Investigation and Analysis on Evacuation Behavior of Large Scale Population in Campus

Abstract

The field investigation on the crowd evacuation behavior of young people is carried out in Northeastern University of Shenyang under time pressure, such as the class break at 9:55-10:05am and the lunchtime at 11:55-12:15am.The database of pedestrian walking velocity of different behavior characteristics is established and the large scale crowd evacuation behavior characteristics are analyzed. Based on the application of the Self-adaptive Ant Colony Optimization Algorithm, the large scale evacuation path is optimized to the whole scale. Based on the academic pedestrian flow investigation and the route optimization analysis, the large scale evacuation behavior in campus is simulated and compared by FDS+Evac. The analysis results show that the personnel flow coefficient will be increasing under time pressure, and the crowding will be produced easier as the same reason. Large scale evacuation plan can be optimized based on the Self- adaptive Ant Colony Optimization Algorithm, which can not only reduce the Real Safety Evacuation Time (RSET) on the whole scale, it can also effectively alleviate the congestion of the crowd in the main exit of evacuation route.