• DocumentCode
    183745
  • Title

    Vehicle routing algorithms to intercept escaping targets

  • Author

    Agharkar, Pushkarini ; Bullo, Francesco

  • Author_Institution
    Dept. of Mech. Eng., Univ. of California Santa Barbara, Santa Barbara, CA, USA
  • fYear
    2014
  • fDate
    4-6 June 2014
  • Firstpage
    952
  • Lastpage
    957
  • Abstract
    We study a dynamic vehicle routing problem for moving targets. Our setup is as follows: (i) targets appear uniformly distributed on a unit disk via a temporal Poisson process and move radially outward with a constant speed v, (ii) a single vehicle with speed greater than that of the targets aims to intercepts them before they escape the disk. With the goal of maximizing the fraction of captured targets in the steady state, we propose three policies: Capturable Nearest Neighbor (CNN), Sector Wise (SW) and Stay Near Boundary (SNB) policy. We derive lower bounds on the fraction of targets captured by the CNN, SW and SNB policies. The CNN policy is shown to be optimal for arrival rate λ below a critical value. For arrival rates above another critical value, the fraction of targets captured by the SW policy is more than that of the CNN policy. Finally, the SNB policy is within a constant factor of optimal in the limiting regime of ν → 0+ and λ → +∞. We present numerical simulations to illustrate our results.
  • Keywords
    optimisation; path planning; stochastic processes; vehicle routing; CNN policy; SNB policy; SW policy; capturable nearest neighbor policy; dynamic vehicle routing problem; escaping target interception; fraction maximization; numerical simulations; sector wise policy; stay near boundary policy; temporal Poisson process; unit disk; vehicle motion planning; Numerical simulation; Optimization; Probability density function; Steady-state; Upper bound; Vehicle routing; Vehicles; Agents-based systems; Stochastic systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    American Control Conference (ACC), 2014
  • Conference_Location
    Portland, OR
  • ISSN
    0743-1619
  • Print_ISBN
    978-1-4799-3272-6
  • Type

    conf

  • DOI
    10.1109/ACC.2014.6858759
  • Filename
    6858759