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Andrea Paliotto and Monica Meocci
Road safety is a central issue in the management and development of a road network. Road agencies must try to identify the most dangerous sections of their network and act on them to improve safety. The most used procedure for this purpose is about consi...
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Yongdong Wang, Haonan Zhai, Xianghong Cao and Xin Geng
The number of motor vehicles on the road is constantly increasing, leading to a rise in the number of traffic accidents. Accurately identifying the factors contributing to these accidents is a crucial topic in the field of traffic accident research. Most...
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Yang Shen, Changjiang Zheng and Fei Wu
Urban highway tunnels are frequent accident locations, and predicting and analyzing road conditions after accidents to avoid traffic congestion is a key measure for tunnel traffic operation management. In this paper, 200 traffic accident data from the Yi...
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Yunfei Zhang, Fangqi Zhu, Qiuping Li, Zehang Qiu and Yajun Xie
Exploring spatiotemporal patterns of traffic accidents from historic crash databases is one essential prerequisite for road safety management and traffic risk prevention. Presently, with the emergence of GIS and data mining technologies, numerous geospat...
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Rafiya Sohail, Yousaf Saeed, Abid Ali, Reem Alkanhel, Harun Jamil, Ammar Muthanna and Habib Akbar
Diabetes is a chronic disease that is escalating day by day and requires 24/7 continuous management. It may cause many complications, precisely when a patient moves, which may risk their and other drivers? and pedestrians? lives. Recent research shows di...
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Zhimin Yang, Xiangzhao Yan, Yutong Tian, Zaohong Pu, Yihan Wang, Chunhui Li, Yujun Yi, Xuan Wang and Qiang Liu
The issue of sudden water pollution resulting from accidents is a challenging environmental problem to address. The frequency of transport accidents involving hazardous materials over tributary bridges is steadily rising due to rapid industrialization an...
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Manlika Seefong, Panuwat Wisutwattanasak, Chamroeun Se, Kestsirin Theerathitichaipa, Sajjakaj Jomnonkwao, Thanapong Champahom, Vatanavongs Ratanavaraha and Rattanaporn Kasemsri
Machine learning currently holds a vital position in predicting collision severity. Identifying factors associated with heightened risks of injury and fatalities aids in enhancing road safety measures and management. Presently, Thailand faces considerabl...
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Mohammed Imran Basheer Ahmed, Rim Zaghdoud, Mohammed Salih Ahmed, Razan Sendi, Sarah Alsharif, Jomana Alabdulkarim, Bashayr Adnan Albin Saad, Reema Alsabt, Atta Rahman and Gomathi Krishnasamy
To constructively ameliorate and enhance traffic safety measures in Saudi Arabia, a prolific number of AI (Artificial Intelligence) traffic surveillance technologies have emerged, including Saher, throughout the past years. However, rapidly detecting a v...
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Jianyu Wang, Shuo Ma, Pengpeng Jiao, Lanxin Ji, Xu Sun and Huapu Lu
This study explores risk factors influencing the at-fault party in traffic accidents and analyzes their impact on traffic accident severity. Based on the traffic accident data of Shenyang City, Liaoning Province, China, from 2018 to 2020, 19 attribute va...
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Artur I. Petrov
The aim of this research is to study the specifics of the road accident rate formation processes in regions of the Russian Federation (2021) using information-entropic analysis. The typical research approaches (correlation-regression, factorial analyses,...
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