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Vehicle Controls & Behaviors

Annual Plan

Advanced Hazard Avoidance in Autonomous Ground Vehicles

Project Team

Principal Investigator

Jeffrey L. Stein, University of Michigan Tulga Ersal, University of Michigan

Government

Paramsothy Jayakumar, U.S. Army GVSC

Industry

Mitchell Rohde, Steve M. Rohde, Quantum Signal LLC

Student

Huckleberry Febbo, University of Michigan

Project Summary

Project began mid-2016 for a length of 2 years.

Vehicle path output

Communication delays and reduced situational awareness negatively affect mobility performance in teleoperation. Purely simulation based studies are not yet feasible due to the challenges with modeling human teleoperators. How to divide the control authority between the human operator and autonomy for best performance, both with and without communication delays, is a research question for the semi-autonomous mode. How much improvement in performance semi-autonomy can offer is also an open research question. Finally, one of the research challenges in the fully autonomous mode of operation is to push the vehicle to its performance limits in an unknown, unstructured environment.

The research objective is threefold: (1) incorporate results of prior research that include a 2D LIDAR model and 14 DoF vehicle model; (2) extend the formulation to add in an algorithm that detects and tracks moving obstacles; and (3) characterize the performance of the formulation to be able to handle moving obstacles through simulation studies under various scenarios with different number of obstacles, speeds, directions, and sizes.

This project extends the mobility of autonomous ground vehicles by including moving obstacles in the formulation of the obstacle avoidance algorithm that was developed in ARC Project “Vehicle-Dynamics-Conscious Real-Time Hazard Avoidance in Autonomous Ground Vehicles”.

Publications:

  • Febbo, H, Liu, J.; Jayakumar, P.; Stein, J. L. and T. Ersal, “Moving obstacle avoidance for large, high-speed autonomous ground vehicles,” in proceedings American Control Conference, Seattle, WA, 2017. doi:10.23919/ACC.2017.7963821