Characterizing road accidents in urban areas of Bogota (Colombia): A data science approach

2019 2nd Latin American Conference on Intelligent Transportation Systems (ITS LATAM) Pub Date : 2019-03-01 DOI:10.1109/ITSLATAM.2019.8721334

Camilo Gutierrez-Osorio, C. Pedraza

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引用次数: 3

Abstract

This paper analyzes a data set that contains reports of road accidents reported by the Municipal government of Bogota city, which occurred between 2016 and 2017, by using descriptive analysis and rule-model algorithms. The main objective is to characterize the road accident data and to highlight the variables that show a significant impact on the type of road accident. The results obtained shows the increase of road accidents by rush hour, from 6:00 to 8:00, one minor group from 12 m to 15:00 and another main group, from 17:00 to 19:00. Also, considering the day of the week, the days with the highest traffic accident frequency were Tuesday, Friday and Saturday. The rules-model obtained allowed to find out that the variables hour, day of week, locality and road geometry show a meaningful effect on the type of traffic accident; the model also allows to infer that the weather conditions does not pose a significant impact on assessing the type of traffic accident. The proposed rule model can be useful to propose accident prevention campaigns and to be incorporated into a traffic control system.

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波哥大(哥伦比亚)城市地区道路交通事故特征:数据科学方法

本文通过描述性分析和规则模型算法，分析了波哥大市政府报告的2016年至2017年期间发生的道路交通事故报告的数据集。主要目标是描述道路事故数据的特征，并突出显示对道路事故类型有重大影响的变量。结果表明:交通高峰时段(6:00 - 8:00)交通事故增加;交通高峰时段(12:00 - 15:00)交通事故增加;交通高峰时段(17:00 - 19:00)交通事故增加;此外，从一周的天数来看，交通事故发生频率最高的日子是周二、周五和周六。所得到的规则模型表明，小时、星期、地点和道路几何等变量对交通事故类型有显著影响;该模型还允许推断天气条件对评估交通事故类型没有重大影响。所提出的规则模型可用于提出事故预防活动，并可纳入交通控制系统。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2019 2nd Latin American Conference on Intelligent Transportation Systems (ITS LATAM)

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