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Paper Abstract and Keywords
Presentation 2026-03-04 10:20
Design of a High-Reliability Spatial Information Sensing System through the Integration of Vehicle-to-Vehicle Sensing and Generative AI
Yuzuru Naito, Hideaki Miyaji, Hiroshi Yamamoto (Ritsumeikan Univ.) NS2025-229
Abstract (in Japanese) (See Japanese page) 
(in English) As expectations for the social implementation of autonomous driving technologies and autonomous mobile robots rise, ensuring safety and reliability in real-world environments has become an urgent challenge. Previous research has proposed systems that observe the surroundings of vehicles using sensors such as LiDAR and RGB cameras. However, LiDAR suffers from decreased recognition accuracy due to the multiple reflection of infrared light caused by water droplets during rain or fog, and RGB cameras are vulnerable to low-light conditions at night and to backlighting caused by sunlight. Thus, relying solely on a single fixed sensor makes it difficult to maintain accurate perception under changing environmental conditions. In this study, we propose a spatial information sensing system that adaptively selects appropriate sensing technologies for the surrounding environment, particularly in adverse weather, by sharing observations from multiple sensors via vehicle-to-vehicle (V2V) communication and estimating the reliability of each sensing technology using large language models (LLMs) that understand environmental states. The proposed system inputs environmental information—such as weather, time of day, and communication status inside and outside the vehicle—into the LLM, dynamically estimates the reliability of each sensing technology (such as LiDAR and RGB cameras) according to their environmental impact, and determines the method of fusing observation results based on those reliabilities. Through this system, we can expect highly accurate vehicle environment recognition even under conditions where the accuracy of LiDAR and RGB cameras decreases, by adaptively switching the sensor fusion strategy.
Keyword (in Japanese) (See Japanese page) 
(in English) autonomous driving / spatial information sensing / sensor fusion / vehicle-to-vehicle communication / generative AI / reliability estimation / UWB positioning /  
Reference Info. IEICE Tech. Rep., vol. 125, no. 385, NS2025-229, pp. 49-54, March 2026.
Paper # NS2025-229 
Date of Issue 2026-02-25 (NS) 
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 NS2025-229

Conference Information
Committee IN NS  
Conference Date 2026-03-04 - 2026-03-06 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa-Ken Shichoson Jichi Kaikan 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General 
Paper Information
Registration To NS 
Conference Code 2026-03-IN-NS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Design of a High-Reliability Spatial Information Sensing System through the Integration of Vehicle-to-Vehicle Sensing and Generative AI 
Sub Title (in English)  
Keyword(1) autonomous driving  
Keyword(2) spatial information sensing  
Keyword(3) sensor fusion  
Keyword(4) vehicle-to-vehicle communication  
Keyword(5) generative AI  
Keyword(6) reliability estimation  
Keyword(7) UWB positioning  
Keyword(8)  
1st Author's Name Yuzuru Naito  
1st Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
2nd Author's Name Hideaki Miyaji  
2nd Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
3rd Author's Name Hiroshi Yamamoto  
3rd Author's Affiliation Ritsumeikan University (Ritsumeikan Univ.)
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Speaker Author-1 
Date Time 2026-03-04 10:20:00 
Presentation Time 25 minutes 
Registration for NS 
Paper # NS2025-229 
Volume (vol) vol.125 
Number (no) no.385 
Page pp.49-54 
#Pages 6 
Date of Issue 2026-02-25 (NS) 

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