Please use this identifier to cite or link to this item:
http://repository.kln.ac.lk/handle/123456789/19030
Title: | Analysis of historical accident data to determine accident prone locations and cause of accidents |
Authors: | Ifthikar, A. Hettiarachchi, S. |
Keywords: | Autonomous automobiles Clustering algorithms Data mining Global positioning system Road traffic accidents |
Issue Date: | 2018 |
Publisher: | International Research Conference on Smart Computing and Systems Engineering - SCSE 2018 |
Citation: | Ifthikar,A. and Hettiarachchi,S. (2018). Analysis of historical accident data to determine accident prone locations and cause of accidents. International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka. p.182. |
Abstract: | Road traffic accidents causes great distress and destroy the lives of many individuals. Inspite of different attempts to solve this problem, it still resides as a major cause of death. This paper proposes a system to analyse historical accident data and subsequently identify accident-prone areas and their relevant causes via clustering accident location coordinates. This system, once developed, can be used to warn drivers and also to aid fully autonomous automobiles to take precautions at accident-prone areas. |
URI: | http://repository.kln.ac.lk/handle/123456789/19030 |
Appears in Collections: | Smart Computing and Systems Engineering - 2018 (SCSE 2018) |
Files in This Item:
File | Description | Size | Format | |
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SCSE Proceedings - (182).pdf | 521.23 kB | Adobe PDF | View/Open |
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