Swarm Optimization Algorithm for Road Bypass Extrapolation

  • Michael A. RowlandEmail author
  • Glenn M. Suir
  • Michael L. Mayo
  • Austin Davis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11844)


Ant Colony Optimization (ACO) algorithms work by leveraging a population of agents that communicate through interaction with deposited “pheromone,” and have been applied in various configurations to the long-standing problem of identifying trafficable terrain from aerial imagery. While these approaches have proven successful in highlighting paved roads in urban, highly-developed sites, they tend to fail in peri-urban and rural locations due to the lower frequency of unnatural features. In this work, we describe a workflow that uses site-specific, near-infrared and first-return LIDAR data to predict the “accessible space” of an image–i.e., the more open regions with shallow elevation gradient that may be readily traversible by both mounted (e.g., all-terrain vehicles) and dismounted forces. Collectively, these regions are supplied as input to an ACO algorithm, modified so that the agents perform a random walk weighted by local elevation change, which allows for a more comprehensive exploration of increasingly featureless imaged terrain. Performance of this workflow is evaluated using two study sites in the continental United States: the Muscatatuck Urban Training Center in rural Indiana, and Camp Shelby in Mississippi. Comparison of results with ground-truth datasets show a high degree of success in predicting areas trafficable by a wide variety of mobile units.


Image analysis Swarm optimization Trafficability 



Opinions, interpretations, conclusions, and recommendations are those of the author(s) and are not necessarily endorsed by the U.S. Army.


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Copyright information

© This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2019

Authors and Affiliations

  • Michael A. Rowland
    • 1
    Email author
  • Glenn M. Suir
    • 1
  • Michael L. Mayo
    • 1
  • Austin Davis
    • 1
  1. 1.U.S. Army Engineer Research and Development CenterVicksburgUSA

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