Analysis of Historical Accident Data to Determine Accident Prone Locations and Cause of Accidents

被引：1

作者：

Ifthikar, Arshardh ^{[1
]}

Hettiarachchi, Saman ^{[1
]}

机构：

[1] Informat Inst Technol, Dept Software Engn, Colombo, Sri Lanka

来源：

2018 8TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEMS, MODELLING AND SIMULATION (ISMS) | 2018年

关键词：

Data Mining; Road Traffic Accidents; Clustering Algorithms; Global Positioning System; Autonomous automobiles;

D O I：

10.1109/ISMS.2018.00012

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Road traffic accidents is a severe issue which causes great distress and destroys lives of many individuals. In spite of different attempts to solve this problem, it still resides as a major cause of death. This paper discusses several attempts made to identify causes for road accidents. Finally, a system is proposed to analyze 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.

引用

页码：11 / 15

页数：5

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