Progress of Dynamic Path Optimization Strategies for Racing Cars Based on Machine Learning

Zihan An

2025

Abstract

Motor racing has always been a globally popular sport that pursues the ultimate and the extreme. Among them, the racing route is undoubtedly a very important aspect. This article will elaborate in detail on how to use machine learning technology to improve the research progress of future racing in dynamic optimization of routes. Next, computer dynamic vision algorithms such as You Only Look Once (YOLO) and Faster R-CNN will be introduced in detail. Meanwhile, the hardware that assists in obtaining information will also be introduced one by one. And combine this with the simulators commonly used by drivers to create the possibility of updated simulator driving, and at the same time, this can also be utilized to cultivate better training plans. At the same time, the challenges that this plan may face will also be taken into account. The first one is the lack of precise and large amounts of data. At the same time, the ethical decision-making of AI and its temporary response ability on the track also need to be considered.

Paper Citation

in Harvard Style

An Z. (2025). Progress of Dynamic Path Optimization Strategies for Racing Cars Based on Machine Learning. In Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI; ISBN 978-989-758-792-4, SciTePress, pages 545-550. DOI: 10.5220/0014362600004718

in Bibtex Style

@conference{emiti25,
author={Zihan An},
title={Progress of Dynamic Path Optimization Strategies for Racing Cars Based on Machine Learning},
booktitle={Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI},
year={2025},
pages={545-550},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014362600004718},
isbn={978-989-758-792-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence - Volume 1: EMITI
TI - Progress of Dynamic Path Optimization Strategies for Racing Cars Based on Machine Learning
SN - 978-989-758-792-4
AU - An Z.
PY - 2025
SP - 545
EP - 550
DO - 10.5220/0014362600004718
PB - SciTePress