Context-Based Visual Aids to Support the Situation Awareness of Field Engineers Conducting Windstorm Risk Surveys

Insurance loss prevention survey, specifically windstorm risk inspection survey is the process of investigating potential damages associated with a building or structure in the event of an extreme weather condition such as a hurricane or tornado. This process is performed by a trained windstorm risk engineer who physically goes to a facility to assess the wind vulnerabilities associated with it. This process is highly subjective, and the accuracy of findings depends on the experience and skillsets of the engineer. Although using sensors and automation enabled systems help engineers gather data, their ability to make sense of this information is vital. Further, their Situation Awareness (SA) can be affected by the use of such systems. Using a between-subjects experimental design, this study explored the use of various context-based visualization strategies to support the SA requirements and performance of windstorm risk engineers. The independent variable included in this study is the type of context-based visualizations used (with 3 levels: no visual aids, checklist based and predictive display based visual aids). We measured SA using SAGAT and performance using a questionnaire. SA and performance were found to be higher for the predictive display and checklist based conditions. The findings from this study will inform the design of context-based decision aids to support the SA of risk engineers.

Teleoperated Vehicle-Perspective Predictive Display Accounting for Network Time Delays

Variable network time-delays in data-transmission is the major problem in tele-operating a vehicle. Even on LTE network, variability of these delays is high (70–150 ms ping). This paper presents an innovative approach of providing the remote operator a forecasted video stream which replicates future perspective of vehicle’s FOV upon reception of maneuvering commands. First, vehicle position is predicted accounting for its speed and data transmission delays. Then perspective image transformation2 is performed to get exact new perspective of vehicle FOV corresponds to the predicted position. This approach addresses both issues, time-delays as well as its variability. Only one display, which shows frontward FOV is availed for mock-up.