Faculty Profiles - OKUDA Hiroyuki

Papers - OKUDA Hiroyuki

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An occlusion- and interaction-aware safe control strategy for autonomous vehicles Reviewed International coauthorship

Siddharth Gangadhar, Zhuoyuan Wang, Kofi Poku, Yorie Nakahira, Naoya Yamada, Kohei Honda, Hiroyuki Okuda, Tatsuya Suzuki

22nd IFAC World Congress 2023(IFAC WC2023) page： 8577 - 8584 2023.7

MPC Builder for Autonomous Drive: Automatic Generation of MPCs for Motion Planning and Control Reviewed

2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV 2023.6

Pedestrian-aware Model Predictive Controller for Design of Considerate Autonomous Driving Reviewed

MURALEEDHARAN Arun, OKUDA Hiroyuki, SUZUKI Tatsuya

Transactions of the Society of Instrument and Control Engineers Vol. 59 ( 11 ) page： 472 - 483 2023

Authorship：Corresponding author Language：Japanese Publisher：The Society of Instrument and Control Engineers

<p>Driving in roads shared with pedestrians remains to be a challenging research problem in suburban/urban autonomous driving scenario. Interacting with pedestrians and making considerate decisions require high level decision making which is close to that of humans. This paper attempts to propose a multi-mode pedestrian model and a model predictive control (MPC) framework that uses the pedestrian model to predict the interactive behavior of the pedestrian. A probability weighted ARX (PrARX) model is used as the pedestrian model. This model can represent both decision making and motion of the pedestrian considering the interaction with ego car. The allowed risk levels of the controller is tunable to create a more personal driving behavior. The decision entropy of the pedestrian is also included as a cost factor in the MPC. This makes the pedestrian's decision making process easier and leads to realization of considerate driving. The validation of proposed model is performed based on the vehicle-crowd interaction (VCI) - CITR dataset and the performance of the controller is demonstrated in simulations using MATLAB.</p>

DOI： 10.9746/sicetr.59.472

CiNii Research

Configuration-aware model predictive motion planning for Tractor-Trailer Mobile Robot Reviewed

Ito Nobuaki, Okuda Hiroyuki, Suzuki Tatsuya

ADVANCED ROBOTICS 2022.9

Development and evaluation of driving speed controller for lane merging considering surrounding driver’s intention toward stress-free driving Reviewed

Vol. 14 ( 1 ) page： 128 - 139 2021.6

Quantitative Driver Acceptance Modeling for Merging Car at Highway Junction and its Application to the design of Merging Behavior Control Reviewed

Kota Harada, Hiroyuki Okuda, Tatsuya Suzuki, Shintaro Saigo, Satoshi Inoue

IEEE Transactions on Intelligent Transportation Systems Vol. 22 ( 1 ) page： 329 - 340 2021.1

Parking Trajectory Planning Using Multiresolution State Roadmaps Reviewed International journal

Yuichi Tazaki, Hiroyuki Okuda, Tatsuya Suzuki

IEEE Transactions on Intelligent Vehicles Vol. 2 ( 4 ) page： 298-307 2017.12

Modeling and Analysis of Driving Behavior based on Probability Weighted ARX Model Reviewed

Hiroyuki Okuda, Norimitsu Ikami, Tatsuya Suzuki, Yuichi Tazaki, Kazuya Takeda

IEEE Transactions on Intelligent Transportation Systems Vol. 14 ( 1 ) page： 98-112 2012.8

Analysis, Modeling, and Control of Merging Behavior at Low Speeds Reviewed International journal

Tatsuya Ishiguro, Hiroyuki Okuda, Kenta Tominaga, Tatsuya Suzuki

2025 IEEE/SICE International Symposium on System Integration, SII 2025 page： 782 - 788 2025.1

Language：English Publishing type：Research paper (international conference proceedings) Publisher：2025 IEEE/SICE International Symposium on System Integration, SII 2025

In a merging environment where automatic and manual operations are mixed, it is important for both parties to communicate with each other. While much research has been conducted at high speeds, such as on expressways, little progress has been made at low speeds, such as on ordinary roads. In this presentation, we will experimentally observe the driving characteristics of drivers in right-angle merging at low speeds, and construct a right-angle merging model that takes negotiation into account.

DOI： 10.1109/SII59315.2025.10871073

Scopus

Modeling of Cyclists' Decision for Left-Turn Vehicle at Unsignalized Intersection using Logistic Regression Model and Gaussian Mixuter Model Reviewed International journal

Ryo Wakisaka, Takuma Yamaguchi, Kazunori Ban, Hiroyuki Okuda, Tatsuya Suzuki

2025 IEEE/SICE International Symposium on System Integration, SII 2025 page： 789 - 796 2025.1

Inducibility Analysis of Pedestrian's Interactive Behavior Reviewed International journal

Kentaro Sugiura, Hiroyuki Okuda, Mizuho Aoki, Kazuma Uchida, Tatsuya Suzuki

2025 IEEE/SICE International Symposium on System Integration, SII 2025 page： 1 - 7 2025.1

Language：English Publishing type：Research paper (international conference proceedings) Publisher：2025 IEEE/SICE International Symposium on System Integration, SII 2025

As the application fields of Autonomous Mobile Robots (AMRs) expand, stress-free interaction with people around them becomes more important. AMRs are highly required to interact with pedestrians like human-human interaction. This paper proposes a new measure, 'Inducibility,' expressing how AMR's behavior can induce (control) the other pedestrian's behavior. In particular, this paper discusses two kinds of inducibility measures: one is based on the sensitivity of decision-making, and the other one is based on the controllability gramian for the state space model of the interactive behavior. Finally, the validity of these two measures is evaluated based on data on interaction behaviors, and typical applications of these measures are discussed.

DOI： 10.1109/SII59315.2025.10870962

Scopus

Switching Sampling Space of Model Predictive Path-Integral Controller to Balance Efficiency and Safety in 4WIDS Vehicle Navigation Reviewed

Mizuho Aoki, Kohei Honda, Hiroyuki Okuda, Tatsuya Suzuki

2024 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS2024), 2024.10

Comparative Study of Distributed Computation for Cooperative Adaptive Cruise Control using Model Prediction Reviewed

Hiroyuki Okuda, Toshiaki Hori, Hyuntai Chin, Tatsuya Suzuki

27th IEEE International Conference on Intelligent Transportation Systems (ITSC2024) 2024.9

Hierarchical Model of Pedestrians' Crossing Decision-making at Unsignalized Intersection Reviewed

NISHIMOTO Takashi, YAMAGUCHI Takuma, OKUDA Hiroyuki, SUZUKI Tatsuya, WAKISAKA Ryo, BAN Kazunori

Transactions of the Society of Instrument and Control Engineers Vol. 60 ( 9 ) page： 509 - 521 2024.9

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

<p>It is important to understand and predict the behavior of pedestrians, who are vulnerable road users, for the safe implementation of autonomous driving including on ordinary roads. Pedestrians make decisions and move considering other traffic participants, and decision-making models have been proposed to understand pedestrians' behavior. However, as the traffic situations become more complex, such as the number of vehicles, the models become more complicated and the scale of the models become larger, which makes modeling more difficult. To solve the problem, this paper models the crossing decisions of pedestrians using small-scale models by dividing the crossing decisions into decisions for each traffic participant. In the proposed model, crossing decisions of pedestrians are expressed by a Bayesian network, and the divided decisions for each traffic participant are modeled by logistic regression. Data of pedestrians' behavior were obtained using interactive multiplayer simulators, and then the proposed model was trained and validated. The accuracy of the proposed model was as good as that of the conventional model, which indicates the effectiveness of the proposed model. The proposed model succeeded in expressing crossing decisions of pedestrians in complex situations from small-scale models. Therefore, the flexibility of the model is increased in response to changes in the number of vehicles.</p>

DOI： 10.9746/sicetr.60.509

CiNii Research

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Operability evaluation of manual operation control for force-sensorless power-assist transport cart Reviewed International journal

Ryuki Sato, Ryuga Nishida, Susumu Hara, Hiroyuki Okuda, Mitsuru Nagatsuka, Masahiko Tsuji, Tatsuya Suzuki

Mechatronics Vol. 100 2024.6

Language：English Publishing type：Research paper (scientific journal) Publisher：Mechatronics

In large-scale factories and warehouses, power-assisted carts are effective in transporting cargo to reduce the burden on workers. Herein, we developed a force-sensorless power-assisted cart system that can detect the operating force applied by the operator without using a force sensor and control the power-assisted drive. In this system, the operator directly grasps and operates the body of the cart, and the applied force is estimated from the cart body sway caused by the operation. The transport cart is controlled based on the estimated hand force. In such closed-loop systems formed by humans and machines, mechanical interactions affect the operability of the equipment. In this study, we experimentally verified the power-assisted manual operability of the proposed force-sensorless power-assisted transport cart. We examined the accuracy of the path tracking in manual operation experiments with 20 subjects and analyzed the results of the subjective evaluation. Based on the experimental results, the influence of the control parameters on operability was considered, and design guidelines were presented.

DOI： 10.1016/j.mechatronics.2024.103189

Scopus

Stein Variational Guided Model Predictive Path Integral Control: Proposal and Experiments with Fast Maneuvering Vehicles Reviewed International journal

Kohei Honda, Naoki Akai, Kosuke Suzuki, Mizuho Aoki, Hirotaka Hosogaya, Hiroyuki Okuda, Tatsuya Suzuki

2024 IEEE International Conference on Robotics and Automation (ICRA) Vol. 29 page： 7020 - 7026 2024.5

Analysis and Modeling of Cyclists' Decision for Left-Turn Vehicle at Unsignalized Intersection Open Access

Wakisaka Ryo, Yamaguchi Takuma, Ban Kazunori, Okuda Hiroyuki, Suzuki Tatsuya

Transactions of Society of Automotive Engineers of Japan Vol. 55 ( 5 ) page： 991 - 998 2024.5

Language：Japanese Publishing type：Research paper (scientific journal) Publisher：Society of Automotive Engineers of Japan

In this paper, the cyclists' decision making behavior is measured and analyzed. The cyclists' decision state are considered to be expressed by operations of pedal and brake. In order to discriminate the pedaling state, a special force sensor was attached on the pedal of the cycling simulator. Then, the cyclists' decision making model was constructed by logistic regression model using the data measured by the cycling simulator. Finally, the accuracy of the model was analyzed and verified. It was found that the proposed model is useful for virtual simulation and/or design of autonomous vehicle, which need interactive behavior model of cyclists.

DOI： 10.11351/jsaeronbun.55.991

Open Access

CiNii Research

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Evaluation of Controllability of Interaction Between Pedestrian and Autonomous Mobile Robot in Shared Mobility Space Reviewed

Kentaro Sugiura, Mizuho Aoki, Kazuhide Kuroda, Hiroyuki Okuda, Tatsuya Suzuki

Proceedings of the International Conference on Informatics in Control, Automation and Robotics page： 249 - 257 2023.11

Bayesian Network Model of Decision-Making for Pedestrians' Crossing Behavior Considering Gaze Information at Unsignalized Intersection. Reviewed

Takashi Nishimoto, Takuma Yamaguchi, Hiroyuki Okuda, Tatsuya Suzuki 0001, Ryo Wakisaka, Kazunori Ban

25th IEEE International Conference on Intelligent Transportation Systems(ITSC) page： 4408 - 4415 2023.9

Bayesian Network-Based Probabilistic Constraints for Safe Autonomous Driving in Occlusion Environments Reviewed International coauthorship

Naoya Yamada, Kohei Honda, Hiroyuki Okuda, Tatsuya Suzuki, Yorie Nakahira

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC page： 3770 - 3777 2023.9

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Papers - OKUDA Hiroyuki