Dynamic Scheduling of Trains in Densely Populated Congested Areas

This proposal addresses real-time dynamic dispatching of trains in complex, high-density heavy-haul railway networks consisting of multiple-track configurations, multiple priorities and multiple speed limits, which are commonly found in urban areas like Los Angeles County. The research will provide the theory and dynamic control algorithms for deadlock-free dispatching with minimal total train delay in high-density heavy-haul rail systems. In order to make optimal use of the capacity, rail networks in urban areas are extremely complicated, consisting of multiple trackage configurations of single, double, and, in high traffic zones, even triple-track. Another complicating factor of rail networks in urban areas is the existence of multiple speed limits at different points in the network because of physical contours, crossovers, or other safety considerations as opposed to travel in rural areas where a single speed limit may apply for long stretches of travel. Therefore, there is a need to develop theory and techniques to model and develop policies to streamline operations in these types of complicated rail networks. Determining the optimal dispatch policies that minimizes train delays and ensures deadlock-free operations is NP-hard. Therefore, most of the research efforts in this direction have focused on developing simple heuristics as well as detailed simulations to plan dispatching policies. Optimization efforts thus far have only addressed simple trackage configurations like single, double, and partially double rail lines. However complicating entities in a rail system like junctions, crossovers, sidings, speed limits and goods priorities need to be considered in order to extend the current theory and scheduling algorithms to large-scale urban rail networks. The current state-of-the art in scheduling these complicated networks includes only simple insertion type algorithms. To address this need, our proposed research will consist of the following tasks: (1) Development of a simulation model that can be implemented using commercially available simulation software. The current train simulation model used by the PI is based on old simulation software that is no longer supported and is outdated. (2) Development of real-time dynamic scheduling algorithms for complex general rail networks, commonly found in urban areas. The main impact of the proposed research will have a significant bearing on real-world urban rail operations, many of whose pertinent complexities have been ignored in theoretical studies thus far.


  • English


  • Status: Active
  • Contract Numbers:


  • Sponsor Organizations:

    National Center for Metropolitan Transportation Research

    University of Southern California
    650 Childs Way, RGL 107
    Los Angeles, CA  United States  90089-0626
  • Project Managers:

    Valentine, Victoria

  • Performing Organizations:

    University of Southern California, Los Angeles

    University Park Campus
    Los Angeles, CA  United States  90089
  • Principal Investigators:

    Dessouky, Maged

  • Start Date: 20090816
  • Expected Completion Date: 0
  • Actual Completion Date: 0
  • Source Data: RiP Project 26524

Subject/Index Terms

Filing Info

  • Accession Number: 01461406
  • Record Type: Research project
  • Source Agency: National Center for Metropolitan Transportation Research
  • Contract Numbers: 10-08
  • Files: UTC, RIP
  • Created Date: Jan 3 2013 1:45PM