Weather simulation for human-in-the-loop and robotic vehicle training: A literature review and new modeling approach
Presenter Email
johnsoc4@erau.edu
Keywords
Weather, Weather Simulation, Simulation, Modeling, Virtual Reality, Augmented Reality, Mixed Reality, Extended Reality, VR, AR, MR, XR, Automation, Robotics, Autonomous Vehicles, Unmanned Vehicles, Artificial Intelligence, AI
Abstract
For decades preceding the advent of “metaverse” becoming a household term, simulation developers and researchers have continued to narrow the gap between digital twins and the high-risk work domains that they replicate. However, the literature review that is reported in this study reveals a void in understanding of how to properly simulate weather in training-based simulations and extended-reality contexts. Inclement weather adversely affects human performance. It can dictate restrictive attire, impact hydration and fatigue, obscure perception, constricts transportation and force asset distribution and bed-down. Similarly, inclement weather can adversely affect autonomous vehicle performance. It can obscure and/or degrade remote sensors, interfere with electro-magnetic frequencies and compromise electro-mechanical components and computing systems. Given these consequential performance factors, simulating weather for human-in-the-loop and robotic-vehicle training seems important, and although several publications emphasized the need for accurate weather simulation to improve simulation fidelity and realism, the literature review reported in this paper did not reveal any concrete methods for accurately simulating dynamic visual and non-visual weather conditions using sound, defensible modeling techniques. In fact, no simulation methods were found that properly correlate visual and non-visual weather affects with weather-information resources that humans and machines use to detect and avoid inclement weather, so this paper also explains why that is important and introduces a method for properly simulating weather accordingly. Findings of the literature review are discussed herein, highlighting inadequacies in simulation methodology that can be overcome as practitioners and researchers employ the proposed weather-simulation method that is also detailed herein.
Weather simulation for human-in-the-loop and robotic vehicle training: A literature review and new modeling approach
For decades preceding the advent of “metaverse” becoming a household term, simulation developers and researchers have continued to narrow the gap between digital twins and the high-risk work domains that they replicate. However, the literature review that is reported in this study reveals a void in understanding of how to properly simulate weather in training-based simulations and extended-reality contexts. Inclement weather adversely affects human performance. It can dictate restrictive attire, impact hydration and fatigue, obscure perception, constricts transportation and force asset distribution and bed-down. Similarly, inclement weather can adversely affect autonomous vehicle performance. It can obscure and/or degrade remote sensors, interfere with electro-magnetic frequencies and compromise electro-mechanical components and computing systems. Given these consequential performance factors, simulating weather for human-in-the-loop and robotic-vehicle training seems important, and although several publications emphasized the need for accurate weather simulation to improve simulation fidelity and realism, the literature review reported in this paper did not reveal any concrete methods for accurately simulating dynamic visual and non-visual weather conditions using sound, defensible modeling techniques. In fact, no simulation methods were found that properly correlate visual and non-visual weather affects with weather-information resources that humans and machines use to detect and avoid inclement weather, so this paper also explains why that is important and introduces a method for properly simulating weather accordingly. Findings of the literature review are discussed herein, highlighting inadequacies in simulation methodology that can be overcome as practitioners and researchers employ the proposed weather-simulation method that is also detailed herein.
Comments
Presented in Session 2 A - AR, VR, & Weather Simulation: Advances in Training