Conceptual Model of a Self-Organizing Traffic Management Hazard Response System

Abstract

The terrorist attacks of September 11, 2001, have sparked renewed interest in developing effective policies and strategies for evacuating densely populated areas. The current analytical tools for dealing with such evacuations are sorely lacking in both theory and practice. The conceptual model presented joins the technical areas of cellular automatons, evolutionary computation, and transportation science with some recent research on infrastructure security to make significant progress in traffic management and hazard response systems. The overall goal of this research is to develop a fundamental understanding of the evolutionary and emergent behavior of transportation systems that are operating under emergency evacuation conditions. This new knowledge can be used to develop more effective operational strategies and consequently more robust hazard response systems. Furthermore, the specific research objective is to investigate the formulation and application of cellular automaton models of metropolitan transportation systems, with a focus on systems operating under emergency evacuation conditions. The basic context is evacuation of a defined urban area, such as the urban core of Washington, D.C., under terrorist attacks. The conceptual model proposes the use of evolutionary algorithms to search the space of the evacuation control strategies and determine the most successful strategies for a given urban area.