Preprint Article Version 1 This version is not peer-reviewed

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

Version 1 : Received: 5 August 2019 / Approved: 6 August 2019 / Online: 6 August 2019 (12:53:49 CEST)

A peer-reviewed article of this Preprint also exists.

Van Pham, H.; Moore, P. Emergency Service Provision Using a Novel Hybrid SOM-Spiral STC Model for Group Decision Support under Dynamic Uncertainty. Appl. Sci. 2019, 9, 3910. Van Pham, H.; Moore, P. Emergency Service Provision Using a Novel Hybrid SOM-Spiral STC Model for Group Decision Support under Dynamic Uncertainty. Appl. Sci. 2019, 9, 3910.

Journal reference: Appl. Sci. 2019, 9, 3910
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 \emph{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.

Subject Areas

self organizing maps; fuzzy rules; emergency planning and management; group decision support; autonomous robot control; smart-environments

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