IATSS Research最新文献

{"title":"E-scooter crash severity in the United Kingdom: A comparative analysis using machine learning techniques and random parameters logit with heterogeneity in means and variances","authors":"Ali Agheli ,&nbsp;Kayvan Aghabayk ,&nbsp;Matin Sadeghi ,&nbsp;Subasish Das","doi":"10.1016/j.iatssr.2025.03.004","DOIUrl":"10.1016/j.iatssr.2025.03.004","url":null,"abstract":"<div><div>The increasing use of e-scooters in urban areas has raised safety concerns, necessitating research for effective safety interventions. This study analyzes three years of e-scooter crash data from the United Kingdom using statistical and machine learning methods to identify key factors influencing crash severity. We employed a random parameters logit model and investigated several machine learning algorithms, with XGBoost performing best. Analysis reveals that severe injuries are more likely in crashes involving senior riders, at night with lighting, and at T, staggered, or crossroad junctions. Further insights from the XGBoost-SHAP analysis and heterogeneity in means and variances of random parameters revealed nuanced patterns. While crashes involving female riders or crashes at give way or uncontrolled junctions typically have less severe outcomes, specific condition (young female riders or nighttime crashes at these junctions) intensify the risk of severe injuries. These insights advocate for tailored public policy adjustments and infrastructure enhancements to mitigate e-scooter risks, ensuring safer urban mobility for all demographics.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 155-168"},"PeriodicalIF":3.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysing the effectiveness of unsignalized crossing infrastructure in improving pedestrian safety using multiple data-driven approaches","authors":"Shengqi Liu,&nbsp;Harry Evdorides","doi":"10.1016/j.iatssr.2025.06.002","DOIUrl":"10.1016/j.iatssr.2025.06.002","url":null,"abstract":"<div><div>This study investigates the effectiveness of unsignalized crossings to enhance pedestrian safety through a robust data-driven approach utilizing multiple machine learning models, including the statistical classifier Logistic Regression, Decision Tree, Random Forest, and Neural Network Multi-Layer Perceptron (MLP). While numerous studies have applied predictive models to traffic crash data, few have systematically analysed pedestrian crash severity at unsignalized crossings using multiple machine learning algorithms. By leveraging historical crash data from the UK's STATS19 database, key factors influencing pedestrian safety at unsignalized crossings were identified and analysed. The research highlights the superior predictive performance of Random Forest and MLP models, with accuracies of 84 % and 86 %, respectively, underscoring their capability to handle complex, nonlinear relationships in crash data. Feature importance analysis revealed critical determinants of crash severity. The findings emphasize the need for targeted interventions to mitigate crash severity of crash outcomes. Despite challenges like underreporting and data imputation biases, this study provides valuable insights into the role of infrastructure in pedestrian safety, offering a foundation for policy recommendations and future research on improving unsignalized crossing designs.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 271-279"},"PeriodicalIF":3.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144338963","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":"Understanding psychological factors behind motorcyclists crossing behavior on undivided roads in mixed traffic conditions: A case study of Hau Giang, Vietnam","authors":"Hai Ngoc Duong ,&nbsp;Minh Cong Chu ,&nbsp;Nathan Huynh","doi":"10.1016/j.iatssr.2025.02.003","DOIUrl":"10.1016/j.iatssr.2025.02.003","url":null,"abstract":"<div><div>Motorcycle crashes are a common occurrence in developing countries with mixed traffic. A contributing factor to these crashes is the crossing maneuvers of motorcyclists on undivided roadways. This study applies the Theory of Planned Behavior to understand the intentions and behaviors of these motorcyclists when making such maneuvers. It utilizes data from two surveys conducted in Hau Giang, Vietnam in 2022. The first investigation surveyed 351 participants to elicit the motorcyclists' behavioral beliefs and control beliefs when making crossing maneuvers that complied with traffic rules (complying maneuvers, CM), and the second investigation interviewed 260 respondents to elicit motorcyclists' beliefs when making crossing maneuvers that violated traffic rules (illegal maneuvers, IM). By applying the Structural Equation Modeling approach, the results reveal that the intention of motorcyclists to perform crossing maneuvers (CMs) is influenced by facilitating circumstances, subjective norms, and descriptive norms. In contrast, the intention to perform improper maneuvers (IMs) is driven by advantage beliefs, descriptive norms, facilitating circumstances, subjective norms, and driving situation awareness. Additionally, risk perception directly affects motorcyclists' performance of CMs, while near-miss incidents related to IMs are directly influenced by facilitating circumstances and perceived risk. These findings suggest that reducing improper maneuvers and promoting safer road-crossing performance can be achieved through targeted safety intervention strategies. Such strategies could include addressing the consequences of advantage beliefs regarding IMs and enhancing riders' situation awareness and risk perception through driver education and training programs.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 114-126"},"PeriodicalIF":3.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686355","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perceptions of pedestrian safety in Delhi: A Rasch analysis approach","authors":"Neba C Tony ,&nbsp;Geetam Tiwari ,&nbsp;Taku Fujiyama ,&nbsp;M. Manoj ,&nbsp;Niladri Chatterjee","doi":"10.1016/j.iatssr.2025.04.003","DOIUrl":"10.1016/j.iatssr.2025.04.003","url":null,"abstract":"<div><div>Safety perception about the built environment influences a pedestrian's walking and crossing decisions. Rasch analysis, a relatively underutilized psychometric technique in the road safety domain, can provide deep insights into pedestrian's perceptions and decision making process. This paper evaluates pedestrian safety perception based on built environment features in Delhi, India. Pedestrians' perceptions of built environment was collected and analyzed using the Rasch technique to simultaneously compute pedestrian performances and safety constructs. The analysis highlights key areas that need immediate interventions. Results revealed that most safety-related constructs are beyond the safety thresholds of even the most capable pedestrians, suggesting that the general pedestrian environment in Delhi is hostile to walking. This paper also discusses the implications of Rasch analysis for revising survey questions, providing valuable insights for early researchers about survey questionnaire design.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 191-200"},"PeriodicalIF":3.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143918328","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":"Unpacking the relationship between task complexity and driving risk: Insights from a UK on-road trial","authors":"Evita Papazikou ,&nbsp;Rachel Talbot ,&nbsp;Laurie Brown ,&nbsp;Sally Maynard ,&nbsp;Ashleigh Filtness","doi":"10.1016/j.iatssr.2025.03.003","DOIUrl":"10.1016/j.iatssr.2025.03.003","url":null,"abstract":"<div><div>This study investigates the intricate relationship between task complexity and driving risk through a comprehensive four-phase on-road trial conducted in the UK. Employing Structural Equation Modelling (SEM), the research illuminates the factors influencing task complexity and its association with risk, treating both as latent concepts—unobservable variables in the study. The findings reveal a notable positive correlation between task complexity and risk, particularly concerning the headway indicator. In essence, the study demonstrates that an escalation in task complexity corresponds to an increased level of risk.</div><div>Throughout the four SEM analyses performed across two waves of on-road trials, the time spent in each safety tolerance zone level for headway measurements emerges as a key indicator of the latent construct of risk in all phases. Notably, the variables constituting the latent concept of task complexity—those proven statistically significant—show slight variations across phases. Variables consistently significant across all phases include the number of right Lane Departure Warnings (LDWs) per 30 s and the day of the week.</div><div>The models reveal the feasibility of quantifying the risk-task complexity relationship in real-world driving settings. This study provides insights to inform efforts to mitigate risk exposure through design and training interventions, targeting the most predictive factors linked to task complexity. Driver demographics did not emerge as statistically significant, emphasising the need for a holistic approach to improve road safety.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 127-136"},"PeriodicalIF":3.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"E-scooter riders: A cross-cultural analysis of traffic safety attitudes and behaviors","authors":"Milad Delavary ,&nbsp;Craig Lyon ,&nbsp;Ward G.M. Vanlaar ,&nbsp;Robyn D. Robertson ,&nbsp;Dimitrios Nikolaou ,&nbsp;George Yannis","doi":"10.1016/j.iatssr.2025.05.002","DOIUrl":"10.1016/j.iatssr.2025.05.002","url":null,"abstract":"<div><div>The rapid adoption of electric scooters (e-scooters) has transformed urban mobility, offering a practical and flexible alternative to traditional transportation modes, particularly in areas with limited access to public transit. However, this rise in popularity has also brought about serious road safety concerns, particularly regarding risky behaviors such as riding under the influence of alcohol, carrying multiple passengers, and non-compliance with traffic regulations. While non-compliance with traffic regulations is not unique to e-scooter users, the combination of multiple risky behaviors observed among them may contribute to a higher likelihood of such violations. In addition, protective behaviors, such as helmet use, remain low among many riders, increasing injury risk in the event of a crash. This study aimed to analyze the prevalence of self-reported risky behaviors across various demographic groups and regions, and to assess factors contributing to the likelihood of unsafe e-scooter riding behavior. To achieve this, we used data from the third edition of the <em>E</em>-Survey of Road users' Attitudes (ESRA), focusing on responses from 39 countries worldwide. Descriptive analyses of self-reported data were conducted to examine e-scooter usage patterns and self-declared risky behaviors. Additionally, mixed-effects logistic regression models were employed to identify significant predictors of these behaviors, including gender, age, student status, crash history, and attitudes toward traffic laws. The results revealed that younger individuals and males are more likely to use e-scooters and engage in risky behaviors. Key factors influencing or associated with these behaviors included previous crash involvement, student status, and permissive attitudes toward safety regulations. The study highlights the need for targeted safety interventions that address infrastructural factors as well as behavioral factors, including demographic and attitudinal influences. This integrated approach can help policymakers develop more effective strategies to mitigate the risks associated with e-scooter use and enhance urban road safety.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 247-258"},"PeriodicalIF":3.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144242870","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":"Exploring the factors affecting injury severity in highway and non-highway crashes in Bangladesh applying machine learning and SHAP","authors":"Nazmus Sakib ,&nbsp;Tonmoy Paul ,&nbsp;Subasish Das ,&nbsp;Ahmed Hossain","doi":"10.1016/j.iatssr.2025.06.001","DOIUrl":"10.1016/j.iatssr.2025.06.001","url":null,"abstract":"<div><div>To create effective preventive measures and targeted interventions, it is crucial to comprehend the contributing factors to the crash and quantify how they affect the injury, especially in least-developed countries. However, highway and non-highway crashes are linked to having distinguished characteristics, road-specific interventions, and data granularity. Combining all sorts of crashes into a single model may offer fewer insights than one would anticipate when building safety countermeasures. This research compares CART, RF, GBM, XGBoost, LightGBM, CatBoost, and AdaBoost and effectively simulates the complex relationship between collision injury severity and risk factors for both highway and non-highway crashes. Additionally, the Shapley Additive exPlanation (SHAP) framework is presented to explain the contribution of each risk factor from the output of the most appropriate classifier, thereby assisting in the construction of safety countermeasures and crash modification factors. GBM classifier was found to be the best classifier in terms of G-mean and AUC scores for both highway and non-highway models. Global SHAP values show that the type of collision, followed by the vehicle type, the vehicle involved, and road division, are the highest contributing factors for injury severity in highway crashes. For injury severity in non-highway crashes, the most important factors are the type of collision, followed by road division, vehicle type, and location type. Policy implications based on the study's findings have been suggested to develop successful preventive strategies and focused interventions. The study concludes by discussing the scope of future studies.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 259-270"},"PeriodicalIF":3.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144280167","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":"Study of psychological aspects of the safety culture of motorcyclists' behaviors in Indonesia's urban road traffic: Construction of road users' belief systems","authors":"Andrijanto ,&nbsp;Makoto Itoh ,&nbsp;Sunardy ,&nbsp;Michael Jonathan","doi":"10.1016/j.iatssr.2025.03.002","DOIUrl":"10.1016/j.iatssr.2025.03.002","url":null,"abstract":"<div><div>The poor development of traffic safety culture by road traffic organizations in Indonesia has caused motorcyclists to behave irresponsibly while driving. Consequently, some behaviors may cause conflict with other road users, which may affect traffic safety. Therefore, studying the beliefs of road users regarding motorcyclists' behavior can describe the psychological aspects of the safety culture in urban road traffic. In this study, we used the reciprocal safety culture model as a framework, by applying a behavioral-based safety program to investigate motorcyclists' critical behaviors in urban areas in Indonesia. Adapting Ward's transformation model of belief systems to a behavior, we approach the psychological aspects of the traffic safety culture by observing the relationship between motorcyclists' critical behaviors and belief systems. We explore the belief system of Ward's model using a driving safety questionnaire (DSQ) and a cause-effect questionnaire. By applying multiple linear regression to the DSQ results, we revealed six motorcyclist behaviors critical to safety that affect car drivers and pedestrians. Furthermore, we constructed the belief systems of these behaviors by investigating behavioral beliefs, attitudes, normative beliefs, perceived norms, perceived control, and control beliefs to reveal “what road users think” about motorcyclits' behaviors related to traffic safety culture in the urban area.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 137-154"},"PeriodicalIF":3.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143724118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Statistical analysis of motorcyclists' safety behavior and crash risks in Kuwait","authors":"Sharaf AlKheder,&nbsp;Shaikha Al Mutairi,&nbsp;Dana Musaed,&nbsp;Dana Nayef","doi":"10.1016/j.iatssr.2025.03.005","DOIUrl":"10.1016/j.iatssr.2025.03.005","url":null,"abstract":"<div><div>Road crashes represent a significant global safety crisis, with motorcyclists, cyclists, and pedestrians involved in over half of all traffic fatalities, motorcyclists being particularly vulnerable as both potential causes and victims of crashes. In Kuwait, the increasing use of motorcycles, particularly for delivery services, has raised crash risks, highlighting the need for updated safety measures. This study analyzes the driving behavior of motorcyclists and car drivers, focusing on road usage, traffic violations, and licensing while identifying key factors contributing to motorcycle crashes through surveys, interviews, and historical records. A busy area of the city was chosen as the research site due to its high concentration of restaurants and heavy traffic from delivery motorcyclists, customers, and other road users. Data was collected from interviews with 103 motorcyclists, an online survey of 300 car drivers, and publicly available open-source national data. Advanced statistical methods were used for analysis, including the Vector Autoregressive Model, Structural Equation Modeling, and Principal Component Analysis. The findings revealed that motorcycle-related road crashes are influenced by factors such as the motorcyclist's gender, spatial awareness, perceptual challenges, and familiarity with motorcycle positioning. Conversely, crash frequency is associated with the driver's experience, right-of-way violations by other road users, traffic violations by motorcyclists, and road conditions. To mitigate motorcycle-related road crashes, the study recommends the development of an Exclusive Motorcycle Lane with an optimal width of 1.855 m in the selected research site. This step has the potential to significantly improve road safety, reduce accidents, and save lives, contributing to safer urban mobility in Kuwait. Similar measures could also be implemented in countries with a high risk of motorcycle-related road crashes.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 169-179"},"PeriodicalIF":3.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143823578","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":"Understanding the changes in long-distance travel behavior due to socio-economic and pandemic drivers","authors":"Farzana Faiza Farha,&nbsp;Sadia Afroj,&nbsp;Md. Musleh Uddin Hasan,&nbsp;Effat Farzana","doi":"10.1016/j.iatssr.2025.06.003","DOIUrl":"10.1016/j.iatssr.2025.06.003","url":null,"abstract":"<div><div>The unprecedented COVID-19 pandemic massively affected the long-distance trips all over the world. Like other countries worldwide, inter-regional mobility restrictions with the capital city were also imposed in Bangladesh to control the spread of coronavirus. Therefore, it is important to examine the changes in long-distance travel behavior to understand people's mobility needs and responses during travel restrictions, as well as the influences of individuals' socio-economic conditions and the country's COVID severity on their travel decisions. Data for this research were collected from 402 respondents in Dhaka using online questionnaires. Voluntary response and convenience sampling techniques were followed in this study. Moreover, district-wise COVID data was obtained from the dashboard of Directorate General of Health Services (DGHS). Descriptive statistics and spatial analyses were employed in this study. In addition, binary logistic regression model and mixed-effect logistic regression model were developed to understand the underlying factors behind the changes in long-distance travel behavior during the pandemic. The findings reveal that the majority of the respondents decreased their long-distance trips during the first pandemic wave. A notable percentage of trip makers' long-distance trip patterns and mode use remained the same as their pre-pandemic situation. Access to private cars was a positive determinant for long-distance trips during the pandemic; hence, the excess cost of private transportation compelled people to use risky public transportation. The presence of elderly individuals and children in households reduced the likelihood of traveling longer distances during the pandemic. Hygiene and safety from COVID-19 contamination were the main concerns for respondents while choosing long-distance travel modes. Individuals' high-risk perception regarding COVID-19 decreased the probability of traveling longer-distance during the pandemic. In general, travelers relatively less preferred COVID hotspots as their long-distance trip destinations during the first pandemic wave. This study's recommendations will assist planners and policymakers in designing a safe and affordable long-distance transport corridor during future pandemics.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 280-289"},"PeriodicalIF":3.2,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144491311","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}