Supporting Real-Time Decision-Making Under Stress in an Online Training Environment

Abstract

Multi-agency crisis management represents one of the most complex real-world situations, requiring rapid negotiation and decision-making under extreme pressure. However, the training provided to Gold Commanders (strategic planners) typically lacks the stress of a real crisis, while research tells us that behavior and decision-making are significantly affected by stress. It is therefore vital that training puts trainees under the pressure of a real crisis situation as far as is possible. The Pandora + system, developed from an EU FP7 research project, provides a unique, original, realistic, immersive, augmented reality training environment in which the stress of each individual trainee can be managed by the trainer, during a training event, with the support of system intelligence. The system uses AI planning techniques to model an unfolding crisis scenario, realized as an event network which can be dynamically updated by the trainer during a training event. This modelling includes points of decision for trainees managed by automated rules from a knowledge base, behavioral modelling of the trainees, and dynamic management of the environment to provide affective inputs to control and manage trainee stress. In this context, the system controls and reacts to trainee performance in relation to the events and decision points and can dynamically remodel and reconfigure the event network to respond appropriately to trainee decisions. The environment can also represent any missing trainees within the scenario and has the potential to provide training in any domain where a timeline-based scenario of events is required for training. This entire approach is completely novel in crisis training and has been rigorously tested in several trials, the most recent involving close to 150 participants, and has the potential to transform online learning in many domains, not just crisis management.

Serious Games: An Attractive Approach to Improve Awareness

“…To ensure the design of the game scenario was as realistic as possible, an Senior Policing, Border and Security Consultant was engaged to design the game scenario. The game platform used was Pandora + (Bacon et al 2017), originally developed for the 2010-2012 EU FP7 project entitled "Advanced Training Environment for Crisis Scenarios" (Bacon et al 2012a, b;Mackinnon et al 2013). The Pandora + training tool is a cloud-based client-server system which runs on a desktop or mobile device.…”

Developing a Framework for Automated Scenario-Based e-Learning Design

“…Whilst a number of specialist products have been developed to provide support for SBeL development, such as Emergo [10] and Pandora + [11], the bulk of the existing SBeL implementations have been developed using existing tools, ranging from simple presentation tools with hyperlinks, through virtual learning environments, to animation and visualisation tools.…”

“…An alternative to a tabletop exercise is the simulation of a real part of a scenario which is very emotionally engaging however these exercises are extremely time consuming to design, prepare and execute, and ultimately can only yield a limited number of outcomes and typically run once. The Pandora + system is designed to find the middle ground [18] -immersive, emotionally engaging, quick to upload a scenario into the Pandora + system, with as many outcomes as the scenario author desires and be used repeatedly to train multiple groups of trainees. With a tabletop exercise a trainer may have limited capacity to adapt a scenario on the fly in response to the approach taken by a group of trainees to solving a problem, however in the Pandora + system the trainer has a variety of tools at their disposal to adapt the trainee experience during execution e.g.…”

Collaborative Decision-Making Method of Emergency Response for Highway Incidents

“…A large number of researchers have tried to use various methods to formulate emergency-decision-making procedures to improve the safety of road traffic: Khan conducted research on sustainable traffic safety in Hong Kong based on the Bayesian network method, in which accident risk factors are introduced into the analysis of real accident reports [7]; Ding proposed a zero-sum game method containing Pythagorean fuzzy uncertain linguistic variables, which improved the fuzziness of decision makers' evaluation data in emergency situations for road emergency decision making [8]; J. Pérez González has developed an analytical network platform to conduct time-space distribution statistics and display of the accident distribution information, thus providing information assistance and support for the decision making of emergency personnel [9]; Wang's interval dynamic reference point method based on prospect theory introduces psychological factors into the consideration of emergency decision making, effectively improving the rationality of emergency decision making [10]. The above research has made unique contributions to the field of emergency decision making, but there are few studies on the emergency disposal processes of road accident scenes, especially regarding the team cooperation of various departments and the emergency disposal process, which need to be further improved [11][12][13].…”