Fairness and efficiency in pedestrian emergency evacuation: Modeling and simulation

The goal of this paper is to study different algorithms for planning a large scale pedestrian evacuation process. A pedestrian (walking) mode of evacuation is an efficient mode of transportation that is often overlooked in the literature. Fairness in the evacuation process is another aspect that is rarely studied. In this paper, we study efficiency and fairness of pedestrian mode of emergency evacuation. We model the evacuation problem as a dynamic network flow problem, which captures the time-dependency of the network attributes such as edge and vertex capacities and edge travel times. To evaluate the efficiency of the algorithms, we consider the clearance time of the network. To investigate fairness, we consider the Gini coefficient and Lorenz curve that are popular indexes in economy to measure wealth distribution in a society. We compute the Gini coefficient and Lorenz curve to measure the fairness in travel time distribution of the evacuees in the emergency evacuation process. We develop a new algorithm called PEPA (Pedestrian Evacuation Planning Algorithm) to find the minimum clearance time of the network. PEPA is compared to two commonly studied graph algorithms in the literature, shortest path and maximum flow algorithms. We compared the algorithms in terms of computation time of the algorithm, clearance time of the network and Gini coefficient. Our results show that PEPA beats both shortest path and maximum flow in terms of efficiency and fairness, although it is slightly slower in terms of computation time. To implement PEPA, shortest path and maximum flow algorithms, we develop a new software named PEMSS (Pedestrian Evacuation Modeler, Solver, and Simulator). PEMSS is written in the Java programming language and is capable of reading and showing maps in open street map XML format.