Optimizing Energy-Efficient Braking Trajectories with Anticipatory Road Data for Automated Vehicles

Fuente: arXiv
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Autores principales: Prado, Andres Alvarez, Nenchev, Vladislav, Rathgeber, Christian
Formato: Preprint
Publicado: 2024
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author Prado, Andres Alvarez
Nenchev, Vladislav
Rathgeber, Christian
author_facet Prado, Andres Alvarez
Nenchev, Vladislav
Rathgeber, Christian
contents Trajectory planning in automated driving typically focuses on satisfying safety and comfort requirements within the vehicle's onboard sensor range. This paper introduces a method that leverages anticipatory road data, such as speed limits, road slopes, and traffic lights, beyond the local perception range to optimize energy-efficient braking trajectories. For that, coasting, which reduces energy consumption, and active braking are combined to transition from the current vehicle velocity to a lower target velocity at a given distance ahead. Finding the switching instants between the coasting phases and the continuous control for the braking phase is addressed as an optimal trade-off between maximizing coasting periods and minimizing braking effort. The resulting switched optimal control problem is solved by deriving necessary optimality conditions. To facilitate the incorporation of additional feasibility constraints for multi-phase trajectories, a sub-optimal alternative solution based on parametric optimization is proposed. Both methods are compared in simulation.
format Preprint
id arxiv_https___arxiv_org_abs_2406_17604
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimizing Energy-Efficient Braking Trajectories with Anticipatory Road Data for Automated Vehicles
Prado, Andres Alvarez
Nenchev, Vladislav
Rathgeber, Christian
Systems and Control
Robotics
Trajectory planning in automated driving typically focuses on satisfying safety and comfort requirements within the vehicle's onboard sensor range. This paper introduces a method that leverages anticipatory road data, such as speed limits, road slopes, and traffic lights, beyond the local perception range to optimize energy-efficient braking trajectories. For that, coasting, which reduces energy consumption, and active braking are combined to transition from the current vehicle velocity to a lower target velocity at a given distance ahead. Finding the switching instants between the coasting phases and the continuous control for the braking phase is addressed as an optimal trade-off between maximizing coasting periods and minimizing braking effort. The resulting switched optimal control problem is solved by deriving necessary optimality conditions. To facilitate the incorporation of additional feasibility constraints for multi-phase trajectories, a sub-optimal alternative solution based on parametric optimization is proposed. Both methods are compared in simulation.
title Optimizing Energy-Efficient Braking Trajectories with Anticipatory Road Data for Automated Vehicles
topic Systems and Control
Robotics
url https://arxiv.org/abs/2406.17604