Evaluating Fixed, Virtual, and Moving Block Control Systems on a Double Track North American Freight Rail Corridor

This paper evaluates the potential for virtual and moving block control systems to increase the capacity of existing North American freight rail corridors to meet future traffic demand. In 2019, US Class I railroads transported 1.6 billion tons of freight across their rail network. To create capacity for a projected increase in freight rail transportation demand of 24% by 2045, billions of dollars must be invested yearly in the mainline route network. As for-profit companies with limited capital budgets, US Class I railroads have a strong economic incentive to properly match mainline capacity to traffic demand. While investing in new track infrastructure does increase network capacity, recently installed Positive Train Control technology and its associated modern communications network may allow virtual and moving block systems to be developed as lower cost alternatives to manage projected traffic increases. Thus, the potential capacity and performance benefits of virtual and moving block systems relative to existing fixed block wayside signal systems should be quantified in a realistic mainline corridor operating scenario. The authors obtained actual route topology and historical train operating data for a longdistance (>2,000 km long) double-track US Class I railroad mainline and developed a novel dispatching algorithm and train simulation framework to compare average train speed under each control system and several levels of projected future train traffic. The simulation results indicate that virtual and moving block systems can substantially increase average train speed compared to existing fixed block systems, especially under high levels of train traffic. Alternatively, virtual and moving block systems can be used to preserve the existing average train speed while increasing the total number of trains handled. The quantitative results of these simulation experiments enable railway practitioners to more accurately evaluate the costs and benefits of investing in these emerging train traffic control technologies.