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Human-Autonomy Interaction

Annual Plan

Dynamic Task Allocation and Understanding of Situation Awareness Under Different Levels of Autonomy in Closed-Hatch Military Vehicles

Project Team

Principal Investigator

Cindy Bethel, Mississippi State University Daniel Carruth, Mississippi State University

Government

Victor Paul, U.S. Army GVSC

Industry

Kartik Tiwari, Starsky Robotics

Student

Jessie Cossitt

Project Summary

Project begins in 2020, estimated duration of 3 years.

This research is based around the need to better understand how humans and autonomous vehicles can work together in order to provide the best case scenario for the successful completion of military missions and utilization of autonomous capabilities. Previous attempts to determine optimal allocation of tasks have allocated the tasks statically. This is not an ideal method for task allocation although it is manageable and more easily implemented.

The proposed research effort focuses on the use and evaluation of dynamic task allocation based on human-computer interaction concepts and physiological responses during multi-modal dynamic task requests in military missions. This effort is one of the first to investigate comprehension of road events under different levels of autonomy in virtual reality simulations.

Effects of automation on vehicle crew member primary and secondary task performance and ultimately the optimization of an intelligent system for allocating secondary tasks across crew members will be studied. There is significant interest in how automated driving systems may allow a vehicle operator to address secondary tasks. This project will investigate how such a system will affect the operator’s ability to monitor the primary driving task and respond if human intervention is required. Improved understanding of how automation and increased secondary tasking affect operator performance will lead to improved system designs that support effective management of crew member cognitive resources and tasks. Effective task allocation will be critical to efforts to reduce the number of crew members using automation.

Prior publications related to this work:

  1. Durst, P., Goodin, C., Bethel, C. L., Anderson, D. T., Carruth, D. W., Lim, H. “A Perception-Based Fuzzy Path Planner for Autonomous Unmanned Ground Vehicles.” Published in World Scientific Unmanned Systems Journal. DOI: https://doi.org/10.1142/S2301385018500073. Volume 06, Issue 4, pages 251-266. November 16, 2018.
  2. Strawderman, L., King, K., & Carruth, D. (2018). Improving Safety of Vulnerable Road Users: Effectiveness of Environment and In-Vehicle Warning Systems at Intermodal Exchanges. Journal of Transportation Safety & Security, 10(3), 177-192. http://dx.doi.org/10.1080/19439962.2016.1237598..
  3. Durst, P. Anderson, D. Bethel, C. L., “A Historical Review of the Development of Verification and Validation Theories for Simulation Models.” Published in the International Journal of Modeling, Simulation, and Scientific Computing. DOI: 10.1142/S1793962317300011 (January 2017). Volume 8, Issue 2, 2017. (Impact Factor: 0.213).
  4. Bethel, C. L. and Murphy, R. R., “Review of Human Studies Methods in HRI and Recommendations,” in International Journal of Social Robotics, DOI: 10.1007/s12369-010-0064-9 (July 2010). Volume 2, Issue 4. 2010. December 2010. (Impact Factor: 2.559)