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)

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.