Developing a model for predicting the number of freight accidents involving death and injury Using Genetic Planning

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Developing a model for predicting the number of freight accidents involving death and injury Using Genetic Planning

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Masoud Bagheri Ramiani / Gholamreza Shirazian

Today, due to the importance of transportation in developing countries, addressing the issues related to transportation safety planning has also become increasingly important. One of the important issues in the field of safety planning is the synchronization of safety planning with the stages of transportation planning and predicting large-scale accidents is one of its components. The purpose of this research is to present a mathematical model for predicting the number of severe road traffic accidents along with transport planning and determine the most appropriate planning stage for building macro level accident prediction models. In this paper, by examining the factors affecting accidents, the macro model is presented using genetic programming method. For this purpose, data from the years 2011 to 2014 were used as baseline data and statistics from year 2015 were used to validate the model. Based on the data of each planning step, separate models were developed and after comparison between them, the model based on travel production variables was identified as the optimal model. The results show that among the data corresponding to the transport planning stages, the variables of the trip generation stage are the most appropriate data set for modelling of predicting road freight accidents.