Optimal path selection using cellular automation with the difficulty model of roadway

In the case of disaster,the vast majority of emergency rescue is simply taking into account the speed of evacuation and safety exit distance to ignore the actual roadway environment complexity. In order to solve this problem,this study introduces a new concept of difficulty degree of roadway and establishes a difficulty degree model of escape roadway. The complex environment of the roadway is divided into four parts,including the up and down slope parts,the horizontal section and the concave and convex obstacle section. Then,the difficulty degree of roadway is characterized by the oxygen uptake and the actual distance of roadway,the slope of roadway and the degree of barrier. In order to achieve the goal of quantitative mathematical analysis and risk assessment,the complexity of the roadway environment is quantified,which is convenient for choosing an optical path. The application of the improved cellular automation to the directed weighted graph provides a new way to find an optimal path for emergency rescue.