Looking Glass

Introduction

A city is administered by a set of agencies, businesses and institutions, each of which is governed by different protocols, objectives and constraints. However, responding to complex situations requires a “shared common operating picture and situational awareness” (Harrald, 2007). Human decisions often must be made without the ability to quickly assess consequences due to the multifaceted interdependencies of all affected systems, either because they are not covered by protocol or because no solution within the required constraints exists. People also adjust their behavior to abnormalities within their surroundings (e.g., unexpected closure of a metro station). Such actions may affect the ability to execute established protocols (e.g., dispatching emergency crews, evacuating people).

Looking Glass is a system in which a shared common operating environment can be maintained and effects of decisions can be explored. The scenario addressed by Looking Glass in its first release is the responses to a complex emergency event (a toxic release in a busy metro station) to demonstrate the ability of linked simulation based models to provide unique insights and support to responsible organizations and individuals. The discovery and exploration of the effects of interdependencies between interconnected urban systems and human behaviors is the objective of Looking Glass. Since it is not feasible to build and maintain a single “world model” spanning all interconnected and interdependent systems, Looking Glass assumes that each system (in this system of systems) is modeled in its own right. Examples of such systems are traffic simulation, human behavior and weather models. Connections between systems do not have to be explicitly specified; their interdependencies in a given situation are discovered through simulation, taking varied human behavior (decisions) into account. For example, during a simulation, a human can interactively trigger an event such as closing a road, or change the rate of pedestrian traffic at certain locations. A key aspect is that each system (e.g., weather model, car and pedestrian traffic, emergency vehicle dispatch scheduler) is assumed to be a “black box” with only the inputs and outputs known. This assumption mimics the real world where independent agencies create their own protocols and assets according to given constraints and optimization goals, and humans frequently act differently than anticipated. With Looking Glass, one is able explore the impacts that even seemingly small human decisions have on situations that have been carefully planned. A visualization engine and business intelligence application are part of Looking Glass, however, the system is not tied to any particular realization of these engines.

Review Of Literature

Emergency response planning, training and incident impact are being studied extensively by government agencies, academic institutions and commercial companies alike. It is an ever-evolving area, as preparedness is only as good as the assumptions on which it is based. However, there seem to be an infinite number of circumstances for emergencies to occur. Protocols, at times, provide multiple decision points on how to address a situation. However, an incident commander cannot analyze all possibilities by him/herself to decide on the most appropriate course of actions, so tooling is a necessary aid.