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Design of Genetic Algorithm-Based Parking System for an Autonomous Vehicle

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Book cover Control and Automation, and Energy System Engineering (CES3 2011, CA 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 256))

Abstract

A Genetic Algorithm (GA) is a kind of search techniques used to find exact or approximate solutions to optimization and searching problems. This paper discusses the design of a genetic algorithm-based intelligent parking system. This is a search strategy based on the model of evolution to solve the problem of parking systems. A genetic algorithm for an optimal solution is used to find a series of optimal angles of the moving vehicle at a parking space autonomously. This algorithm makes the planning simpler and the movement more effective. At last we present some simulation results.

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References

  1. Li, T.-H.S., Chang, S.-J.: Autonomous fuzzy parking control of a car-like mobile robot. In: Proc. IEEE Int. Conf. Systems, Man and Cybernetics, Part A, vol. Aut3, pp. 415–465 (2003)

    Google Scholar 

  2. Hao, Y.-H., Kim, T.-K., Choi, B.-J.: Design of fuzzy logic based parking systems for intelligent vehicles. J. of Korean Institute of Intelligent Systems 18, 1–6 (2008)

    Article  Google Scholar 

  3. Zhao, Y., Collins, E.-G., Dunlap, D.: Design of genetic fuzzy parallel parking control systems. In: Proc. The American Control Conference, Denver, pp. 4107–4112 (2003)

    Google Scholar 

  4. Bühler, O., Wegener, J.: Automatic testing of an autonomous parking system using evolutionary computation. SAE Int. (2004)

    Google Scholar 

  5. Zhang, H.-D., Dong, B.-H., Cen, Y.-W., Zheng, R.: Path planning algorithm for mobile robot based on path grids encoding novel mechanism. In: Int. Conference on Natural Computation, vol. 3 (2007)

    Google Scholar 

  6. Hu, X.-Z., Xie, C.-X.: Niche genetical agorithm for robot path planning. In: Int. Conference on Natural Computation, vol. 3 (2007)

    Google Scholar 

  7. Wan, T.-R., Chen, H., Earnshaw, R.: Real-time path planning for Navigation in unknown environment. In: Proc. Theory and Practice of Computer Graphics, vol. 3 (2003)

    Google Scholar 

  8. Geiger, B.-R., Horn, J.-F., Delullo, A.-M., Long, L.-N.: Optimal path planning of UAVs using direct collocation with nonlinear programming. In: AIAA GNC Conference, pp. 1–13 (2006)

    Google Scholar 

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Author information

Authors and Affiliations

  1. School of Electronic Engineering, Daegu University, Jillyang, Gyeongsan, Gyeongbuk, 712-714, Korea

    Xing Xiong & Byung-Jae Choi

Authors
  1. Xing Xiong
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  2. Byung-Jae Choi
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Editor information

Editors and Affiliations

  1. Multimedia Engineering Department, Hannam University, 133 Ojeong-dong, Daeduk-gu, Daejeon, Korea

    Tai-hoon Kim

  2. The Ohio State University, 470 Hitchcock Hall, 2070 Neil Avenue, OH 43210-1275, Columbus, USA

    Hojjat Adeli

  3. Jet Propulsion Laboratory/Caltech, NASA, 4800 Oak Grove Drive, 91109, Pasadena, CA, USA

    Adrian Stoica

  4. School of Computing and Information Systems, University of Tasmania, Hobart, TAS, Australia

    Byeong-Ho Kang

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© 2011 Springer-Verlag Berlin Heidelberg

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Xiong, X., Choi, BJ. (2011). Design of Genetic Algorithm-Based Parking System for an Autonomous Vehicle. In: Kim, Th., Adeli, H., Stoica, A., Kang, BH. (eds) Control and Automation, and Energy System Engineering. CES3 CA 2011 2011. Communications in Computer and Information Science, vol 256. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-26010-0_6

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  • DOI: https://doi.org/10.1007/978-3-642-26010-0_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-26009-4

  • Online ISBN: 978-3-642-26010-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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