Optimal Control, Pairing, and Scheduling for Manned-Unmanned Vehicles Teaming based on RoboTrust Algorithms

Principal Investigators: Yue Wang, Clemson University, yue6@clemson.edu
John Wagner (co-PI), Clemson University, jwagner@clemson.edu
Student: Fangjian Li, Clemson University
Government: Dariusz Mikulski, U.S. Army TARDEC
Industry: Andrew Dallas, SoarTech

The research objectives of this proposal are to establish trust-based optimal switching control, dynamic pairing, and real-time scheduling algorithms for manned and unmanned vehicles teaming. This work seeks to (i) fill the gap in our fundamental understanding in human-robot collaboration (HRC) systems and trust dynamics, (ii) create quantitative models for the HRC systems capturing dynamic levels of autonomy (LOAs) and vehicle trustworthiness based on the RoboTrust algorithm developed at the Army, (iii) establish a general trust-based framework for manned and unmanned teaming, and (iv) perform Matlab simulations over distributed and heterogeneous multi-agent systems with human-in-the loop.

Related Publications:

  • Nianfeng Wan, Ardalan Vahidi, and Andre Luckow, "Optimal Speed Advisory For Connected Vehicles in Arterial Roads and The Impact on Mixed Traffic," in press, Transportation Research, Part C, 2016. doi:10.1016/j.trc.2016.01.011
  • Nianfeng Wan, Ardalan Vahidi, and Andre Luckow, "Reconstructing Maximum Likelihood Trajectory of Probe Vehicles Between Sparse Updates," Transportation Research, Part C, Vol. 65, pp. 16–30, April 2016. doi:10.1016/j.trc.2016.01.010