International Journal of Transportation Science and Technology最新文献_第7页

Modeling economic impacts of transportation infrastructure in Pennsylvania considering spatial dependency across counties 考虑跨县空间依赖的宾夕法尼亚州交通基础设施经济影响模型

IF 4.8

International Journal of Transportation Science and Technology Pub Date : 2026-03-01 Epub Date: 2025-01-27 DOI: 10.1016/j.ijtst.2025.01.006

Asif Mahmud , Vikash V. Gayah , S. Ilgin Guler

{"title":"Modeling economic impacts of transportation infrastructure in Pennsylvania considering spatial dependency across counties","authors":"Asif Mahmud , Vikash V. Gayah , S. Ilgin Guler","doi":"10.1016/j.ijtst.2025.01.006","DOIUrl":"10.1016/j.ijtst.2025.01.006","url":null,"abstract":"<div><div>Quantifying the impacts of investments in transportation infrastructures such as bridges, roads, traffic signals, ports, and railroads has been of immense interest to researchers. Due to the nature of transportation infrastructure and how it geographically connects regions, any transportation-related investment is likely to have an impact on the economy of neighboring territories. This phenomenon, known as ‘spatial spillover’, is of great concern for transportation professionals and policymakers when deciding on investments in transportation infrastructure. This study aims to investigate the impacts of transportation infrastructure investments on the gross domestic product (GDP) at a county level in Pennsylvania, using a spatial econometric model to quantify the impact of spatial spillover. The novelty of this study lies in the proposed structures of spatial dependency (SD), including distance, inverse distance, proximity, and interstate highway connections. Analysis results show evidence of the presence of spatial spillover among the counties in Pennsylvania. An elasticity analysis is conducted to quantify the impacts of several factors, including transportation infrastructure investments, on the GDP across all counties. Key findings indicate that investments in bridges, traffic signals, and safety infrastructure positively contribute to economic growth, while higher crash frequency is associated with decreased economic activity. Notably, infrastructure spending on safety shows a significantly higher impact on GDP compared to other types of investments.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"21 ","pages":"Pages 77-91"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147556805","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}

引用次数: 0

Short-term passenger flow prediction of urban rail transit on Bayesian optimization-bidirectional long short-term memory with causal temporal pattern attention 基于贝叶斯优化的城市轨道交通短期客流预测——具有因果时间模式注意的双向长短期记忆

IF 4.8

International Journal of Transportation Science and Technology Pub Date : 2026-03-01 Epub Date: 2025-01-23 DOI: 10.1016/j.ijtst.2025.01.008

Jing Zuo , Ming He , Zhao Yu , Jianqiang Wang

{"title":"Short-term passenger flow prediction of urban rail transit on Bayesian optimization-bidirectional long short-term memory with causal temporal pattern attention","authors":"Jing Zuo , Ming He , Zhao Yu , Jianqiang Wang","doi":"10.1016/j.ijtst.2025.01.008","DOIUrl":"10.1016/j.ijtst.2025.01.008","url":null,"abstract":"<div><div>Accurate and reliable short-term passenger flow prediction is crucial for optimizing operational organization and enhancing intelligent management in urban rail transit. However, passenger flow remains relatively stable during off-peak periods, while intense fluctuations during peak hours increase the complexity and uncertainty of prediction, posing challenges for comprehensive and accurate short-term forecasting. To accurately capture the complex dynamic changes in peak-hour passenger flow and reduce the emphasis on the stable characteristics of off-peak periods, this study proposes a composite model. Initially, we construct a passenger flow dataset by processing passenger card swipe information from the automatic fare collection (AFC) system. Temporal features are extracted from the data using a bidirectional long short-term memory (BiLSTM) neural network. Furthermore, we introduce a causal temporal pattern attention (CTPA) mechanism enhanced with dilated causal convolution to optimize temporal feature weights specifically for peak and off-peak passenger flow periods. The optimized features from the regression BiLSTM and CTPA modules are integrated, and multi-step passenger flow predictions are obtained through a fully connected layer. During the training process of the BiLSTM-CTPA model, we utilize the Bayesian optimization (BO) algorithm to optimize key hyperparameters such as the number of hidden layers, neurons, batch size, learning rate, regularization, and iterations, thereby enhancing training efficiency. Experimental results demonstrate that compared to the baseline model, our approach achieves lower mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE). In conclusion, the model presented in this paper provides robust data support for the daily operation and management of urban rail transit.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"21 ","pages":"Pages 109-124"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147556807","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}

引用次数: 0

An approach of identifying and assessing the factors influencing traffic crashes: a combination of exploratory factor analysis and fuzzy analytical hierarchy process 交通事故影响因素识别与评价方法：探索性因子分析与模糊层次分析法相结合

IF 4.8

International Journal of Transportation Science and Technology Pub Date : 2026-03-01 Epub Date: 2025-01-23 DOI: 10.1016/j.ijtst.2025.01.007

Md Shohel Parvez , Sara Moridpour , Palash Saha

{"title":"An approach of identifying and assessing the factors influencing traffic crashes: a combination of exploratory factor analysis and fuzzy analytical hierarchy process","authors":"Md Shohel Parvez , Sara Moridpour , Palash Saha","doi":"10.1016/j.ijtst.2025.01.007","DOIUrl":"10.1016/j.ijtst.2025.01.007","url":null,"abstract":"<div><div>Preventing traffic accidents is a top priority worldwide, considering its extensive negative impact on people’s physical and mental health, the economy, and government expenditure. This research aims to identify and categorize the potential crash-related factors and evaluate the impact of those factors on the risk of traffic accidents. “Preferred reporting items for systematic reviews and meta-analysis (PRISMA)” is used to identify twenty-five potential crash-related factors. In addition, the exploratory factor analysis (EFA) method is used to classify the crash-related factors into five categories, including 1) road, 2) traffic, 3) vehicle, 4) personal, and 5) environment. Finally, the fuzzy analytical hierarchy process (FAHP) prioritizes the factors in each category. For each factor, the factor loadings varied from 0.659 to 0.934, satisfying the factor analysis condition in the EFA. Furthermore, Cronbach’s alpha values were higher than 0.8 for all factors, which means the collected data had high internal consistency. According to the relative weights identified from FAHP, the road-related factors were ranked in the following order: roadway geometry, non-signalized intersections, number of lanes and lane widths, road surface condition, and road surface type. Similarly, traffic, vehicle, personal, and environmental factors were ranked using FAHP. This study may contribute to the existing literature by scientifically categorizing crash-related factors into five main categories and understanding the impacts of the factors on traffic crashes. The results from this study will assist the government and road authorities in reducing the severity of traffic crashes and implementing road safety strategies through informed decisions.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"21 ","pages":"Pages 92-108"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557221","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}

引用次数: 0

Effects of urban form and socio-economic factors on transport-related carbon dioxide emissions: a structural equation approach 城市形态和社会经济因素对交通相关二氧化碳排放的影响：一个结构方程方法

IF 4.8

International Journal of Transportation Science and Technology Pub Date : 2026-03-01 Epub Date: 2025-01-31 DOI: 10.1016/j.ijtst.2025.01.013

Maricel C. Dalde , Vilas Nitivattananon , Deepak Sharma , Sarawut Ninsawat

{"title":"Effects of urban form and socio-economic factors on transport-related carbon dioxide emissions: a structural equation approach","authors":"Maricel C. Dalde , Vilas Nitivattananon , Deepak Sharma , Sarawut Ninsawat","doi":"10.1016/j.ijtst.2025.01.013","DOIUrl":"10.1016/j.ijtst.2025.01.013","url":null,"abstract":"<div><div>Transport-related CO<sub>2</sub> emissions are a major contributor to climate change, with urban areas playing a critical role in both the generation and mitigation of these emissions. This study investigates the effects of urban form (UF) and socio-economic (SE) characteristics on transport-related CO<sub>2</sub> emissions using structural equation modeling (SEM). The study reveals that UF does not significantly influence travel behavior (TB), whereas SE factors exert a strong negative direct effect on TB. In relation to CO<sub>2</sub> emissions, UF directly reduces emissions significantly; however, its indirect effect through TB is negligible. In contrast, SE factors do not directly affect CO<sub>2</sub> emissions, but they exert a strong indirect effect mediated by TB. Furthermore, TB itself significantly mitigates CO<sub>2</sub> emissions. These findings highlight the necessity of addressing SE determinants to effectively modify TB and achieve substantial reductions in CO<sub>2</sub> emissions, suggesting that alterations in UF alone are insufficient. This research supports the creation of sustainable urban mobility not only in the Philippines but also in diverse global contexts, thereby contributing to the broader goal of combating climate change.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"21 ","pages":"Pages 191-207"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147556803","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}

引用次数: 0

An analysis of layout strategies for public transport hubs in polycentric urban regions considering functional classification 考虑功能分类的多中心城市公共交通枢纽布局策略分析

IF 4.8

International Journal of Transportation Science and Technology Pub Date : 2026-03-01 Epub Date: 2025-02-17 DOI: 10.1016/j.ijtst.2025.02.003

Yueer Zhou , Linbo Li , Yahua Zhang

{"title":"An analysis of layout strategies for public transport hubs in polycentric urban regions considering functional classification","authors":"Yueer Zhou , Linbo Li , Yahua Zhang","doi":"10.1016/j.ijtst.2025.02.003","DOIUrl":"10.1016/j.ijtst.2025.02.003","url":null,"abstract":"<div><div>The polycentric urban regions (PURs) necessitate an integrated public transport system encompassing intra and inter-city transport. Compared to traditional monocentric cities, the hubs and lines of networks within this extensive service area require functional classification to accommodate the heterogeneous features of PURs. Unfortunately, the existing studies on hub location have overlooked this crucial concept. To address this issue, we introduce a parameterized description of PURs’ travel demands with a ternary functional classification of hub nodes, and this serves as the basic framework for bi-level programming. The upper-level model aims to determine the number of hubs of each functional classification and their location. The lower-level model is a stochastic user equilibrium model with elastic demand. We apply this analysis framework to the Suzhou-Wuxi region (SWR) and find that 1) an increased number of hubs may not necessarily enhance the efficiency of a regional public transport network from the perspective of passenger behaviors; 2) a decentralized layout of public transport hubs outperforms a centralized one; 3) the sub-centers (SCs) or peripheral areas (PAs) are more appropriate as regional hub nodes than the center business district (CBD) nodes. All these findings could be valuable for the future PUR development. These conclusions have important reference value for decision-makers of PUR development, and also verify the effectiveness and applicability of the decision analysis framework of PURs' public transport hubs proposed in this study.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"21 ","pages":"Pages 322-337"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147556809","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}

引用次数: 0

Non-disruptive rail track geometry measurement system using an unmanned aerial vehicle and a light detection and ranging sensor 使用无人机和光探测和测距传感器的无干扰轨道几何测量系统

IF 4.8

International Journal of Transportation Science and Technology Pub Date : 2026-03-01 Epub Date: 2025-03-05 DOI: 10.1016/j.ijtst.2025.02.008

Lihao Qiu , Ming Zhu , Yingtao Jiang , Hualiang (Harry) Teng , Jee Woong Park

{"title":"Non-disruptive rail track geometry measurement system using an unmanned aerial vehicle and a light detection and ranging sensor","authors":"Lihao Qiu , Ming Zhu , Yingtao Jiang , Hualiang (Harry) Teng , Jee Woong Park","doi":"10.1016/j.ijtst.2025.02.008","DOIUrl":"10.1016/j.ijtst.2025.02.008","url":null,"abstract":"<div><div>The safety of train operations largely depends on the health of rail tracks, necessitating regular and meticulous inspection and maintenance. A significant part of such inspections involves geometric measurements of the tracks to detect any potential problems. Existing commercial track geometry measurement processes typically rely on dedicated on-track inspection vehicles. These solutions usually necessitate temporary track closures during the assessment period and become increasingly time-consuming as the inspection area expands, resulting in significant disruptions to regular railroad operations and increased costs. To address this challenge, this paper proposes an aerial track geometry measurement system (TGMS) that utilizes an unmanned aerial vehicle (UAV) equipped with a light detection and ranging (LiDAR) sensor and an inertial measurement unit (IMU) sensor. Integrated with a state-of-the-art machine learning (ML)-based computer vision algorithm and a simultaneous localization and mapping (SLAM) algorithm, this platform can conduct track geometry inspections seamlessly over a larger area without interrupting rail operations. In particular, this semi- or fully automated measurement is capable of measuring critical track geometry irregularities in gauge, curvature, and profile with a root mean square error (RMSE) of 1 cm, 0.84 cm, and 0.87 cm, respectively. By eliminating operational interruptions, the proposed system can offer a more flexible, efficient, and cost-effective solution for inspecting and maintaining rail infrastructure.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"21 ","pages":"Pages 399-413"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147556800","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}

引用次数: 0

Development of an unsupervised 3D LiDAR-based methodology for automated safety monitoring of railway facilities 开发一种基于无监督3D激光雷达的方法，用于铁路设施的自动安全监测

IF 4.8

International Journal of Transportation Science and Technology Pub Date : 2026-03-01 Epub Date: 2025-01-23 DOI: 10.1016/j.ijtst.2025.01.011

Ehsan Nateghinia, Luis F. Miranda-Moreno

{"title":"Development of an unsupervised 3D LiDAR-based methodology for automated safety monitoring of railway facilities","authors":"Ehsan Nateghinia, Luis F. Miranda-Moreno","doi":"10.1016/j.ijtst.2025.01.011","DOIUrl":"10.1016/j.ijtst.2025.01.011","url":null,"abstract":"<div><div>Railway safety (e.g., at grade crossings, platforms, or rail tracks) is a primary concern for transportation authorities. Unfortunately, preventable railway collisions claim the lives of hundreds annually, often involving individuals crossing illegally at highway-railway grade crossings or trespassing at unauthorized railroad facilities. Transportation authorities often deploy a range of engineering countermeasures to mitigate the frequency or risk of such events. These countermeasures include technological solutions that automatically activate warning systems, barriers, or gates to alert and deter road users from unlawfully entering restricted railway facilities. For the safety monitoring of such facilities, alternative sensing technologies such as video-based computer-vision systems have been evaluated and, in some cases, utilized in practice. Despite their merits, automated LiDAR-based detection and tracking methods have yet to be explored in railway safety applications. This research aims to introduce and assess an unsupervised 3D-LiDAR-based methodology for monitoring rail-road level facilities. This study’s core is the implementation of an unsupervised learning algorithm designed to detect, track, and classify road users using point clouds gathered by a 3D-LiDAR sensor. The proposed methodology demonstrates encouraging results when monitoring rail-road level crossings. The aggregate average absolute percentage deviation (AAPD) for motorized road users and counting motorized road users stands at 5% and 3%, for non-motorized road users at 10% and 14% on two separate test days, each featuring distinct system installations.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"21 ","pages":"Pages 157-172"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147556806","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}

引用次数: 0

Graph neural networks for travel distance estimation and route recommendation under probabilistic hazards 基于图神经网络的概率危险下的行程估计和路线推荐

IF 4.8

International Journal of Transportation Science and Technology Pub Date : 2026-03-01 Epub Date: 2025-02-26 DOI: 10.1016/j.ijtst.2025.02.006

Tong Liu, Hadi Meidani

{"title":"Graph neural networks for travel distance estimation and route recommendation under probabilistic hazards","authors":"Tong Liu, Hadi Meidani","doi":"10.1016/j.ijtst.2025.02.006","DOIUrl":"10.1016/j.ijtst.2025.02.006","url":null,"abstract":"<div><div>Estimating the shortest travel time and providing route recommendations between different locations in a city or region can quantitatively measure the conditions of the transportation network during or after extreme events. One common approach is to use Dijkstra’s algorithm, which produces the shortest path as well as the shortest distance. However, this option is computationally expensive when applied to large-scale networks. This paper proposes a novel fast framework based on graph neural networks (GNNs) which approximate the single-source shortest distance between pairs of locations, and predict the single-source shortest path subsequently. We conduct multiple experiments on synthetic graphs of different sizes to demonstrate the feasibility and computational efficiency of the proposed model. In real-world case studies, we also apply the proposed method of flood risk analysis of coastal urban areas to calculate delays in evacuation to public shelters during hurricanes. The results indicate the accuracy and computational efficiency of the GNN model, and its potential for effective implementation in emergency planning and management.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"21 ","pages":"Pages 372-383"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147556811","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}

引用次数: 0

Integrating acoustic-based risk quantification for modeling one-to-one dynamic pedestrian-vehicle interactions at non-signalized crosswalks using empirical data 利用经验数据集成基于声学的风险量化，对无信号人行横道上的一对一动态行人-车辆相互作用进行建模

IF 4.8

International Journal of Transportation Science and Technology Pub Date : 2026-03-01 Epub Date: 2025-01-20 DOI: 10.1016/j.ijtst.2025.01.003

Shikun Xie , Zhen Yang , Guilong Xu

{"title":"Integrating acoustic-based risk quantification for modeling one-to-one dynamic pedestrian-vehicle interactions at non-signalized crosswalks using empirical data","authors":"Shikun Xie , Zhen Yang , Guilong Xu","doi":"10.1016/j.ijtst.2025.01.003","DOIUrl":"10.1016/j.ijtst.2025.01.003","url":null,"abstract":"<div><div>Perceived risk is a key factor influencing pedestrian-vehicle interactions. Existing risk assessments primarily quantify conflict probabilities, overlooking the subjective and ambiguous nature of perceived risk, which differs significantly from precise probabilities. Establishing a mapping between objective probabilistic risk and subjective perceived risk is therefore crucial. Drawing on sound perception theory, this study introduces the concept of decibel (dB) to propose a novel method for quantifying perceived risk while incorporating uncertainty and ambiguity. Combined with evolutionary game theory (EGT), the model analyzes dynamic interactions between pedestrians and vehicles at unsignalized crosswalks, quantifying perceived risks and determining acceptable levels. The acceptable perceived risk range is 1.13–2.48 dB for vehicles and 0–1.85 dB for pedestrians, with pedestrians more likely to yield at lower perceived risks. Perceived risk significantly impacts four evolutionary strategies and their paths. “Pedestrian Wait, Vehicle Not Yield” exhibits steep slopes and rapid convergence, reflecting high-conflict scenarios. “Pedestrian Cross, Vehicle Yield” is stable, with steady convergence, while “Pedestrian Wait, Vehicle Yield” and “Pedestrian Cross, Vehicle Not Yield” are unstable, showing low slopes and weak convergence. Simulations reveal that increasing vehicle distance, reducing speed, and limiting acceleration promote “Pedestrian Cross, Vehicle Yield”, while reducing pedestrian distance and speed shifts behavior toward “Pedestrian Wait, Vehicle Not Yield”. The proposed model and strategy analysis provide valuable insights for designing traffic safety facilities and improving autonomous driving algorithms, enabling real-time monitoring and enhancing pedestrian safety.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"21 ","pages":"Pages 31-50"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557224","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}

引用次数: 0

Factors affecting the injury severity of head-on crashes on undivided rural roads under different weather conditions 不同天气条件下未分割乡村道路迎面碰撞伤害严重程度的影响因素

IF 4.8

International Journal of Transportation Science and Technology Pub Date : 2026-03-01 Epub Date: 2025-03-10 DOI: 10.1016/j.ijtst.2025.02.007

Mehdi Ebrahimi Darkhaneh, Meysam Effati, Mahyar Arabani

{"title":"Factors affecting the injury severity of head-on crashes on undivided rural roads under different weather conditions","authors":"Mehdi Ebrahimi Darkhaneh, Meysam Effati, Mahyar Arabani","doi":"10.1016/j.ijtst.2025.02.007","DOIUrl":"10.1016/j.ijtst.2025.02.007","url":null,"abstract":"<div><div>Head-on collisions are among the most severe types of crashes, consistently resulting in more severe injuries than other types of collisions. One of the most important factors affecting these crashes is weather conditions. In this study, for the first time, the effects of different weather conditions on the severity of head-on crashes on undivided rural roads were investigated using parametric and nonparametric approaches. With the parametric and non-parametric approaches, this study aimed to analyze head-on crashes on undivided roads and the factors influencing their severity under different weather conditions. Recorded data on head-on crashes in the study area over a 5-year period were categorized into two groups based on weather conditions: clear (sunny) and adverse (cloudy, rainy, snowy, and foggy). By identifying the factors affecting crash severity using the the classification and regression tree (CART) algorithm, the logistic regression algorithm was employed to determine the significance and impact of each variable. The results revealed that summer affects both clear and adverse weather conditions, increasing the crash severity by 11% and 27%, respectively. Motorcycle-to-motorcycle collisions were significant in both clear and adverse weather conditions, with over 90% resulting in injuries or fatalities. The familiarity of at-fault drivers, wet surface, and early morning significantly affected the severity of head-on collisions in adverse weather. Specifically, night-dark increased the crash severity by 30% in clear weather. At-fault young drivers and heavy vehicle-to-motorcycle collision increased the severity, while road geometry and afternoon reduced the severity of head-on collisions in clear weather conditions. The findings guide weather-specific safety strategies, like improving visibility and addressing motorcyclist and young driver risks, to reduce head-on collision severity.</div></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":"21 ","pages":"Pages 384-398"},"PeriodicalIF":4.8,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147557208","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}

引用次数: 0