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Road traffic accidents (RTA) pose a significant public health threat worldwide, leading to considerable loss of life and economic burdens. This is particularly acute in developing countries like Bangladesh. Building reliable models to…

Machine Learning · Computer Science 2024-09-19 Md. Asif Khan Rifat , Ahmedul Kabir , Armana Sabiha Huq

Different factors have effects on traffic crashes and crash-related injuries. These factors include segment characteristics, crash-level characteristics, occupant level characteristics, environment characteristics, and vehicle level…

Machine Learning · Computer Science 2023-01-06 Mehdi Moeinaddini , Mozhgan Pourmoradnasseri , Amnir Hadachi , Mario Cools

Road accidents have significant economic and societal costs, with a small number of severe accidents accounting for a large portion of these costs. Predicting accident severity can help in the proactive approach to road safety by…

Machine Learning · Computer Science 2023-10-10 Adekunle Adefabi , Somtobe Olisah , Callistus Obunadike , Oluwatosin Oyetubo , Esther Taiwo , Edward Tella

Tree-involved crashes represent a critical subset of run-off-road (ROR) collisions, often resulting in fatal or severe injuries due to high-energy impacts. This study develops a comprehensive analytical framework to identify and quantify…

Machine Learning · Computer Science 2026-05-11 Abdul Azim , Ahmed Hossain , Soumyadip Maitra , Panick Kalambay

The costs of fatalities and injuries due to traffic accident have a great impact on society. This paper presents our research to model the severity of injury resulting from traffic accidents using artificial neural networks and decision…

Artificial Intelligence · Computer Science 2007-05-23 Miao M. Chong , Ajith Abraham , Marcin Paprzycki

Road-safety inspection is an indispensable instrument for reducing road-accident fatalities contributed to road infrastructure. Recent work formalizes road-safety assessment in terms of carefully selected risk factors that are also known as…

Computer Vision and Pattern Recognition · Computer Science 2024-09-20 Marin Kačan , Marko Ševrović , Siniša Šegvić

Accurately modeling crash severity on rural two-lane roads is essential for effective safety management, yet standard single level approaches often overlook unobserved heterogeneity across road segments. In this study, we analyze 19 956…

Motor vehicle crashes remain a leading cause of injury and death worldwide, necessitating data-driven approaches to understand and mitigate crash severity. This study introduces a curated dataset of more than 3 million people involved in…

Rapid increase of traffic volume on urban roads over time has changed the traffic scenario globally. It has also increased the ratio of road accidents that can be severe and fatal in the worst case. To improve traffic safety and its…

Other Computer Science · Computer Science 2020-10-29 Muhammad Umer , Saima Sadiq , Abid Ishaq , Saleem Ullah , Najia Saher , Hamza Ahmad Madni

Road safety is impacted by a range of factors that can be categorized into human, vehicle, and roadway/environmental elements. This research explores the connection between pavement performance and road safety, particularly in relation to…

Physics and Society · Physics 2025-07-01 Prathyush Kumar Reddy Lebaku , Lu Gao , Jingran Sun , Xingju Wang , Xuejian Kang

Despite paying special attention to the motorcycle-involved crashes in the safety research, little is known about their pattern and impacts in developing countries. The widespread adoption of motorcycles in such regions in tandem with the…

Applications · Statistics 2022-04-11 Sina Asgharpour , Mohammadjavad Javadinasr , Zeinab Bayati , Abolfazl , Mohammadian

Traffic accidents pose a severe global public health issue, leading to 1.19 million fatalities annually, with the greatest impact on individuals aged 5 to 29 years old. This paper addresses the critical need for advanced predictive methods…

Machine Learning · Computer Science 2024-06-21 Noushin Behboudi , Sobhan Moosavi , Rajiv Ramnath

As a key indicator of unsafe driving, driving volatility characterizes the variations in microscopic driving decisions. This study characterizes volatility in longitudinal and lateral driving decisions and examines the links between driving…

General Economics · Economics 2020-10-13 Behram Wali , Asad Khattak , Thomas Karnowski

This study investigates pedestrian crash severity through Automated Machine Learning (AutoML), offering a streamlined and accessible method for analyzing critical factors. Utilizing a detailed dataset from Utah spanning 2010-2021, the…

Machine Learning · Computer Science 2024-06-17 Amir Rafe , Patrick A. Singleton

Work zone safety is influenced by many risk factors. Consequently, a comprehensive knowledge of the risk factors identified from crash data analysis becomes critical in reducing risk levels and preventing severe crashes in work zones. This…

Computers and Society · Computer Science 2021-04-15 Huthaifa I Ashqar , Qadri H Shaheen , Suleiman A Ashur , Hesham A Rakha

Highway traffic crashes exert a considerable impact on both transportation systems and the economy. In this context, accurate and dependable emergency responses are crucial for effective traffic management. However, the influence of crashes…

Machine Learning · Computer Science 2024-01-02 Shuang Li , Ziyuan Pu , Zhiyong Cui , Seunghyeon Lee , Xiucheng Guo , Dong Ngoduy

Vehicles equipped with automated driving capabilities have shown potential to improve safety and operations. Advanced driver assistance systems (ADAS) and automated driving systems (ADS) have been widely developed to support vehicular…

Applications · Statistics 2024-10-15 Shengxuan Ding , Mohamed Abdel-Aty , Natalia Barbour , Dongdong Wang , Zijin Wang , Ou Zheng

Road traffic casualties represent a hidden global epidemic, demanding evidence-based interventions. This paper demonstrates a network lattice approach for identifying road segments of particular concern, based on a case study of a major…

Applications · Statistics 2023-03-13 Andrea Gilardi , Jorge Mateu , Riccardo Borgoni , Robin Lovelace

Understanding the factors contributing to traffic crashes and developing strategies to mitigate their severity is essential. Traditional statistical methods and machine learning models often struggle to capture the complex interactions…

Machine Learning · Computer Science 2025-05-16 Ahmed S. Abdelrahman , Mohamed Abdel-Aty , Samgyu Yang , Abdulrahman Faden

Influencing factors on crashes involved with autonomous vehicles (AVs) have been paid increasing attention. However, there is a lack of comparative analyses between influencing factors on crashes of AVs and human-driven vehicles. To fill…

Applications · Statistics 2022-04-11 Weixi Ren , Bo Yu , Yuren Chen , Kun Gao , Shan Bao
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