Study On Urban Flood Evacuation Model Based On Cellular Automata

With the rapid development of urbanization,the urban impervious underlying surface increases sharply,resulting in the increase of surface runoff and runoff coefficient,urban flood problem is becoming increasingly prominent,making a reasonable emergency evacuation plan for flood disaster has important practical significance to ensure the safety of people's lives and property.The traditional flood disaster emergency evacuation mainly adopts evacuation drills to improve people's emergency evacuation awareness.Compared with the way of drills,the establishment of flood emergency evacuation model can express the evacuation process scientifically and quantitatively,which has become the focus of emergency evacuation research.At present,most of the flood emergency evacuation research is to formulate and optimize the shortest evacuation path through the macroscopic generalization model,and often fails to consider the reasonable evacuation behavior of people,resulting in the problems of low efficiency and limited vision of the relevant path planning algorithm.The evacuation model based on cellular automata can deduce the reasonable evacuation behavior of people from the microscopic point of view through appropriate rules,so as to provide reference and guidance for urban flood control and disaster reduction emergency plan,and has important significance for improving the emergency evacuation capacity of flood disasters.This paper established the emergency evacuation model of flood disaster based on the cellular automata theory,and on the basis of the research on the optimization of the global shortest path algorithm for static obstacles,a dynamic path optimization algorithm for flood process is developed,which realizes the expansion from single evacuation to crowd evacuation,and simulates the emergency evacuation process of flood disaster.The main conclusions are as follows:?1?The optimization of global shortest evacuation path algorithm based on cellular automata.A global shortest path optimization algorithm based on cellular automata is proposed by constructing the detour distance field under static obstacle distribution and setting the minimum detour rule,and the GSPCA₂D pattern algorithm for plain cities and GSPCA₃D pattern algorithm for mountainous and hilly cities are proposed.Compared with the heuristic search algorithm?A* algorithm?,it can avoid the phenomenon of wall-attached detour.The average number of time steps is reduced by 11.09 %,the average path length is reduced by 12.39 %?GSPCA₂D?,16.82 %?GSPCA₃D?,the solution efficiency is higher,and the search path is better.?2?The dynamic optimization model of evacuation path in flood process.By constructing the detour distance field in flood process and setting the dynamic minimum detour rule considering the initial pre-judgment time,a dynamic optimization algorithm of evacuation path in flood process based on cellular automata?FPPCA?is proposed.This algorithm can quickly solve the accurate optimal evacuation time range for different geographic locations by combining with the flood process,and optimize safer dynamic evacuation path.?3?The crowd evacuation model in flood process.By designing the crowed state and considering the crowds' competition relationship,the FPPCA single evacuation algorithm is extended to crowd evacuation algorithm in flood process.This algorithm can not only simulate the location and time of congestion,and predict paths with large traffic in the evacuation process,but also simulate the possible trapped location and estimate the minimum time of flood emergency evacuation.