Study on Motorcycle Rider Model Using Reinforcement Learning - Learning Examples Including Following Target Velocity and Basic Research on Rider Proficiency
<div class="section abstract"><div class="htmlview paragraph">In this study, an initial approach using deep reinforcement learning to replicate the complex behaviors of motorcycle riders was presented. Three learning examples were demonstrated: following a target velocity, maintaining stability at low speeds, and following a target trajectory. These examples serve as a starting point for further research. Additionally, the proficiency of the constructed models was examined using rider proficiency evaluation methods developed in previous studies. Initial results indicated that the models have the potential to mimic real rider behaviors; however, challenges such as differences between the model’s output and what humans can produce were also identified for future work.</div></div>
Authors
- Yasuhiro Mitsuhashi
- Noboru Yabe
- Y. Momiyama
Institutions
- Yamaha (Japan) (JP)
- Inova Design Solutions (United Kingdom) (GB)
Publication Details
- Journal
- SAE technical papers on CD-ROM/SAE technical paper series
- Published
- 2025-04-17
- DOI
- https://doi.org/10.4271/2024-32-0028
- Primary Topic
- Soil Mechanics and Vehicle Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.00