"title":"Infrastructure use and related safety feeling of different road user types globally","authors":"George Yannis , Dimitrios Nikolaou , Konstantinos Kaselouris , Gerald Furian","doi":"10.1016/j.iatssr.2025.08.002","DOIUrl":"10.1016/j.iatssr.2025.08.002","url":null,"abstract":"<div><div>Road crashes are a complex phenomenon affected by several parameters that can be categorized into three distinct aspects: road users, vehicles, and road infrastructure. Effective infrastructure enhances safety, accessibility and transportation efficiency. The objective of this paper is to investigate trends in road infrastructure usage and safety perceptions among car drivers and vulnerable road users across different types of roads worldwide. For the study, data from the third edition of the E-Survey on Road Users' Attitudes (ESRA3), conducted in 2023 and covering 39 countries from 5 continents, were utilized. The results revealed that car drivers in Europe have the highest usage of inter-city motorways, while America leads in using thoroughfares and high-speed roads within cities. Moreover, in Europe, rural roads and roads connecting towns and villages are heavily utilized. Moped riders and motorcyclists frequently use urban thoroughfares, especially in America and Europe, whereas cyclists and pedestrians show the highest usage of urban roads with dedicated infrastructure, such as cycle lanes and sidewalks, respectively. Car drivers generally perceive inter-city motorways as relatively safe, while moped riders and motorcyclists perceive thoroughfares within cities as safer in America, compared to Asia-Oceania. Similarly, cyclists express higher safety perceptions on urban roads with cycle lanes, particularly in Europe, and pedestrians consistently feel safest on urban streets and roads with sidewalks. Furthermore, moderate to weak linear relationships were discovered between the perceived safety of road infrastructure and road fatality rates, as well as between the perceived safety of road infrastructure and Gross Domestic Product. Lastly, recommendations for enhancing infrastructure safety, such as road maintenance and upgrades, are provided.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 3","pages":"Pages 387-398"},"PeriodicalIF":3.3,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145118889","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}
Pub Date : 2025-09-13DOI: 10.1016/j.iatssr.2025.08.001
Mehraab Nazir, Sai Chand, Rahul Goel
Road traffic crashes (RTCs) are a major cause of fatalities worldwide. However, the influence of the road network structure on RTCs has not been adequately explored. Furthermore, methodologies employed in earlier studies to quantify road networks have often relied on visual inspection, which is both subjective and impractical. Therefore, this study aimed to address these gaps by (1) utilizing graph theory metrics to quantify the road network structure and (2) developing a statistical model to determine how various characteristics of the network structure—such as connectivity, density, complexity and centrality—are correlated with RTCs while accounting for over-dispersion and spatial auto-correlation. Using a Bayesian conditional auto-regressive model, a spatial analysis of fatal RTCs was conducted at the ward level in Delhi, India. The findings demonstrated a significant positive association between road network connectivity and fatal crash risk. Areas with a higher density of intersections involving major roads were linked to a greater number of fatal crashes. Furthermore, areas with a higher number of intersections deviating from the typical 90-degree angle (higher skewness) were associated with a higher incidence of fatal RTCs. Conversely, an efficient network structure (lower circuitry) and higher network centrality were negatively correlated with fatal RTCs. In addition, wards with a mix of higher-category and lower-category roads (increased entropy) faced an increased risk of fatal crashes. In summary, this study underscores the significant impact of network structure on road safety outcomes. Based on the findings, the study offers policy recommendations for developing targeted road safety measures to address the issues identified via network analysis.
{"title":"Quantifying the road network structure and its impact on road traffic crashes: A Bayesian CAR modelling approach","authors":"Mehraab Nazir, Sai Chand, Rahul Goel","doi":"10.1016/j.iatssr.2025.08.001","DOIUrl":"10.1016/j.iatssr.2025.08.001","url":null,"abstract":"<div><div>Road traffic crashes (RTCs) are a major cause of fatalities worldwide. However, the influence of the road network structure on RTCs has not been adequately explored. Furthermore, methodologies employed in earlier studies to quantify road networks have often relied on visual inspection, which is both subjective and impractical. Therefore, this study aimed to address these gaps by (1) utilizing graph theory metrics to quantify the road network structure and (2) developing a statistical model to determine how various characteristics of the network structure—such as connectivity, density, complexity and centrality—are correlated with RTCs while accounting for over-dispersion and spatial auto-correlation. Using a Bayesian conditional auto-regressive model, a spatial analysis of fatal RTCs was conducted at the ward level in Delhi, India. The findings demonstrated a significant positive association between road network connectivity and fatal crash risk. Areas with a higher density of intersections involving major roads were linked to a greater number of fatal crashes. Furthermore, areas with a higher number of intersections deviating from the typical 90-degree angle (higher skewness) were associated with a higher incidence of fatal RTCs. Conversely, an efficient network structure (lower circuitry) and higher network centrality were negatively correlated with fatal RTCs. In addition, wards with a mix of higher-category and lower-category roads (increased entropy) faced an increased risk of fatal crashes. In summary, this study underscores the significant impact of network structure on road safety outcomes. Based on the findings, the study offers policy recommendations for developing targeted road safety measures to address the issues identified via network analysis.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 3","pages":"Pages 374-386"},"PeriodicalIF":3.3,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050151","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}
Pub Date : 2025-09-12DOI: 10.1016/j.iatssr.2025.09.003
Mohamed Ahmed Al-Awad , Mohamed Kharbeche , Faris Tarlochan
The global disparity in Child Restraint System (CRS) adoption contributes directly to variations in road traffic mortality and morbidity among children. Despite the proven effectiveness of CRS in reducing harm, its adoption remains inconsistent across regions due to socio-economic, legislative, and cultural factors. This review evaluates global CRS adoption rates, identifies barriers to effective utilization, and explores interventions to enhance usage and legislative compliance, ultimately proposing strategies to improve child passenger safety.
A total of 93 articles published between 2013 and 2024 were reviewed, with a focus on CRS usage and intervention patterns, the effectiveness of interventions, and legislative impact across high, middle, and low-income countries.
The review highlights a significant gap in CRS usage between high-income and low to middle-income countries, with affordability, lack of awareness, and inadequate legislation as primary barriers. High-income regions showed better adherence but struggled with proper installation and misuse. Intervention strategies, including legislation, public education, and economic incentives, showed varying success in improving CRS adoption.
Enhancing global CRS usage requires stringent legislation, comprehensive campaigns, economic support, and innovative technological solutions. Tailored strategies that account for regional socio-economic and cultural norms are essential to achieve widespread adoption and proper CRS use, ultimately reducing child passenger fatalities and injuries.
{"title":"Evaluating child restraint system (CRS) adoption and policy interventions worldwide: a review","authors":"Mohamed Ahmed Al-Awad , Mohamed Kharbeche , Faris Tarlochan","doi":"10.1016/j.iatssr.2025.09.003","DOIUrl":"10.1016/j.iatssr.2025.09.003","url":null,"abstract":"<div><div>The global disparity in Child Restraint System (CRS) adoption contributes directly to variations in road traffic mortality and morbidity among children. Despite the proven effectiveness of CRS in reducing harm, its adoption remains inconsistent across regions due to socio-economic, legislative, and cultural factors. This review evaluates global CRS adoption rates, identifies barriers to effective utilization, and explores interventions to enhance usage and legislative compliance, ultimately proposing strategies to improve child passenger safety.</div><div>A total of 93 articles published between 2013 and 2024 were reviewed, with a focus on CRS usage and intervention patterns, the effectiveness of interventions, and legislative impact across high, middle, and low-income countries.</div><div>The review highlights a significant gap in CRS usage between high-income and low to middle-income countries, with affordability, lack of awareness, and inadequate legislation as primary barriers. High-income regions showed better adherence but struggled with proper installation and misuse. Intervention strategies, including legislation, public education, and economic incentives, showed varying success in improving CRS adoption.</div><div>Enhancing global CRS usage requires stringent legislation, comprehensive campaigns, economic support, and innovative technological solutions. Tailored strategies that account for regional socio-economic and cultural norms are essential to achieve widespread adoption and proper CRS use, ultimately reducing child passenger fatalities and injuries.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 3","pages":"Pages 362-373"},"PeriodicalIF":3.3,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050150","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}
Driving comfort assessment is a prerequisite to improve the journey experience for the drivers as well as the passengers. In this work, we proposed an advanced approach for the measurement of driving comfort in real-time. Different types of environmental features are considered along with the traditionally used Comfort Index (CI), and an Environment-specific Comfort Index (EsCI) is proposed. EsCI is also inversely proportional to the drivers' comfort level, just like CI. We also developed an android application named QDCL (Quantification of Driver Comfort Level) for overall data collection and computation of EsCI from the same. A series of driving experiments at different times of the day and different traffic conditions have been performed in Indian urban road scenarios to assess the performance of QDCL and the relevance of EsCI. We extended the work by studying the effects of different external stimuli on the computed driving comfort level. The performance of EsCI is observed to outperform the traditionally used CI (Comfort Index) in terms of accuracy for the quantification of overall driving comfort.
驾驶舒适性评估是提高驾驶员和乘客出行体验的前提。在这项工作中，我们提出了一种先进的实时驾驶舒适性测量方法。考虑了不同类型的环境特征以及传统使用的舒适度指数（CI），并提出了环境特异性舒适度指数（EsCI）。与CI一样，EsCI也与驾驶员的舒适度成反比。我们还开发了一个名为QDCL （Quantification of Driver Comfort Level）的android应用程序，用于收集驾驶员舒适度的整体数据并计算驾驶员舒适度。在印度城市道路场景中，在一天中不同时间和不同交通条件下进行了一系列驾驶实验，以评估QDCL的性能和EsCI的相关性。我们通过研究不同外部刺激对计算的驾驶舒适度的影响来扩展工作。EsCI的性能被观察到优于传统使用的CI（舒适指数）在准确性量化整体驾驶舒适性。
{"title":"A new paradigm in driving comfort measurement: Environment-specific comfort index and its real-time application in Indian context","authors":"Ishita Sar , Soumitra Kundu , Aurobinda Routray , Biswajit Mahanty","doi":"10.1016/j.iatssr.2025.09.002","DOIUrl":"10.1016/j.iatssr.2025.09.002","url":null,"abstract":"<div><div>Driving comfort assessment is a prerequisite to improve the journey experience for the drivers as well as the passengers. In this work, we proposed an advanced approach for the measurement of driving comfort in real-time. Different types of environmental features are considered along with the traditionally used Comfort Index (CI), and an Environment-specific Comfort Index (EsCI) is proposed. EsCI is also inversely proportional to the drivers' comfort level, just like CI. We also developed an android application named QDCL (Quantification of Driver Comfort Level) for overall data collection and computation of EsCI from the same. A series of driving experiments at different times of the day and different traffic conditions have been performed in Indian urban road scenarios to assess the performance of QDCL and the relevance of EsCI. We extended the work by studying the effects of different external stimuli on the computed driving comfort level. The performance of EsCI is observed to outperform the traditionally used CI (Comfort Index) in terms of accuracy for the quantification of overall driving comfort.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 3","pages":"Pages 353-361"},"PeriodicalIF":3.3,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050149","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}
Pub Date : 2025-09-02DOI: 10.1016/j.iatssr.2025.09.001
Debashis Ray Sarkar , K. Ramachandra Rao , Niladri Chatterjee
Crash prediction models (CPMs) typically use statistical or data-driven approaches derived from observed crash data, but these can be limited by unreliable historical data. Near-crash-based CPMs provide a proactive alternative, predicting crash frequencies before actual crashes occur. Surrogate Safety Measures (SSMs) examine potentially hazardous traffic events to improve the understanding of traffic safety dynamics. These events serve as proxies for crashes, enabling proactive and timely safety assessments. This study proposes a methodological framework for evaluating crash risk at unsignalized intersections using UAV-acquired vehicle trajectory data and applies Extreme Value Theory (EVT) to statistically model the tail behavior of a time-based SSM—Post Encroachment Time (PET). High-resolution (4 K) video data were acquired at six different unsignalized intersections to capture morning rush hour traffic (8 to 9 a.m.). Vehicle trajectories and surrogate measures such as Post Encroachment Time (PET) were extracted using advanced AI-driven video analysis via the DataFromSky (DFS) platform. The analysis employed the Peak Over Threshold (POT) method. The threshold was determined to be −1.25 s using the Mean Residual Life (MRL) plot, as well as the scale and shape parameter stability plots of the Generalized Pareto Distribution (GPD). The results show that traffic volume and crash frequency have a significant impact on collision risk. As traffic volume increases, PET decreases, leading to a higher likelihood of conflicts and crashes. Additionally, mean speed shows an inverse relationship with both crash frequency and collision risk. Overall, traffic volume and conflict frequency emerge as key predictors of crash risk occurrences. This study establishes a foundation for leveraging UAV-based vehicle trajectory data in conducting proactive safety assessments at unsignalized intersections.
{"title":"Crash risk assessment at unsignalized intersections using vehicle trajectory data","authors":"Debashis Ray Sarkar , K. Ramachandra Rao , Niladri Chatterjee","doi":"10.1016/j.iatssr.2025.09.001","DOIUrl":"10.1016/j.iatssr.2025.09.001","url":null,"abstract":"<div><div>Crash prediction models (CPMs) typically use statistical or data-driven approaches derived from observed crash data, but these can be limited by unreliable historical data. Near-crash-based CPMs provide a proactive alternative, predicting crash frequencies before actual crashes occur. Surrogate Safety Measures (SSMs) examine potentially hazardous traffic events to improve the understanding of traffic safety dynamics. These events serve as proxies for crashes, enabling proactive and timely safety assessments. This study proposes a methodological framework for evaluating crash risk at unsignalized intersections using UAV-acquired vehicle trajectory data and applies Extreme Value Theory (EVT) to statistically model the tail behavior of a time-based SSM—Post Encroachment Time (PET). High-resolution (4 K) video data were acquired at six different unsignalized intersections to capture morning rush hour traffic (8 to 9 a.m.). Vehicle trajectories and surrogate measures such as Post Encroachment Time (PET) were extracted using advanced AI-driven video analysis via the DataFromSky (DFS) platform. The analysis employed the Peak Over Threshold (POT) method. The threshold was determined to be −1.25 s using the Mean Residual Life (MRL) plot, as well as the scale and shape parameter stability plots of the Generalized Pareto Distribution (GPD). The results show that traffic volume and crash frequency have a significant impact on collision risk. As traffic volume increases, PET decreases, leading to a higher likelihood of conflicts and crashes. Additionally, mean speed shows an inverse relationship with both crash frequency and collision risk. Overall, traffic volume and conflict frequency emerge as key predictors of crash risk occurrences. This study establishes a foundation for leveraging UAV-based vehicle trajectory data in conducting proactive safety assessments at unsignalized intersections.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 4","pages":"Pages 459-469"},"PeriodicalIF":3.3,"publicationDate":"2025-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145326258","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}
Unsignalized intersections require more diverse and appropriate physical functions than signalized intersections because traffic is not controlled, and more objects and broader areas must be checked. Elderly drivers may lack adequate physical functions, leading to inadequate spatial exploration and missed recognition, resulting in accidents. This study aims to clarify the spatial exploration behavior of elderly drivers when passing through unsignalized intersections, considering road conditions, traffic conditions, and drivers' physical functions. Participants (n = 62) whose physical function was measured were asked to watch an entry video of 10 intersections using a head-mounted display with eye-tracking function, and the average angular velocity during the viewing was measured. Factorial analysis on spatial exploration showed that the elderly group did not exhibit greater spatial exploration at intersections with acute angles compared to other age groups, even considering physical function effects and traffic conditions through the linear mixed model.
{"title":"A study on spatial exploration of elderly drivers at unsignalized intersections considering road and traffic conditions and driver's physical function","authors":"Yasuhiro Mimura , Keiichi Higuchi , Misako Yamagishi , Ryo Ito","doi":"10.1016/j.iatssr.2025.07.003","DOIUrl":"10.1016/j.iatssr.2025.07.003","url":null,"abstract":"<div><div>Unsignalized intersections require more diverse and appropriate physical functions than signalized intersections because traffic is not controlled, and more objects and broader areas must be checked. Elderly drivers may lack adequate physical functions, leading to inadequate spatial exploration and missed recognition, resulting in accidents. This study aims to clarify the spatial exploration behavior of elderly drivers when passing through unsignalized intersections, considering road conditions, traffic conditions, and drivers' physical functions. Participants (<em>n</em> = 62) whose physical function was measured were asked to watch an entry video of 10 intersections using a head-mounted display with eye-tracking function, and the average angular velocity during the viewing was measured. Factorial analysis on spatial exploration showed that the elderly group did not exhibit greater spatial exploration at intersections with acute angles compared to other age groups, even considering physical function effects and traffic conditions through the linear mixed model.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 3","pages":"Pages 314-323"},"PeriodicalIF":3.3,"publicationDate":"2025-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145005198","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}
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