SwePub - search: WFRF:(Caldas Kenny A. Q.)

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1.	Caldas, Kenny A. Q., et al. (author) Autonomous Driving of Trucks in Off-Road Environment 2023 In: JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS. - : Springer. - 2195-3880. ; 34:6, s. 1179-1193 Journal article (peer-reviewed)abstract Off-road driving operations can be a challenging environment for human conductors as they are subject to accidents, repetitive and tedious tasks, strong vibrations, which may affect their health in the long term. Therefore, they can benefit from a successful implementation of autonomous vehicle technology, improving safety, reducing labor costs and fuel consumption, and increasing operational efficiency. The main contribution of this paper is the experimental validation of a path tracking control strategy, composed of longitudinal and lateral controllers, on an off-road scenario with a fully loaded heavy-duty truck. The longitudinal control strategy relies on a nonlinear model predictive controller, which considers the path geometry and simplified vehicle dynamics to compute a smooth and comfortable input velocity, without violating the imposed constraints. The lateral controller is based on a robust linear quadratic regulator, which considers a vehicle model subject to parametric uncertainties to minimize its lateral displacement and heading error, as well as ensure stability. Experiments were carried out using a fully loaded vehicle on unpaved roads in an open-pit mine. The truck followed the reference path within the imposed constraints, showing robustness and driving smoothness.

Caldas, Kenny A. Q., et al. (author)
Autonomous Driving of Trucks in Off-Road Environment
2023
In: JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS. - : Springer. - 2195-3880. ; 34:6, s. 1179-1193
Journal article (peer-reviewed)abstract
- Off-road driving operations can be a challenging environment for human conductors as they are subject to accidents, repetitive and tedious tasks, strong vibrations, which may affect their health in the long term. Therefore, they can benefit from a successful implementation of autonomous vehicle technology, improving safety, reducing labor costs and fuel consumption, and increasing operational efficiency. The main contribution of this paper is the experimental validation of a path tracking control strategy, composed of longitudinal and lateral controllers, on an off-road scenario with a fully loaded heavy-duty truck. The longitudinal control strategy relies on a nonlinear model predictive controller, which considers the path geometry and simplified vehicle dynamics to compute a smooth and comfortable input velocity, without violating the imposed constraints. The lateral controller is based on a robust linear quadratic regulator, which considers a vehicle model subject to parametric uncertainties to minimize its lateral displacement and heading error, as well as ensure stability. Experiments were carried out using a fully loaded vehicle on unpaved roads in an open-pit mine. The truck followed the reference path within the imposed constraints, showing robustness and driving smoothness.

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