Route Assignment for Autonomous Vehicles

  • Nick MoranEmail author
  • Jordan Pollack
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9882)


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.


Swarm intelligence Vehicle routing Autonomous vehicles Multi-agent systems Co-evolution Coordination games 


  1. 1.
    Traffic Assignment Manual. US Bureau of Public Roads (1964)Google Scholar
  2. 2.
    Beni, G., Wang, J.: Swarm intelligence in cellular robotic systems. In: Dario, P., Sandini, G., Aebischer, P. (eds.) Robots and Biological Systems: Towards a New Bionics? NATO ASI Series, vol. 102, pp. 703–712. Springer, Heidelberg (1993)Google Scholar
  3. 3.
    D’Acierno, L., Gallo, M., Montella, B.: An ant colony optimisation algorithm for solving the asymmetric traffic assignment problem. Eur. J. Oper. Res. 217(2), 459–469 (2012)MathSciNetCrossRefzbMATHGoogle Scholar
  4. 4.
    Dafermos, S., Sparrow, F.: The traffic assignment problem for a general network. J. Res. Natl. Bur. Stan. B 73, 91–118 (1969)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Dorigo, M.: Optimization, Learning and Natural Algorithms (in Italian). Ph.D. thesis, Dipartimento di Elettronica, Politecnico di Milano, Milan, Italy (1992)Google Scholar
  6. 6.
    Frank, M., Wolfe, P.: An algorithm for quadratic programming. Nav. Res. Logist. Q. 3, 95–110 (1956)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Fukushima, M.: A modified frank-wolfe algorithm for solving the traffic assignment problem. Transp. Res. Part B: Methodol. 18, 169–177 (1984)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Jeihani, M., Lawe, S., Connolly, J.: Improving traffic assignment model using intersection delay function. In: 47th Annual Transportation Research Forum, March 2006Google Scholar
  9. 9.
    Ji, Y., Geroliminis, N.: Modelling congestion propagation in urban transportation networks. In: Swiss Transport Research Conference (2012)Google Scholar
  10. 10.
    Larsson, T., Patriksson, M.: Simplicial decomposition with disaggregated representation for the traffic assignment problem. Transp. Sci. 26, 4–17 (1994)CrossRefzbMATHGoogle Scholar
  11. 11.
    Medina, J.S., Moreno, M.G., Royo, E.R.: Evolutionary computation applied to urban traffic optimization. In: Advances in Evolutionary Algorithms (2008)Google Scholar
  12. 12.
    Schweitzer, F., Ebeling, W., Rosé, H., Weiss, O.: Optimization of road networks using evolutionary strategies. Evol. Comput. 5(4), 419–438 (1997)CrossRefGoogle Scholar
  13. 13.
    Spiess, H.: Conical volume-delay functions. Transp. Sci. 24, 153–158 (1990)CrossRefGoogle Scholar
  14. 14.
    Teodorovic, D., Lucic, P.: Schedule synchronization in public transit by fuzzy ant system. Transp. Plan. Technol. 28, 47–76 (2005)CrossRefGoogle Scholar
  15. 15.
    Turky, A.M., Ahmad, M.S., Yusoff, M.Z.M., Sabar, N.R.: Genetic algorithm application for traffic light control. In: Yang, J., Ginige, A., Mayr, H.C., Kutsche, R.-D. (eds.) Information Systems: Modeling, Development, and Integration. LNBIP, vol. 20, pp. 115–120. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  16. 16.
    Wardrop, J.G.: Some theoretical aspects of road traffic research. Proc. ICE 1(3), 325–362 (1952)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Brandeis UniversityWalthamUSA

Personalised recommendations