Basic study on path planning method utilizing iterative reversing maneuvers at narrow L-junctions

The purpose of this paper is to discuss a path planning method for navigating narrow L-junctions using iterative reversing maneuvers, as one of the technologies necessary for achieving full self-driving system. First, an analysis of the vehicle's behavior during repeated reversing maneuvers is conducted. Next, based on the analyzed characteristics, a strategy for navigating narrow L-junctions using reversing maneuvers is discussed. Following the proposed strategy, the necessary turning trajectories—constituting segments of the overall path—are formulated sequentially, and the complete path is derived geometrically. Furthermore, an algorithm for generating the entire path from the entrance to the exit is proposed by utilizing the formulated trajectories. The proposed algorithm is validated through numerical simulations. Path generation is performed under varying road width conditions, and it is confirmed that the paths are generated as intended. Additionally, path generation is conducted under a comprehensive range of road width conditions, and it is verified whether the path generation is successful or deemed infeasible. As a result, it is confirmed that the path generation method utilizing reversing maneuvers allows for a wider range of road width conditions to be successfully navigated compared to when reversing maneuvers are not used, indicating the effectiveness of the proposed method. However, after checking for interference with the road boundaries for all path generation results, it is found that in some conditions, the generated paths interfered with the road boundaries, indicating the need for further improvement.

Authors

Institutions

Publication Details

Journal
Mechanical Engineering Journal
Published
2025-01-01
DOI
https://doi.org/10.1299/mej.25-00058
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Basic study on path planning method utilizing iterative reversing maneuvers at narrow L-junctions

Ryuzo HAYASHI, Koki TAHIRA
Mechanical Engineering Journal
Robotic Path Planning Algorithms
article

Basic study on path planning method utilizing iterative reversing maneuvers at narrow L-junctions

Ryuzo HAYASHI, Koki TAHIRA
article en

Abstract

The purpose of this paper is to discuss a path planning method for navigating narrow L-junctions using iterative reversing maneuvers, as one of the technologies necessary for achieving full self-driving system. First, an analysis of the vehicle's behavior during repeated reversing maneuvers is conducted. Next, based on the analyzed characteristics, a strategy for navigating narrow L-junctions using reversing maneuvers is discussed. Following the proposed strategy, the necessary turning trajectories—constituting segments of the overall path—are formulated sequentially, and the complete path is derived geometrically. Furthermore, an algorithm for generating the entire path from the entrance to the exit is proposed by utilizing the formulated trajectories. The proposed algorithm is validated through numerical simulations. Path generation is performed under varying road width conditions, and it is confirmed that the paths are generated as intended. Additionally, path generation is conducted under a comprehensive range of road width conditions, and it is verified whether the path generation is successful or deemed infeasible. As a result, it is confirmed that the path generation method utilizing reversing maneuvers allows for a wider range of road width conditions to be successfully navigated compared to when reversing maneuvers are not used, indicating the effectiveness of the proposed method. However, after checking for interference with the road boundaries for all path generation results, it is found that in some conditions, the generated paths interfered with the road boundaries, indicating the need for further improvement.

Mechanical Engineering JournalVol. 12(4)
Tokyo University of Science (JP)
Japan Society for the Promotion of Science
Sustainable cities and communities
Openalex Percentile: Top 88%
Robotic Path Planning Algorithms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.