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K-Optimal Chaos Ant Colony Algorithm and Its Application on Dynamic Route Guidance System

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Computer Engineering and Networking

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 277))

Abstract

Dynamic route guidance system is an important part of the intelligent transportation system; the core part of which is optimal path algorithm. This paper has analyzed the main influencing factors on the choice of optimal path, then provided an improved K-optimal chaos ant colony algorithm (K-CACA). The road impedance factor in K-CACA is based on the length, crowdedness, condition, and traffic load of the road sections. The optimizing procedure of the algorithm is speeded up by introducing the included angle threshold of direction. The chaos perturbation effectively refrains the algorithm from trapping into local optima. The results of simulation experiment show that K-CACA is effective and has much higher capacity of global optimization than Dijkstra algorithm and basic ant colony algorithm for optimal route choice.

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Acknowledgements

The research is supported by Chinese Natural Science Foundation (61103022) and Scientific Research Fund Project of Shandong Jiaotong University (Z201213).

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Authors and Affiliations

  1. College of Information Science and Electricity Engineering, Shandong Jiaotong University, Jinan, 250023, Shandong, China

    Hai Yang

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  1. Hai Yang
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Correspondence to Hai Yang .

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Editors and Affiliations

  1. University of Texas at Dallas, Richardson, Texas, USA

    W. Eric Wong

  2. Chinese Academy of Sciences, Beijing, China, People’s Republic

    Tingshao Zhu

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© 2014 Springer International Publishing Switzerland

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Yang, H. (2014). K-Optimal Chaos Ant Colony Algorithm and Its Application on Dynamic Route Guidance System. In: Wong, W.E., Zhu, T. (eds) Computer Engineering and Networking. Lecture Notes in Electrical Engineering, vol 277. Springer, Cham. https://doi.org/10.1007/978-3-319-01766-2_27

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  • DOI: https://doi.org/10.1007/978-3-319-01766-2_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01765-5

  • Online ISBN: 978-3-319-01766-2

  • eBook Packages: EngineeringEngineering (R0)

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