A fuzzy logic model for identifying spatial degrees of exposure to the risk of road accidents (Case study of the Wilaya of Mascara, Northwest of Algeria)

M. Driss, Thierry Saint-Gérand, A. Bensaid, K. Benabdeli, M. Hamadouche
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引用次数: 10

Abstract

The significant growth generally observed in road transportation has led to serious human and economic losses as a result of road accidents. This observation calls for considerable attention from civil security policies and requires a precise and rigorous identification of public action priority sectors. In this paper, we propose a traffic accident prediction system based on fuzzy logic which allows to identify “the degree of exposure to road accidents' risk”, and to analyze the level of complexity of the factors involved. We focus our study on the possible influence of a series of local criteria observed and selected for each kilometer per segment of the road network studied. The study was conducted on a road network within the rural area of the Wilaya of Mascara in the northwestern region of Algeria. After data analysis and simulation conducted using Matlab/Simulink, a series of logical rules using multiple fuzzy membership functions were implemented on the evaluation criteria observed. The evaluation system has an adaptive capacity and an automatic learning advantage and provides a very important contribution as a treatment system contributing to measure the risk of road accidents to improve the level of safety on the roads. A Geographic Information System (GIS) was integrated into the analysis process to enable a spatial visualization of the degrees of exposure to road accidents' risk, providing a cartographically measurable solution to establish and attenuate accident risk. Results show that the developed system can be effectively applied as a useful Road Safety tool capable of identifying risk factors related to the characteristics of the road.
用于识别道路交通事故风险空间暴露程度的模糊逻辑模型(以阿尔及利亚西北部马斯卡拉村为例)
道路运输的普遍显著增长已导致道路事故造成严重的人员和经济损失。这一观察结果要求民事安全政策予以相当重视,并要求精确和严格地确定公共行动优先部门。本文提出了一种基于模糊逻辑的交通事故预测系统,该系统可以识别“道路事故风险暴露程度”,并分析所涉及因素的复杂程度。我们的研究重点是为所研究的路网每段每公里观察和选择的一系列局部标准可能产生的影响。这项研究是在阿尔及利亚西北地区马斯卡拉维拉亚农村地区的一个公路网上进行的。通过Matlab/Simulink进行数据分析和仿真,对观察到的评价标准实施一系列利用多个模糊隶属函数的逻辑规则。该评价系统具有自适应能力和自动学习优势,为衡量道路交通事故风险,提高道路安全水平提供了重要的处理系统。将地理信息系统(GIS)集成到分析过程中,以实现道路事故风险暴露程度的空间可视化,为建立和降低事故风险提供制图上可测量的解决方案。结果表明,所开发的系统可以有效地作为一个有用的道路安全工具,能够识别与道路特征相关的危险因素。
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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