Citation
Fei Miao, Shuo Han, Shan Lin, George Pappas. "Robust Taxi Dispatch under Model Uncertainties". 54th Conference on Decision and Control (CDC), Osaka, IEEE, 15, December, 2015.

Abstract
In modern taxi networks, large amount of real-time taxi occupancy and location data are collected from networked in-vehicle sensors. They provide knowledge of system models on passenger demand and taxi supply for efficient dispatch control and coordinating strategies. Such dispatch approaches face a new challenge: how to deal with future customer demand uncertainties while fulfilling system's performance requirements, such as balancing service across the whole city and minimizing taxis' total idle cruising distance. To address this problem, we present a novel robust optimization method for taxis dispatch problems to consider polytope model uncertainties of highly spatiotemporally correlated demand and supply models. An objective function concave over the uncertain demand parameters and convex over the variables is formulated according to the design requirements. We transform the robust optimization problem to an equivalent convex optimization form by strong duality and minimax theorem, and computational tractability is guaranteed. By Monte-Carlo simulations, we show that the robust taxi dispatch solutions in this work are less probable to get large costs compared with non-robust results.

Electronic downloads

• https://www.src.org/library/publication/p086073/. (link to SRC site)
• http://dx.doi.org/10.1109/CDC.2015.7402643. (published version)

• HTML

  Fei Miao, Shuo Han, Shan Lin, George Pappas. <a
  href="http://www.terraswarm.org/pubs/661.html"
  >Robust Taxi Dispatch under Model
  Uncertainties</a>, 54th Conference on Decision and
  Control (CDC), Osaka, IEEE, 15, December, 2015.

• Plain text

  Fei Miao, Shuo Han, Shan Lin, George Pappas. "Robust
  Taxi Dispatch under Model Uncertainties". 54th
  Conference on Decision and Control (CDC), Osaka, IEEE, 15,
  December, 2015.

• BibTeX

  @inproceedings{MiaoHanLinPappas15_RobustTaxiDispatchUnderModelUncertainties,
      author = {Fei Miao and Shuo Han and Shan Lin and George
                Pappas},
      title = {Robust Taxi Dispatch under Model Uncertainties},
      booktitle = {54th Conference on Decision and Control (CDC),
                Osaka},
      organization = {IEEE},
      day = {15},
      month = {December},
      year = {2015},
      abstract = {In modern taxi networks, large amount of real-time
                taxi occupancy and location data are collected
                from networked in-vehicle sensors. They provide
                knowledge of system models on passenger demand and
                taxi supply for efficient dispatch control and
                coordinating strategies. Such dispatch approaches
                face a new challenge: how to deal with future
                customer demand uncertainties while fulfilling
                system's performance requirements, such as
                balancing service across the whole city and
                minimizing taxis' total idle cruising distance. To
                address this problem, we present a novel robust
                optimization method for taxis dispatch problems to
                consider polytope model uncertainties of highly
                spatiotemporally correlated demand and supply
                models. An objective function concave over the
                uncertain demand parameters and convex over the
                variables is formulated according to the design
                requirements. We transform the robust optimization
                problem to an equivalent convex optimization form
                by strong duality and minimax theorem, and
                computational tractability is guaranteed. By
                Monte-Carlo simulations, we show that the robust
                taxi dispatch solutions in this work are less
                probable to get large costs compared with
                non-robust results. },
      URL = {http://terraswarm.org/pubs/661.html}
  }
  

Posted by Fei Miao on 11 Oct 2015.
Groups: services