| Paper Abstract and Keywords |
| Presentation |
2025-08-29 09:25
A Hybrid Reinforcement Learning Framework for Cooperative Driving: From Algorithm Design to Real-World Validation Yu Taoyuan, Wang Kui, Li Zongdian, Yu Tao, Kei Sakaguchi (Institute of Science Tokyo) RCS2025-114 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Unsignalized intersections face significant challenges in safety and efficiency due to complex traffic dynamics. This paper proposes an RSU-centric cooperative driving framework that leverages global perception and vehicle-to-infrastructure communication. The framework employs a two-stage hybrid reinforcement learning method, combining offline pre-training with online fine-tuning, and incorporates the multi-attention mechanism to address inter-agent dependencies. Extensive experiments show that the proposed method achieves a failure rate below 0.03% when controlling three connected autonomous vehicles. Moreover, it exhibits strong robustness to different numbers of agents and generalizes well to other traffic maps. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Cooperative driving / reinforcement learning / V2I / CAVs / RSUs / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 125, no. 163, RCS2025-114, pp. 81-86, Aug. 2025. |
| Paper # |
RCS2025-114 |
| Date of Issue |
2025-08-21 (RCS) |
| ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
| Download PDF |
RCS2025-114 |
| Conference Information |
| Committee |
RCS SAT |
| Conference Date |
2025-08-28 - 2025-08-29 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Toki Messe |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Satellite Communications, Broadcasting, Forward Error Correction, Wireless Communications, etc. |
| Paper Information |
| Registration To |
RCS |
| Conference Code |
2025-08-RCS-SAT |
| Language |
English |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
A Hybrid Reinforcement Learning Framework for Cooperative Driving: From Algorithm Design to Real-World Validation |
| Sub Title (in English) |
|
| Keyword(1) |
Cooperative driving |
| Keyword(2) |
reinforcement learning |
| Keyword(3) |
V2I |
| Keyword(4) |
CAVs |
| Keyword(5) |
RSUs |
| Keyword(6) |
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| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Yu Taoyuan |
| 1st Author's Affiliation |
Institute of Science Tokyo (Institute of Science Tokyo) |
| 2nd Author's Name |
Wang Kui |
| 2nd Author's Affiliation |
Institute of Science Tokyo (Institute of Science Tokyo) |
| 3rd Author's Name |
Li Zongdian |
| 3rd Author's Affiliation |
Institute of Science Tokyo (Institute of Science Tokyo) |
| 4th Author's Name |
Yu Tao |
| 4th Author's Affiliation |
Institute of Science Tokyo (Institute of Science Tokyo) |
| 5th Author's Name |
Kei Sakaguchi |
| 5th Author's Affiliation |
Institute of Science Tokyo (Institute of Science Tokyo) |
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| Speaker |
Author-1 |
| Date Time |
2025-08-29 09:25:00 |
| Presentation Time |
25 minutes |
| Registration for |
RCS |
| Paper # |
RCS2025-114 |
| Volume (vol) |
vol.125 |
| Number (no) |
no.163 |
| Page |
pp.81-86 |
| #Pages |
6 |
| Date of Issue |
2025-08-21 (RCS) |