Faculty Profiles - OKUDA Hiroyuki

Papers - OKUDA Hiroyuki

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Indication of interaction plans based on model predictive interaction control: Cooperation between AMRs and pedestrians using eHMI

Suzuki Kosuke, Yamaguchi Takuma, Okuda Hiroyuki, Suzuki Tatsuya

2022 61ST ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS (SICE) page： 1232 - 1237 2022

Evaluation of impact by control switching according to driving environment

Oi Yusuke, Yamaguchi Takuma, Okuda Hiroyuki, Suzuki Tatsuya

2022 61ST ANNUAL CONFERENCE OF THE SOCIETY OF INSTRUMENT AND CONTROL ENGINEERS (SICE) page： 521 - 526 2022

Modeling Lane Keeping Behavior by Controller Model with Stochastic Parameters

TSUJI Yusuke, SUGAMOTO Shusaku, OKUDA Hiroyuki, YAMAGUCHI Takuma, SUZUKI Tatsuya

Transactions of the Society of Instrument and Control Engineers Vol. 58 ( 12 ) page： 581 - 590 2022

Language：Japanese Publishing type：Research paper (scientific journal) Publisher：The Society of Instrument and Control Engineers

<p>Recently, advanced driver assistance systems (ADAS), such as adaptive cruise control, lane keeping assistance and so on are widely spreading and these systems are improving comfortability and decreasing the number of accidents. The systems should be designed considering not only the usability but the acceptability from the driver because some drivers would switch it off if the system is not acceptable from the driver. Since the drivers' behavior is not simple but often varied even in a normal safety driving, there should be a kind of 'distribution' of the allowable driving behavior. This paper tries to construct the driver model which can simulate the variation in driving behavior in order to define distribution of the allowable driving behavior. Stochastic parameters and dead zones were used in the model structure taking into account the human nature. A method for evaluating the distribution of acceptable driving behavior is proposed, and parameter study is done based on the method.</p>

DOI： 10.9746/sicetr.58.581

CiNii Research

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Configuration-aware Model Predictive Motion Planning in Narrow Environment for Autonomous Tractor-trailer Vehicle Reviewed

Nobuaki Ito, Hiroyuki Okuda, Shinkichi Inagaki, Tatsuya Suzuki

Proceedings of 47th Annual Conference of the IEEE Industrial Electronics Society page： 1 - 6 2021.10

Variable Selection and Modeling of Drivers' Decision in Overtaking Behavior Based on Logistic Regression Model With Gazing Information Reviewed

Nwadiuto Jude C., Yoshino Soichi, Okuda Hiroyuki, Suzuki Tatsuya

IEEE ACCESS Vol. 9 page： 127672 - 127684 2021.9

受け入れられる運転知能を目指して―人の行動予測を用いた低ストレスな協調制御 Reviewed

奥田裕之・山口拓真

システム／制御／情報 Vol. 65 ( 9 ) page： 370 - 376 2021.9

Introduction of a Manual Control Mode for Autonomous Mobile Robots to Transportation of Equipment in Manufacturing Sites of Aircraft Industry

Gia Minh Thao Nguyen, Shoya Hirokawa, Susumu Hara, Hiroyuki Okuda, Mitsuru Nagatsuka, Naoki Ogawa, Tatsuya Suzuki

2021 IEEE International Conference on Advanced Robotics and its Social Impacts page： 127 - 130 2021.7

Driving Behavior Modeling Based on Consistent Variable Selection in a PWARX Model Reviewed

Nwadiuto Jude Chibuike, Okuda Hiroyuki, Suzuki Tatsuya

APPLIED SCIENCES-BASEL Vol. 11 ( 11 ) 2021.6

Realization and evaluation of an instructor-like assistance system for collision avoidance Reviewed

Keji Chen, Takuma Yamaguchi, Hiroyuki Okuda, Tatsuya Suzuki, Xuexun Guo

IEEE Transactions on Intelligent Transportation Systems Vol. 22 ( 5 ) page： 2751 - 2760 2021.5

Comparative Study of Prediction Models for Model Predictive Path-Tracking Control in Wide Driving Speed Range Reviewed

Mizuho Aoki, Kohei Honda, Hiroyuki Okuda, Tatsuya Suzuki

The IEEE Intelligent Vehicles Symposium page： 1261 - 1267 2021

Model Predictive Path Planning for Autonomous Parking Based on Projected C-Space Reviewed

Takuma Yamaguchi, Tatsuya Ishiguro, Hiroyuki Okuda, Tatsuya Suzuki

The IEEE Intelligent Transportation Systems Society Conference page： 929 - 935 2021

Design of Fail-safe Model Predictive Controller for Sudden Changes in Driving Scenes Reviewed

Bui Tu Ha, Arun Muraleedharan, Srishti Sinha, Hiroyuki Okuda, Tatsuya Suzuki

The IEEE Intelligent Transportation Systems Society Conference page： 790 - 797 2021

Configuration-aware Model Predictive Motion Planning in Narrow Environment for Autonomous Tractor-trailer Mobile Robot

Ito Nobuaki, Okuda Hiroyuki, Inagaki Shinkichi, Suzuki Tatsuya

IECON 2021 - 47TH ANNUAL CONFERENCE OF THE IEEE INDUSTRIAL ELECTRONICS SOCIETY 2021

「ヒトトツナガルセイギョシステムノミライオノゾク」トクシュウゴウ

奥田裕之, 山口拓真

システム・制御・情報 = Systems, control and information : システム制御情報学会誌 Vol. 65 ( 9 ) page： 370 - 376 2021

非線形モデル予測制御を用いたレーンチェンジにおける行動決定・経路計画・制御の同時実行 Reviewed

本田康平, 奥田裕之, 鈴木達也

自動車技術会論文集 Vol. 52 ( 1 ) page： 100 - 105 2020.12

Simultaneous Realization of Decision, Planning and Control for Lane-Changing Behavior Using Nonlinear Model Predictive Control

Okuda Hiroyuki, Sugie Nobuto, Suzuki Tatsuya, Haraguchi Kentaro, Kang Zibo

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS Vol. E103D ( 12 ) page： 2632 - 2642 2020.12

A hierarchical hybrid system of integrated longitudinal and lateral control for intelligent vehicles Reviewed

Chen, KJ; Pei, XF; Okuda, H; Zhu, ML; Guo, XX; Guo, KH; Suzuki, T

ISA TRANSACTIONS Vol. 106 page： 200 - 212 2020.11

Language：Japanese Publisher：ISA Transactions

A hierarchical hybrid control system is proposed to cope with highly automated driving in highway environments with multiple lanes and surrounding vehicles. In the high-level layer, the discrete driving decisions are coordinated by the finite-state machine (FSM) based on the relative position identification and predictive longitudinal distance of the surrounding vehicles. The low-level layer is responsible for the vehicle motion control, where the model predictive control (MPC) approach is utilized to integrate the longitudinal and lateral control mainly including car-following control and lane changing control. The proposed control system focuses on two issues regarding safe driving on highways. On one hand, the subject vehicle must always keep a safe distance with its leading vehicle to avoid the rear-end collision. On the other hand, the subject vehicle should also overtake the preceding vehicle by safe lane changes if the desired speed is not achieved. The effectiveness of the hybrid control is tested in the simulation, whose results verify that the driving decisions are made reasonably and the vehicle motion control obeys stability and comfort requirements. Moreover, it is also indicated by the simulations in random scenarios that the control strategy is able to deal with most of ordinary situations on highways although some emergency situations or critical driving maneuvers of other vehicles are not considered.

DOI： 10.1016/j.isatra.2020.07.009

Web of Science

Scopus

PubMed

Modeling Car-Following Behavior in Downtown Area based on Unsupervised Clustering and Variable Selection Method Reviewed

Duc-An Nguyen, Jude Nwadiuto, Hiroyuki Okuda, Tatsuya Suzuki

IEEE International Conference on Systems, Man, and Cybernetics 2020 (SMC2020) page： 1 - 6 2020.10

Drivers' driving style and their take-over-control judgment

Matsumuro Miki, Miwa Kazuhisa, Okuda Hiroyuki, Suzuki Tatsuya, Makiguchi Minoru

TRANSPORTATION RESEARCH PART F-TRAFFIC PSYCHOLOGY AND BEHAVIOUR Vol. 74 page： 237 - 247 2020.10

Model predictive driving for tractor-trailer mobile robot with an omni-directional tractor Reviewed

Nobuaki Ito, Hiroyuki Okuda, Tatsuya Suzuki,

2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE) page： 1530 - 1533 2020.9

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Papers - OKUDA Hiroyuki