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Evaluation of Fuzzy Inference-based Self-tuning of Steering Control Gains for Heavy-duty Trucks

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Abstract

As the number of automobiles in worldwide increases, the number of associated serious environmental and safety problems also increases. A solution to these problems is an autonomous platooning system for trucks, which is expected to have various effects such as reduction in carbon dioxide emissions and increase in traffic capacity. Although various control laws have been proposed for automated driving, control gains are typically tuned manually. The optimal values change owing to the freight or over a period of several years. Therefore, when the control performance decreases, gain tuning is again required. In this study, as additional evaluations of the proposed self-tuning method, we newly examine if the method can adjust gain to the change of a freight weight by simulation and evaluate the convergence property of the method experimentally.

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Acknowledgments

The New Energy and Industrial Technology Development Organization (NEDO) supported this study.

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Authors and Affiliations

  1. Kobe University, 1-1 Rokkodai, Nada-ku, Kobe, Hyogo, Japan

    Takuma Ario

  2. Tokyo University, 4-6-1, Komaba, Meguro-ku, Tokyo, Japan

    Toshiyuki Sugimachi

  3. Kobe University, 1-1 Rokkodai, Nada-ku, Kobe, Hyogo, Japan

    Takanori Fukao

  4. Japan Automobile Research Institute, 2530 Karima, Tsukuba, Ibaraki, Japan

    Hiroki Kawashima

Authors
  1. Takuma Ario
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  2. Toshiyuki Sugimachi
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  3. Takanori Fukao
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  4. Hiroki Kawashima
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Corresponding authors

Correspondence to Takuma Ario, Toshiyuki Sugimachi, Takanori Fukao or Hiroki Kawashima.

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Ario, T., Sugimachi, T., Fukao, T. et al. Evaluation of Fuzzy Inference-based Self-tuning of Steering Control Gains for Heavy-duty Trucks. Int. J. ITS Res. 14, 92–100 (2016). https://doi.org/10.1007/s13177-014-0105-0

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  • DOI: https://doi.org/10.1007/s13177-014-0105-0

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