Automatic Route Design by Stepwise Subdivision of Virtual Walls —Reduces Route Length and Speeds Up Execution Time

With the development of autonomous driving technology utilizing machine learning, AI, and sensors, research on autonomous driving control has become more active, and a large number of innovative studies are underway. In the near future, all autonomous vehicle fleets will be able to communicate with...

Full description

Saved in:
Bibliographic Details
Published in:Journal of robotics and mechatronics 2024-06, Vol.36 (3), p.628-641
Main Authors: Itoh, Yuki, Hoshino, Junya, Suzuki, Tenta, Matsuda, Kenji, Kumagae, Kaito, Tobisawa, Mao, Harada, Tomohiro, Matsuoka, Jyouhei, Kagawa, Toshinori, Hattori, Kiyohiko
Format: Article
Language:English
Subjects:
Active control
Control methods
Machine learning
Route selection
Traffic control
Traffic intersections
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:With the development of autonomous driving technology utilizing machine learning, AI, and sensors, research on autonomous driving control has become more active, and a large number of innovative studies are underway. In the near future, all autonomous vehicle fleets will be able to communicate with each other for sharing information and overall optimal traffic control will be achieved. One of the vehicle control systems that are based on the premise of such a fully automated society is the “signal-less intersection.” There is an intersection traffic control method that achieves safe and rational route selection by using virtual walls (VWs), which are virtual obstacles, but there are issues in terms of total route length and reduction of computation time. To address the issues, we propose a method that (1) prunes unneeded paths and (2) arranges VWs in a stepwise manner. The effectiveness of the proposed method was evaluated by simulation, and the results showed that the total route length and execution time were reduced.
ISSN:0915-3942
1883-8049
DOI:10.20965/jrm.2024.p0628