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Driver behavior modeling and its application to a guidance-as-needed steering system for individualized lane change assistance

Research Project

Project/Area Number 19K20318
Research Category

Grant-in-Aid for Early-Career Scientists

Allocation TypeMulti-year Fund
Review Section Basic Section 61020:Human interface and interaction-related
Research InstitutionThe University of Tokyo

Principal Investigator

Wang Zheng  東京大学, 生産技術研究所, 特任助教 (20837497)

Project Period (FY) 2019-04-01 – 2022-03-31
Project Status Completed (Fiscal Year 2021)
Budget Amount *help
¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2020: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2019: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
KeywordsShared control / Haptic interface / Driver behavior modeling / Driver monitoring system / Mobility system / Steering assist system / Human factors / Machine learning / Lane change assistance / Guidance-as-needed / haptic interface / driver behavior modeling / lane change assistance / shared control / guidance-as-needed
Outline of Research at the Start

The research focuses on modeling lane change behavior of individual driver and designing a guidance-as-needed steering system through haptic interface. The haptic interface provides haptic information in order to compensate for the limitation of driver visual information perception. Driving simulator and real-world experiments will be conducted to evaluate the effectiveness of the proposed system. The research will contribute to the improvement of driving safety and comfort, and to better understanding of driver behavior influenced by integrated visual and haptic information.

Outline of Final Research Achievements

This research focuses on modeling lane change behavior of individual drivers and designing a guidance-as-needed steering system through haptic interface. At the beginning of this project, a novel lane change model that takes account of driving styles was developed by analyzing driver behavior data collected from driving simulator experiments. After that, an intention-based haptic guidance steering system was designed by real-time measuring vehicle sensory data and driver gaze behavior, which shows its effectiveness for both lane keeping and lane changing tasks. Furthermore, an adaptive haptic guidance system by real-time monitoring driver arm muscle activity was designed and evaluated in lane change tasks. The driving simulator and real-vehicle experiment results show that, compared to a one-size-fits-all interface, the developed guidance-as-needed interface by taking account of individualized behavior is capable to improve driving safety and comfort as well as driver acceptance.

Academic Significance and Societal Importance of the Research Achievements

My research provides insights on understanding how driver interacts with haptic shared control system. Moreover, by designing a guidance-as-needed system, my research helps to raise people’s motivation and ability to move that would expand their life space by improving driving safety and comfort.

Report

(4 results)
  • 2021 Annual Research Report   Final Research Report ( PDF )
  • 2020 Research-status Report
  • 2019 Research-status Report
  • Research Products

    (14 results)

All 2022 2021 2020 2019

All Journal Article (10 results) (of which Int'l Joint Research: 4 results,  Peer Reviewed: 10 results,  Open Access: 3 results) Presentation (4 results) (of which Int'l Joint Research: 4 results)

  • [Journal Article] Modeling and analysis of driver behaviour under shared control through weighted visual and haptic guidance2022

    • Author(s)
      Wang Zheng、Zheng Rencheng、Nacpil Edric John Cruz、Nakano Kimihiko
    • Journal Title

      IET Intelligent Transport Systems

      Volume: 16 Issue: 5 Pages: 648-660

    • DOI

      10.1049/itr2.12163

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Analysis of visual risk perception model for braking control behaviour of human drivers: A literature review2022

    • Author(s)
      Liu Chao、Wang Zheng、Nacpil Edric John Cruz、Hou Wenbin、Zheng Rencheng
    • Journal Title

      IET Intelligent Transport Systems

      Volume: - Issue: 6 Pages: 1-14

    • DOI

      10.1049/itr2.12170

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Effect of Fixed and sEMG-Based Adaptive Shared Steering Control on Distracted Driver Behavior2021

    • Author(s)
      Wang Zheng、Suga Satoshi、Nacpil Edric John Cruz、Yang Bo、Nakano Kimihiko
    • Journal Title

      Sensors

      Volume: 21 Issue: 22 Pages: 7691-7691

    • DOI

      10.3390/s21227691

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Application of Physiological Sensors for Personalization in Semi-Autonomous Driving: A Review2021

    • Author(s)
      Nacpil Edric John Cruz、Wang Zheng、Nakano Kimihiko
    • Journal Title

      IEEE Sensors Journal

      Volume: 21 Issue: 18 Pages: 19662-19674

    • DOI

      10.1109/jsen.2021.3100038

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed
  • [Journal Article] A Classified Driver’s Lane-Change Decision- Making Model Based on Fuzzy Inference for Highly Automated Driving2021

    • Author(s)
      Guan Muhua、Wang Zheng、Yang Bo、Nakano Kimihiko
    • Journal Title

      IEEE International Conference on Human-Machine Systems

      Volume: - Pages: 1-4

    • DOI

      10.1109/ichms53169.2021.9582453

    • Related Report
      2021 Annual Research Report
    • Peer Reviewed
  • [Journal Article] Adaptive Driver-Automation Shared Steering Control via Forearm Surface Electromyography Measurement2021

    • Author(s)
      Wang Zheng、Suga Satoshi、Nacpil Edric John Cruz、Yan Zhanhong、Nakano Kimihiko
    • Journal Title

      IEEE Sensors Journal

      Volume: 21 Issue: 4 Pages: 5444-5453

    • DOI

      10.1109/jsen.2020.3035169

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Journal Article] Surface Electromyography-controlled Pedestrian Collision Avoidance: A Driving Simulator Study2021

    • Author(s)
      Nacpil Edric John Cruz、Wang Zheng、Yan Zhanhong、Kaizuka Tsutomu、Nakano Kimihiko
    • Journal Title

      IEEE Sensors Journal

      Volume: - Issue: 12 Pages: 1-1

    • DOI

      10.1109/jsen.2021.3070597

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Journal Article] Intention-Based Lane Changing and Lane Keeping Haptic Guidance Steering System2020

    • Author(s)
      Yan Zhanhong、Yang Kaiming、Wang Zheng、Yang Bo、Kaizuka Tsutomu、Nakano Kimihiko
    • Journal Title

      IEEE Transactions on Intelligent Vehicles

      Volume: - Issue: 4 Pages: 1-1

    • DOI

      10.1109/tiv.2020.3044180

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Journal Article] Learning Personalized Discretionary Lane-Change Initiation for Fully Autonomous Driving Based on Reinforcement Learning2020

    • Author(s)
      Liu Zhuoxi、Wang Zheng、Yang Bo、Nakano Kimihiko
    • Journal Title

      IEEE International Conference on Systems, Man and Cybernetics

      Volume: - Pages: 457-463

    • DOI

      10.1109/smc42975.2020.9283222

    • Related Report
      2020 Research-status Report
    • Peer Reviewed
  • [Journal Article] Comfort-oriented Haptic Guidance Steering via Deep Reinforcement Learning for Individualized Lane Keeping Assist2019

    • Author(s)
      Wang Zheng、Yan Zhanhong、Nakano Kimihiko
    • Journal Title

      IEEE International Conference on Systems, Man and Cybernetics

      Volume: - Pages: 4283-4289

    • DOI

      10.1109/smc.2019.8914219

    • Related Report
      2019 Research-status Report
    • Peer Reviewed / Int'l Joint Research
  • [Presentation] A Classified Driver’s Lane-Change Decision- Making Model Based on Fuzzy Inference for Highly Automated Driving2021

    • Author(s)
      Guan Muhua
    • Organizer
      IEEE International Conference on Human-Machine Systems
    • Related Report
      2021 Annual Research Report
    • Int'l Joint Research
  • [Presentation] Surface Electromyography-controlled Automotive Braking Assistance System Using Deep Learning Method2021

    • Author(s)
      Gia Quoc Bao Tran
    • Organizer
      12th International Conference on Applied Human Factors and Ergonomics (AHFE 2021)
    • Related Report
      2020 Research-status Report
    • Int'l Joint Research
  • [Presentation] Learning Personalized Discretionary Lane-Change Initiation for Fully Autonomous Driving Based on Reinforcement Learning2020

    • Author(s)
      Liu Zhuoxi
    • Organizer
      2020 IEEE International Conference on Systems, Man and Cybernetics (SMC 2020)
    • Related Report
      2020 Research-status Report
    • Int'l Joint Research
  • [Presentation] Comfort-oriented Haptic Guidance Steering via Deep Reinforcement Learning for Individualized Lane Keeping Assist2019

    • Author(s)
      Zheng Wang
    • Organizer
      2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
    • Related Report
      2019 Research-status Report
    • Int'l Joint Research

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Published: 2019-04-18   Modified: 2023-01-30  

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