IATSS Research最新文献

{"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":"2025-06-27","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}

{"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":"2025-06-23","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":"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":"2025-06-14","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":"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":"2025-06-09","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":"Fundamental theory of coordination efficiency of signalized intersections on an arterial road","authors":"Hajime Sakakibara ,&nbsp;Takashi Oguchi","doi":"10.1016/j.iatssr.2025.04.002","DOIUrl":"10.1016/j.iatssr.2025.04.002","url":null,"abstract":"<div><div>In this study, we employed the general formula of the delay per vehicle for the case of one link at two intersections as a function of the link length and offset of traffic signals at two adjacent intersections with the general value of green splits under arbitral demand condition without oversaturation. The highest and lowest coordination efficiencies are defined for different link lengths. The nature of the link lengths and offsets that provide minimum delay per vehicle were analyzed and demonstrated. Additionally, two types of extensions to this study were conducted by determining the effects of an additional intersection located in the middle of the target link and for the installation at two adjacent intersections outside the target link.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 231-246"},"PeriodicalIF":3.2,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144189912","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":"Distractions or long waits? Impacts on risky crossing behaviour","authors":"Mohsen Miladi ,&nbsp;E. Owen D. Waygood ,&nbsp;Marie-Soleil Cloutier ,&nbsp;Wang Bobin ,&nbsp;Zeinab Ali Yas","doi":"10.1016/j.iatssr.2025.05.001","DOIUrl":"10.1016/j.iatssr.2025.05.001","url":null,"abstract":"<div><div>Pedestrian-vehicle conflicts at intersections are considered as a major source of injuries and fatalities. Intersections are a critical part of roadway design since pedestrians are exposed to different and potentially dangerous activities due to how an intersection is designed, but also what the pedestrian is doing and where in the city they are. In this study, various influences on risky crossing behaviour are examined. At the individual level, the influence of distractions and where people are looking before crossing are tested. Further, various intersection design variables including wait time, intersection size and speed limits, and contextual variables such as the built environment nearby and traffic flow are examined. The data was gathered by observing pedestrians at 24 intersections in Montreal and Quebec City (12 each). Logistic regression models were estimated to determine the influencing variables on four dangerous behaviours: a) start on red, b) finish on red, c) finish on red having started on green, and d) cross completely on red. Results demonstrate the importance of wait time on risky crossing behaviour with short wait times (&lt; 30s) decreasing the likelihood of such behaviours considerably. For individual behaviour, having a cellphone in one's hand reduces the likelihood of starting to cross on red. In contrast, looking at traffic was over four times more associated with crossing illegally.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 220-230"},"PeriodicalIF":3.2,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144168105","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":"Traffic safety evaluation using surrogate safety measures in the context of Indian mixed traffic: A critical review","authors":"N. Mohamed Hasain ,&nbsp;Mokaddes Ali Ahmed","doi":"10.1016/j.iatssr.2025.04.004","DOIUrl":"10.1016/j.iatssr.2025.04.004","url":null,"abstract":"<div><div>The concern over road safety has increased in the last several decades, especially in developing countries like India. Even with increasing road accidents, crash data at a particular location is mostly underreported. Hence, using the Traffic Conflict Technique (TCT) with Surrogate Safety Measures (SSMs) to evaluate traffic safety instead of accident data has gained significant attention among researchers in India. However, the traffic existing in the country is more complex and diverse than most of the developed nations around the world. This led the researchers to modify the existing methods and propose new methods to address the heterogeneity of the existing mixed traffic. The current study formulated six research questions to guide the review process. Since the number of studies in the area of research is increasing rapidly, there is a need to study the current state of the art in the country. Hence, the paper critically reviewed thirty-three studies conducted in the area of research in Indian conditions, including their findings and limitations. Further, an overview of sixteen commonly used SSMs worldwide was presented, along with some potential research gaps and recommendations.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 201-219"},"PeriodicalIF":3.2,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144070761","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":"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":"2025-04-18","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":"Determinants of crash injury severity for delivery riders: Insights from an error components mixed logit model with heterogeneous means and variances","authors":"Thanapong Champahom ,&nbsp;Chamroeun Se ,&nbsp;Wimon Laphrom ,&nbsp;Sajjakaj Jomnonkwao ,&nbsp;Rattanaporn Kasemsri ,&nbsp;Vatanavongs Ratanavaraha","doi":"10.1016/j.iatssr.2025.04.001","DOIUrl":"10.1016/j.iatssr.2025.04.001","url":null,"abstract":"<div><div>The rapid growth of e-commerce and food delivery services has led to an increase in commercial motorcycle riders, raising concerns about their safety on the road. This study aims to identify and analyze the determinants of crash injury severity for delivery riders in Thailand. Questionairs data was collected from 2000 commercial motorcycle users across five regions of Thailand, incorporating a wide range of demographic, work-related, and environmental factors. The study employs a Heteroscedastic Error Components Mixed Logit with Heterogeneity in Means (HECMLHM) model to capture unobserved heterogeneity and complex interactions between variables. Key findings reveal that rider age, experience, education level, income, work frequency, and rest periods significantly influence crash injury severity, often with varying effects across the population. Counterintuitively, more experienced riders faced a higher risk of severe injuries. Based on these findings, policy recommendations include targeted safety education programs, experience-based training to mitigate overconfidence, work schedule management, and optimized rest period policies. This study contributes to the field by focusing exclusively on delivery riders, employing advanced modeling techniques, and providing a comprehensive analysis of factors influencing crash severity in an emerging market context. The findings offer valuable insights for developing targeted safety interventions and policies to reduce crash injury severity among this growing workforce.</div></div>","PeriodicalId":47059,"journal":{"name":"IATSS Research","volume":"49 2","pages":"Pages 180-190"},"PeriodicalIF":3.2,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838850","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":"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":"2025-04-13","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}