Motion planning for intersection turning of heavy-duty autonomous vehicles using vehicle body trajectory prediction and risk potential evaluation

The shortage of drivers for trucks and buses has become a critical problem in recent years, leading to active research and development on unmanned and manpower-saving operation of heavy-duty vehicles. However, due to their larger overhangs compared to passenger cars, heavy-duty vehicles are more dif...

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Main Authors: Yutaka HAMAGUCHI, Yo SANOGAWA, Pongsathorn RAKSINCHAROENSAK
Format: Article
Language:Japanese
Published: The Japan Society of Mechanical Engineers 2023-10-01
Series:Nihon Kikai Gakkai ronbunshu
Subjects:
Online Access:https://www.jstage.jst.go.jp/article/transjsme/89/926/89_23-00139/_pdf/-char/en
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author Yutaka HAMAGUCHI
Yo SANOGAWA
Pongsathorn RAKSINCHAROENSAK
author_facet Yutaka HAMAGUCHI
Yo SANOGAWA
Pongsathorn RAKSINCHAROENSAK
author_sort Yutaka HAMAGUCHI
collection DOAJ
description The shortage of drivers for trucks and buses has become a critical problem in recent years, leading to active research and development on unmanned and manpower-saving operation of heavy-duty vehicles. However, due to their larger overhangs compared to passenger cars, heavy-duty vehicles are more difficult to maneuver on narrow roads and sharp curves, especially those commonly found in urban areas or parking lots. Consequently, path tracking control systems commonly applied to passenger cars cannot be directly used for heavy-duty vehicles. Thus, the objective of this study is to develop a path planning and motion control system for autonomous driving of heavy-duty vehicles on roads with large curvatures. To design the control system, a risk potential is utilized to express the driver's sense of danger towards obstacles and road boundaries. Simulations are conducted on a course that replicates an actual intersection, and a parameter study is carried out. Finally, the simulation results of this approach are compared with those of a conventional path-following method. The results demonstrate that the proposed method is effective for obstacle avoidance in intersection situations.
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spelling doaj.art-1ea28efbe6514e788d30ae0eedeb8db32023-10-26T04:51:05ZjpnThe Japan Society of Mechanical EngineersNihon Kikai Gakkai ronbunshu2187-97612023-10-018992623-0013923-0013910.1299/transjsme.23-00139transjsmeMotion planning for intersection turning of heavy-duty autonomous vehicles using vehicle body trajectory prediction and risk potential evaluationYutaka HAMAGUCHI0Yo SANOGAWA1Pongsathorn RAKSINCHAROENSAK2Hino Motors, Ltd.Department of Mechanical Systems Engineering, Tokyo University of Agriculture and TechnologyDepartment of Mechanical Systems Engineering, Tokyo University of Agriculture and TechnologyThe shortage of drivers for trucks and buses has become a critical problem in recent years, leading to active research and development on unmanned and manpower-saving operation of heavy-duty vehicles. However, due to their larger overhangs compared to passenger cars, heavy-duty vehicles are more difficult to maneuver on narrow roads and sharp curves, especially those commonly found in urban areas or parking lots. Consequently, path tracking control systems commonly applied to passenger cars cannot be directly used for heavy-duty vehicles. Thus, the objective of this study is to develop a path planning and motion control system for autonomous driving of heavy-duty vehicles on roads with large curvatures. To design the control system, a risk potential is utilized to express the driver's sense of danger towards obstacles and road boundaries. Simulations are conducted on a course that replicates an actual intersection, and a parameter study is carried out. Finally, the simulation results of this approach are compared with those of a conventional path-following method. The results demonstrate that the proposed method is effective for obstacle avoidance in intersection situations.https://www.jstage.jst.go.jp/article/transjsme/89/926/89_23-00139/_pdf/-char/enheavy-duty vehiclesautonomous drivingmotion planningintersectionrisk potential
spellingShingle Yutaka HAMAGUCHI
Yo SANOGAWA
Pongsathorn RAKSINCHAROENSAK
Motion planning for intersection turning of heavy-duty autonomous vehicles using vehicle body trajectory prediction and risk potential evaluation
Nihon Kikai Gakkai ronbunshu
heavy-duty vehicles
autonomous driving
motion planning
intersection
risk potential
title Motion planning for intersection turning of heavy-duty autonomous vehicles using vehicle body trajectory prediction and risk potential evaluation
title_full Motion planning for intersection turning of heavy-duty autonomous vehicles using vehicle body trajectory prediction and risk potential evaluation
title_fullStr Motion planning for intersection turning of heavy-duty autonomous vehicles using vehicle body trajectory prediction and risk potential evaluation
title_full_unstemmed Motion planning for intersection turning of heavy-duty autonomous vehicles using vehicle body trajectory prediction and risk potential evaluation
title_short Motion planning for intersection turning of heavy-duty autonomous vehicles using vehicle body trajectory prediction and risk potential evaluation
title_sort motion planning for intersection turning of heavy duty autonomous vehicles using vehicle body trajectory prediction and risk potential evaluation
topic heavy-duty vehicles
autonomous driving
motion planning
intersection
risk potential
url https://www.jstage.jst.go.jp/article/transjsme/89/926/89_23-00139/_pdf/-char/en
work_keys_str_mv AT yutakahamaguchi motionplanningforintersectionturningofheavydutyautonomousvehiclesusingvehiclebodytrajectorypredictionandriskpotentialevaluation
AT yosanogawa motionplanningforintersectionturningofheavydutyautonomousvehiclesusingvehiclebodytrajectorypredictionandriskpotentialevaluation
AT pongsathornraksincharoensak motionplanningforintersectionturningofheavydutyautonomousvehiclesusingvehiclebodytrajectorypredictionandriskpotentialevaluation