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Main Authors: Fieni, Giona, Neumann, Marc-Philippe, Zanardi, Alessandro, Cerofolini, Alberto, Onder, Christopher H.
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2405.11032
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author Fieni, Giona
Neumann, Marc-Philippe
Zanardi, Alessandro
Cerofolini, Alberto
Onder, Christopher H.
author_facet Fieni, Giona
Neumann, Marc-Philippe
Zanardi, Alessandro
Cerofolini, Alberto
Onder, Christopher H.
contents This paper presents an interaction-aware energy management optimization framework for Formula 1 racing. The considered scenario involves two agents and a drag reduction model. Strategic interactions between the agents are captured by a Stackelberg game formulated as a bilevel program. To address the computational challenges associated with bilevel optimization, the problem is reformulated as a single-level nonlinear program employing the Karush-Kuhn-Tucker conditions. The proposed framework contributes towards the development of new energy management and allocation strategies, caused by the presence of another agent. For instance, it provides valuable insights on how to redistribute the energy in order to optimally exploit the wake effect, showcasing a notable difference with the behavior studied in previous works. Robust energy allocations can be identified to reduce the lap time loss associated with unexpected choices of the other agent. It allows to recognize the boundary conditions for the interaction to become relevant, impacting the system's behavior, and to assess if overtaking is possible and beneficial. Overall, the framework provides a comprehensive approach for a two-agent Formula 1 racing problem with strategic interactions, offering physically intuitive and practical results.
format Preprint
id arxiv_https___arxiv_org_abs_2405_11032
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Game-theoretic Energy Management Strategies With Interacting Agents in Formula 1
Fieni, Giona
Neumann, Marc-Philippe
Zanardi, Alessandro
Cerofolini, Alberto
Onder, Christopher H.
Systems and Control
This paper presents an interaction-aware energy management optimization framework for Formula 1 racing. The considered scenario involves two agents and a drag reduction model. Strategic interactions between the agents are captured by a Stackelberg game formulated as a bilevel program. To address the computational challenges associated with bilevel optimization, the problem is reformulated as a single-level nonlinear program employing the Karush-Kuhn-Tucker conditions. The proposed framework contributes towards the development of new energy management and allocation strategies, caused by the presence of another agent. For instance, it provides valuable insights on how to redistribute the energy in order to optimally exploit the wake effect, showcasing a notable difference with the behavior studied in previous works. Robust energy allocations can be identified to reduce the lap time loss associated with unexpected choices of the other agent. It allows to recognize the boundary conditions for the interaction to become relevant, impacting the system's behavior, and to assess if overtaking is possible and beneficial. Overall, the framework provides a comprehensive approach for a two-agent Formula 1 racing problem with strategic interactions, offering physically intuitive and practical results.
title Game-theoretic Energy Management Strategies With Interacting Agents in Formula 1
topic Systems and Control
url https://arxiv.org/abs/2405.11032