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Fuzzy truck control scheme for obstacle avoidance

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Abstract

The fuzzy system can be a good solution when a mathematical model of the system is either unavailable or too complex. Truck backer-upper control problem is one example of a standard highly nonlinear control problem. Bearing this in mind the control scheme that considers obstacles near the truck is much more complex than other conventional approaches. In this paper a fuzzy truck control system for obstacle avoidance, using newly designed 33 fuzzy inference rules for steering control and 13 rules for speed control, is proposed. Through simulations of various real world situations, we observed that the proposed fuzzy controller could drive the truck to the goal smoothly while avoiding the obstacles, and showed a reasonably good trajectory. This flexible and applicable fuzzy control logic can be adapted to provide easy interaction with the driver for state-of-the-art intelligent cruise control systems.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Pusan National University, Jangjeon-dong, Geumjeong-gu, Busan, 609-735, South Korea

    Do-Hyeon Kim & Eui-Young Cha

  2. Division of Computer and Information Engineering, Silla University, Gwaebop-dong, Sasang-gu, Busan, 617-736, South Korea

    Kwang-Baek Kim

Authors
  1. Do-Hyeon Kim
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  2. Kwang-Baek Kim
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  3. Eui-Young Cha
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Correspondence to Do-Hyeon Kim.

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Kim, DH., Kim, KB. & Cha, EY. Fuzzy truck control scheme for obstacle avoidance. Neural Comput & Applic 18, 801–811 (2009). https://doi.org/10.1007/s00521-008-0209-z

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  • DOI: https://doi.org/10.1007/s00521-008-0209-z

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