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| Paper Abstract and Keywords | ||
| Presentation | 2019-09-24 15:50 Reinforcement learning for pedestrian agent route planning and collision avoidance Trinh Thanh Trung, Masaomi Kimura (SIT)  SSS2019-21 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Pedestrian navigation plays a significant role in many traffic safety simulation systems. In microscopic pedestrian navigation, most models use the concept of “forces” applied to the pedestrian agents to replicate the navigation environment. While the approach could provide believable results in regular situations, it does not always resemble natural pedestrian navigation behaviour in many typical settings. In our research, we proposed a novel approach using reinforcement learning for simulation of pedestrian agent route planning and collision avoidance problem. The primary focus of this approach is using human perception of the environment and danger awareness of interferences. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | pedestrian / reinforcement learning / PPO / navigation / route planning / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 210, SSS2019-21, pp. 17-22, Sept. 2019. | |
| Paper # | SSS2019-21 | |
| Date of Issue | 2019-09-17 (SSS) | |
| ISSN | Print edition: ISSN 0913-5685 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 | SSS2019-21 |
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| Conference Information | |
| Committee | SSS |
| Conference Date | 2019-09-24 - 2019-09-24 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SSS |
| Conference Code | 2019-09-SSS |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Reinforcement learning for pedestrian agent route planning and collision avoidance |
| Sub Title (in English) | |
| Keyword(1) | pedestrian |
| Keyword(2) | reinforcement learning |
| Keyword(3) | PPO |
| Keyword(4) | navigation |
| Keyword(5) | route planning |
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| 1st Author's Name | Trinh Thanh Trung |
| 1st Author's Affiliation | Shibaura Institute of Technology (SIT) |
| 2nd Author's Name | Masaomi Kimura |
| 2nd Author's Affiliation | Shibaura Institute of Technology (SIT) |
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| Speaker | Author-1 |
| Date Time | 2019-09-24 15:50:00 |
| Presentation Time | 35 minutes |
| Registration for | SSS |
| Paper # | SSS2019-21 |
| Volume (vol) | vol.119 |
| Number (no) | no.210 |
| Page | pp.17-22 |
| #Pages | 6 |
| Date of Issue | 2019-09-17 (SSS) |
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