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First Place Solution in Fall 2025 Simulation Racing Series

Written by Mark Menaker on behalf of his team from University High School (Irvine).

GitHub: https://github.com/MightyMark3/ROAR_1_S25

Table of Contents

Introduction and History

The 1st Place Fall 2025 solution was based on our 2nd place Spring 2025 solution, since the winning solution from Summer 2025 never finished successfully on our computers. The 2nd place spring 2025 solution was largely based on the 1st place solution from Fall 2024 by BHS Racing.

This solution was slightly modified from their 1st place solution from Summer 2024, which our 2nd place solution from Fall 2024 was adapted from. Thus, our solution was nearly identical to our 2nd place solution from Fall 2024, with slight modifications that we will outline below.

Modifications from Spring 2025 2nd Place Solution

Our main adjustment to the solution was based on the racing technique of left-foot braking, when a driver uses both feet in order to slow down while still keeping the throttle open. While braking on the way into a turn, we did not reduce throttle to zero in order to improve response when exiting the turn. The amount of throttle provided while braking was adjusted based on the section of the track, the car’s current speed, and the duration of braking required.

It is interesting to note that the car in the simulation is a Tesla, which, unlike a combustion-engined car, should provide instantaneous throttle response that renders this solution ineffective. However, the simulation doesn’t simulate the car accurately (as shown by the fact that gear changes are possible), and thus, our method helped it accelerate more quickly out of the corners.

Conclusion

A big thank you to Dr. Allen Yang, Mr. Huo Chao Kuan, and your team of experts for all the effort put into running the competition! In the Autonomous Car Racing Club’s second year, I enjoyed the opportunity to promote ROAR in my school. Another big Thank You goes to Mr. Shulman, our supportive club advisor! Finally, I would like to thank my teammates: Aryan Mukherjee, Austin Shulman, and Reed Stibolt!

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