Project/Area Number |
19K20318
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Research Category |
Grant-in-Aid for Early-Career Scientists
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Allocation Type | Multi-year Fund |
Review Section |
Basic Section 61020:Human interface and interaction-related
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Research Institution | The 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)
|
Keywords | Shared 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.
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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.
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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.
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