Special Issue on Vehicle and Mobile Robot Technology (Part 1)

Recently, mobility technologies have undergone remarkable advances, with innovations such as autonomous driving and vehicle electrification, becoming increasingly integrated into society. The deployment of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications has accelerated the realization of connected cars, and the use of advanced driver assistance systems (ADAS) powered by artificial intelligence (AI) and machine learning continues to expand. Simultaneously, the emergence of mobility as a service (MaaS) and the introduction of smart infrastructure are becoming essential to ensure safe and efficient urban transportation. Collectively, these developments have reshaped the concept of mobility and driven the global transition toward autonomous driving. This special issue on “Vehicle and Mobile Robot Technology” is published in two issues (Vol.37 No.5 and No.6). The present issue corresponds to No.5 and features 20 selected papers. The accepted papers are categorized as follows: • Reinforcement learning and machine learning • Control theory and algorithms • Sensing, simulation, and system identification • Human–machine interface The papers in this issue are organized to present the most recent advances in reinforcement learning and machine learning for mobility systems, followed by significant contributions to control theory and algorithms. The subsequent sections introduce the progress in sensing, simulation, and system identification technologies, and the issue concludes with studies focusing on human–machine interfaces. These contributions encompass diverse application domains, including automobiles, ships, mobile robots, and heavy-duty vehicles, which are systematically arranged according to their technical approaches. We would like to express our gratitude to all the authors and reviewers and hope that this special issue will contribute to future research and development in vehicle and mobile robot technology.

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Institutions

Publication Details

Journal
Journal of Robotics and Mechatronics
Published
2025-10-19
DOI
https://doi.org/10.20965/jrm.2025.p1009
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
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article

Special Issue on Vehicle and Mobile Robot Technology (Part 1)

Kenji Sawada, Yuichiro SUEOKA, Hiroshi Okajima, Yuki Minami et al.
Journal of Robotics and Mechatronics
Robotic Path Planning Algorithms
article

Special Issue on Vehicle and Mobile Robot Technology (Part 1)

Kenji Sawada, Yuichiro SUEOKA, Hiroshi Okajima, Yuki Minami, Kazuma Sekiguchi
article en

Abstract

Recently, mobility technologies have undergone remarkable advances, with innovations such as autonomous driving and vehicle electrification, becoming increasingly integrated into society. The deployment of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications has accelerated the realization of connected cars, and the use of advanced driver assistance systems (ADAS) powered by artificial intelligence (AI) and machine learning continues to expand. Simultaneously, the emergence of mobility as a service (MaaS) and the introduction of smart infrastructure are becoming essential to ensure safe and efficient urban transportation. Collectively, these developments have reshaped the concept of mobility and driven the global transition toward autonomous driving. This special issue on “Vehicle and Mobile Robot Technology” is published in two issues (Vol.37 No.5 and No.6). The present issue corresponds to No.5 and features 20 selected papers. The accepted papers are categorized as follows: • Reinforcement learning and machine learning • Control theory and algorithms • Sensing, simulation, and system identification • Human–machine interface The papers in this issue are organized to present the most recent advances in reinforcement learning and machine learning for mobility systems, followed by significant contributions to control theory and algorithms. The subsequent sections introduce the progress in sensing, simulation, and system identification technologies, and the issue concludes with studies focusing on human–machine interfaces. These contributions encompass diverse application domains, including automobiles, ships, mobile robots, and heavy-duty vehicles, which are systematically arranged according to their technical approaches. We would like to express our gratitude to all the authors and reviewers and hope that this special issue will contribute to future research and development in vehicle and mobile robot technology.

Journal of Robotics and MechatronicsVol. 37(5)
University of Hyogo (JP), Tokyo City University (JP), Kumamoto University (JP), The University of Osaka (JP)
Openalex Percentile: Top 71%
Robotic Path Planning Algorithms
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