Development of Equations to Predict the Visual Demand of Driving Next Generation Combat Vehicles

Project begins Oct. 2021

The U.S. Army plans to field remotely-operated robotic combat vehicles. Those vehicles will be driven by soldiers in another moving vehicle. To develop a maximally effective vehicle and minimize crew size, it is important to predict the visual demand of driving, which is most of the workload that soldiers will experience.

The fundamental research question this project addresses: How does the workload of driving vary as a function of road or path geometry, the position and movement of other vehicles, sight distance, surface conditions, and other factors?

The results from this research pertain to the issues the Army faces, issues of takeover time for partially automated vehicles, concerns about when and which in-vehicle tasks should not be performed while driving, when certain roads will be too demanding for individuals with limited driving capabilities, and for other purposes.

Research Objectives:

1. The first objective of this project is to develop an improved implementation of the visual occlusion method that was employed in the Crew Optimization and Augmentation Technologies (COAT) program to determine the visual demand of driving tracked vehicles, in particular, Optionally Manned Fighting Vehicles/Robotic Combat Vehicles (OMFV/RCV).
2. The second objective is to develop and validate initial predictions of the demand of various driving situations as a function of relevant characteristics such as speed, road geometry (e.g., curve radius and deflection angle), traffic, and occlusion timing parameters and activation methods.

#2.A93