Abstract
Injuries due to road accidents are one of the most prevalent causes of death. The World Health Organization states that approximately 1.35 million people die each year as a result of road traffic crashes. That is, a person is killed every 25 s and from 20 to 50 million more people suffer non-fatal injuries. This calls for the need to analyze road accidents and the factors affecting them. This paper aims to provide that the information from traffic volume, traffic statistics and weather can improve the prediction of road accident hotspots through clustering algorithms in machine learning and advanced techniques for analyzing information.
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Ravikanth, K., Chandra Shekar, K., Shashi Kethana, K., Sai Praveena, V., Sharon Rachel, C. (2022). Identification of Accident Hotspots Using Clustering Algorithms in Machine Learning. In: Saini, H.S., Sayal, R., Govardhan, A., Buyya, R. (eds) Innovations in Computer Science and Engineering. Lecture Notes in Networks and Systems, vol 385. Springer, Singapore. https://doi.org/10.1007/978-981-16-8987-1_65
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DOI: https://doi.org/10.1007/978-981-16-8987-1_65
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