Inner-Loop Command Governors for Adaptive Cruise Control in Heavy-Duty Trucks.

GROELKE, BENJAMIN J. Inner-Loop Command Governors for Adaptive Cruise Control in Heavy-Duty Trucks. (Under the direction of Dr. Christopher Vermillion.) In automobiles, cruise control is no longer a convenience feature aimed solely at improving driver comfort. Advances in Vehicle-to-Vehicle (V2V) and Infrastructure-to-Vehicle (I2V) communication technologies have pushed forward new predictive cruise control strategies that leverage knowledge of the driving scenario (such as route terrain and traffic) to improve fuel economy and safety. Predictive cruise control strategies have the potential to be especially beneficial for heavy-duty trucks, which consume large amounts of fuel and are capable of inflicting significant damage to surrounding vehicles if operated incorrectly. The research contained within this dissertation aims to fuse fuel efficiency with safe vehicle following for heavy-duty vehicles. The research presented in this dissertation develops a longitudinal vehicle control framework where various upper-level driving controllers can be cascaded with a command governor (CG) to enforce vehicle-following constraints. Command governors are predictive control schemes used solely to enforce constraints and are computationally inexpensive in comparison to other predictive control techniques, such as model predictive control (MPC). This allows the upper-level controllers to focus on other objectives like maintaining a certain velocity or minimizing fuel consumption through optimal control techniques. This controller design is especially beneficial for heavy-duty trucks, which require large horizon lengths to engage in ecological driving, making it computationally burdensome to execute at a time step fast enough to effectively enforce vehicle-following constraints. The work presented in this dissertation developed various CG-based vehicle-following strategies and tests their efficacy in highway driving simulations using real-world trucking routes and a proprietary heavy-duty truck model provided by Volvo Group North America. A CG-based ecological and adaptive cruise controller (Eco-ACC) is developed by cascading an MPC-based ecological cruise controller (ECC) with a CG, and simulation results indicate up to a 6% reduction in fuel consumption in comparison to a Gipps’ car-following model. A CG-based ACC is designed that ensures rear-end collision avoidance through the use of various lead vehicle prediction techniques, while improving drivability and ecological performance when compared to a traditional PID-based ACC. Finally, the inner-loop CG is formulated such that recursive feasibility is ensured through the utilization of a controlled invariant set, addressing an open challenge in the CG literature. © Copyright 2020 by Benjamin J. Groelke All Rights Reserved Inner-Loop Command Governors for Adaptive Cruise Control in Heavy-Duty Trucks by Benjamin J. Groelke A dissertation submitted to the Graduate Faculty of North Carolina State University in partial fulfillment of the requirements for the Degree of Doctor of Philosophy Mechanical Engineering Raleigh, North Carolina 2020