Abstract
As is the case in most countries of the world Traffic accidents are a major problem in the Gaza City, the number of traffic accidents increased significantly from 2017 to 2018, and the number of traffic accidents was higher than the normal rate. Most of the methodologies that have been developed to identify danger points for traffic accidents do not achieve the required level and decision maker can take correct actions after understanding the local factors that contribute significantly to traffic accidents. In this study, a new methodology will be developed to predict and identify the locations of traffic accidents and to identify the factors that contribute to the occurrence of traffic accidents. Through this study, a distance of 13.06 km was chosen as a case study to predict the locations of traffic accidents on those roads.
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References
World Health Organization report on traffic accident statistics. https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries
Gaza Municipality (traffic accident sites—road data)
Traffic accident statistics in Gaza City: Ministry of Transport and Communications (2021)
Levels of Service for Road Transportation. https://transportgeography.org/contents/methods/transport-technical-economic-performance-indicators/levels-of-service-road-transportation/
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© 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG
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Qarrot, A., Alramlawi, K. (2024). Artificial Intelligence and Forecasting of Traffic Accidents Using GIS. In: Alareeni, B., Elgedawy, I. (eds) AI and Business, and Innovation Research: Understanding the Potential and Risks of AI for Modern Enterprises. Studies in Systems, Decision and Control, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-031-42085-6_56
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DOI: https://doi.org/10.1007/978-3-031-42085-6_56
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