Using a Game Engine to Simulate Critical Incidents and Data Collection by Autonomous Drones

TL;DR

This paper presents a virtual environment built with a game engine to simulate critical incident scenarios, enabling safe development and testing of AI systems for autonomous incident assessment and evidence gathering.

Contribution

It introduces a novel virtual simulation platform for training and validating AI-based autonomous systems in critical incident scenarios before real-world deployment.

Findings

Effective virtual environment for simulating CBRNe incidents

Prototype system using simulated RAVs for environmental mapping

Facilitates safe testing of AI methodologies for incident assessment

Abstract

Using a game engine, we have developed a virtual environment which models important aspects of critical incident scenarios. We focused on modelling phenomena relating to the identification and gathering of key forensic evidence, in order to develop and test a system which can handle chemical, biological, radiological/nuclear or explosive (CBRNe) events autonomously. This allows us to build and validate AI-based technologies, which can be trained and tested in our custom virtual environment before being deployed in real-world scenarios. We have used our virtual scenario to rapidly prototype a system which can use simulated Remote Aerial Vehicles (RAVs) to gather images from the environment for the purpose of mapping. Our environment provides us with an effective medium through which we can develop and test various AI methodologies for critical incident scene assessment, in a safe and controlled manner