Emergency Service Provision Using a Novel Hybrid SOM-Spiral STC Model for Group Decision Support under Dynamic Uncertainty

Hai Van Pham,Philip Moore

doi:10.3390/app9183910

Abstract

In emergency scenarios service vehicles must identify potential route(s) and use the best available route. However, route identification requires intelligent decision-support systems which generally use non-traditional approaches with tools characterised by flexible non-hierarchical structures. Conventional models using group decision-support systems have been applied; however, when used in smart urban environments, emergency response services have limitations in their ability to identify unobstructed paths (routes) in dynamic operating environments. In this paper we introduce a novel path planning method for autonomous vehicle control in emergency situations. The proposed model uses self-organizing maps in an integrated Spiral STC algorithm termed the: Hybrid SOM-Spiral STC model which uses hedge algebras and Kansei evaluation in group decision-support. The proposed model has been designed to quantify qualitative factors using sensor derived data processed with human sensibilities and preferences in emergency decision support. The experimental results show that the proposed model achieves significant improvements in group decision-support under dynamic uncertainty. We posit that our novel approach holds the prospect of improvements in the provision of emergency services.

Highlights

The world has experienced a paradigm shift in the mode of living with a transition from rural living to a growing urban population [1]
Let X S = { X1S, X2S, . . . , Xm alternatives in evaluating an emergency situation where m is the number of Kansei words; Assume that quantification of human sensibilities using in decision making can be presented in an emergency situation domain S; Optimized Kansei words in X S are used to evaluate alternatives which belong to the criteria and factors S; S; Let WmS = {Wm−, Wm+ } be adjective pairs of Kansei words belonging to Xm
In order to evaluate the effectiveness of the proposed system in simulation of disaster response, the performance of the proposed model is calculated from: (a) the average of ratings between times, and (b) the number of objectives involved in selection of the appropriate service vehicle(s) based on the available routes in the emergency zone

Summary

Introduction

The world has experienced a paradigm shift in the mode of living with a transition from rural living to a growing urban population [1]. The United Nations predict that on a global basis the urban population will reach 61% by 2030 and will eventually reach a “dynamic equilibrium of approximately 80% urban to 20% rural dwellers that will persist for the foreseeable future” [1]. This transition presents a number of challenges which include many socio-economic, demographic, economic, cultural, and environmental considerations [1]. The literature provides abundant examples of research into these challenges; the growth of urban environments presents significant problems for authorities in the effective provision of emergency services. A primary concern for authorities tasked with the provision of emergency services is the ability to travel in urban areas efficiently, this is an area that has received

Methods

Results

Conclusion