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Route Assignment for Autonomous Vehicles

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Swarm Intelligence (ANTS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9882))

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Abstract

We demonstrate a self-organizing, multi-agent system to generate approximate solutions to the route assignment problem for a large number of vehicles across many origins and destinations. Our algorithm produces a set of mixed strategies over the set of paths through the network, which are suitable for use by autonomous vehicles in the absence of centralized control or coordination. Our approach combines ideas from co-evolutionary dynamics in which many species coordinate and compete for efficient navigation, and ideas from swarm intelligence in which many simple agents self-organize into successful behavior using limited inter-agent communication. Experiments demonstrate a marked improvement of both individual and total travel times as compared to greedy uncoordinated strategies, and we analyze the differences in outcomes for various routes as the simulation progresses.

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Author information

Authors and Affiliations

  1. Brandeis University, Waltham, MA, USA

    Nick Moran & Jordan Pollack

Authors
  1. Nick Moran
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  2. Jordan Pollack
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Corresponding author

Correspondence to Nick Moran .

Editor information

Editors and Affiliations

  1. Université Libre de Bruxelles , Bruxelles, Belgium

    Marco Dorigo

  2. Université Libre de Bruxelles , Bruxelles, Belgium

    Mauro Birattari

  3. RMIT University , Melbourne, Victoria, Australia

    Xiaodong Li

  4. University of Manchester, Manchester, United Kingdom

    Manuel López-Ibáñez

  5. Hiroshima University , Hiroshima, Japan

    Kazuhiro Ohkura

  6. École Polytechnique de Montréal , Montréal, Québec, Canada

    Carlo Pinciroli

  7. Université Libre de Bruxelles IRIDIA, CoDE, Brüssel, Belgium

    Thomas Stützle

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© 2016 Springer International Publishing Switzerland

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Moran, N., Pollack, J. (2016). Route Assignment for Autonomous Vehicles. In: Dorigo, M., et al. Swarm Intelligence. ANTS 2016. Lecture Notes in Computer Science(), vol 9882. Springer, Cham. https://doi.org/10.1007/978-3-319-44427-7_24

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  • DOI: https://doi.org/10.1007/978-3-319-44427-7_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44426-0

  • Online ISBN: 978-3-319-44427-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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