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Road Boundary Detection Using Ant Colony Optimization Algorithm

  • Tim Andersson
  • August Kihlberg
  • Anton Sundström
  • Ning XiongEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1074)

Abstract

A common problem for autonomous vehicles is to define a coherent round boundary of unstructured roads. To solve this problem an evolutionary approach has been evaluated, by using a modified ant optimization algorithm to define a coherent road edge along the unstructured road in night conditions. The work presented in this paper involved pre-processing, perfecting the edges in an autonomous fashion and developing an algorithm to find the best candidates of starting positions for the ant colonies. All together these efforts enable ant colony optimization (ACO) to perform successfully in this application scenario. The experiment results show that the best paths well followed the edges and that the mid-points between the paths stayed centered on the road.

Keywords

Ant colony optimization Lane detection Autonomous vehicles 

References

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    Pinninghoff, M.A., Contreras, R., Ortega, J.: Using ant colony optimization for edge detection in gray scale images (2015) Google Scholar
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    Bertozzi, M., Broggi, A., Fascioli, A., Tibaldi, A.: An evolutionary approach to lane markings detection in road environments (2002)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Tim Andersson
    • 1
  • August Kihlberg
    • 1
  • Anton Sundström
    • 1
  • Ning Xiong
    • 1
    Email author
  1. 1.Academy of Innovation, Design, and EngineeringMälardalen UniversityVästeråsSweden

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