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

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.

Effects of Air Route Alternation and Display Design on an Operator’s Situation Awareness, Task Performance and Mental Workload in Simulated Flight Tasks

“…SA can be a significant concern, especially in abnormal environments, where operators are required to respond immediately and appropriately to unexpected events or emergencies. In these scenarios, demands on the operators' SA can be even higher so that the operators' mental resources may not be able to provide sufficient support for good task performance, thereby leading to human errors [13][14][15][16].…”

Informatics and the Challenge of Determinism

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