Identification of High Crash Road Segment using Genetic Algorithmand Dynamic Segmentation

This paper presents an evolutionary algorithm for recognizing high and low crash road segments usingGenetic Algorithm as a dynamic segmentation method. Social and economic costs as well as physical andmental injuries make the governments perceiving to road safety indexes in order to diminish theconsequences of road accidents. Due to the limitation of budget for safety improvement of all parts of theroad, the road segments with more accidents should be recognized for safety budget assignment. So,considering this fact it s important to identify the segments with high and low number of accidents tooptimize the road safety program. In this study, a novel chromosome coding method and a fitness functionwhich are consistent with Genetic Algorithm are proposed. The proposed methodology is also validated byusing two mathematical parameters so that the results confirm that the proposed modeling works properly.Afterward, the proposed dynamic segmentation method is compared with the other static segmentationmethods along 51 km of Shahrood–Sabzevar highway. The proposed method may have more advantagescomparing to static segmentation methods for all of the performance indexes which were considered in thisstudy. The proposed method has a variance about two times higher than the one for accident density incomparison with the other static segmentation methods. About 62% and 34% improvement is achieved inaverage of segments accident density and total segments density respectively in comparison with the otherfixed methods.

Keywords:

Genetic Algorithm , dynamic segmentation , road accident segments