3.1a <p>Integrating Management of Truck and Rail Systems in Los Angeles</p>

Project Number


Project Summary

Integrating Management of Truck and Rail Systems in Los Angeles

Project Status




Topic Area

Sustainable Urban Freight

P.I. Name & Address

Professor, Daniel J. Epstein Department of Industrial and Systems Engineering; USC Viterbi School of Engineering
University of Southern California
3715 McClintock Ave.
Ethel Percy Andrus Gerontology Center (GER) 206A
Los Angeles, CA 90089-0193
United States

Railways, as one of the most cost-efficient ways to transport goods and people, serve a major part of the transportation demand, especially for freight transportation in the United States. According to an Association of American Railroads’ study, railway moves about 40% of freight measured in ton-miles, generating $71.6 billion of revenue in the United States in 2012. Based on the statistics given by the Federal Railroad Administration, the railway system will experience a 22% increase in the amount of tonnage from 2010 to 2035. However, it is very expensive to extend the current railway’s infrastructure. Therefore a better way of managing the railway system is needed.  One possible means to increase the efficiency of rail systems is through improved scheduling and dispatching.

New communication technologies have the potential to improve railway operations, especially through more efficient train scheduling and dispatching. Positive Train Control (PTC) is introduced as a system of monitoring and controlling the movement of trains to increase security by reducing human operation.  With PTC, trains can communicate with other trains to share information. Previously trains are ‘blind’ and controlled by the signals which are operated by experienced human dispatchers. With PTC, each train can have information of trains near it (‘locally’) and even trains far away from it (‘globally’).

In reality, trains are controlled by signals in order to avoid collision.  Hence, the track segment between two consecutive signals works as headway between two consecutive trains. Therefore the railway track is typically modeled as a set of blocks, where each block can hold only one train at any time. As a consequence, headway between two consecutive trains is represented as a block with fixed length in most of the simulation modelling approaches. The introduction of a PTC system enlarges the limited control given by the signals. The trains can be controlled to decelerate, accelerate and travel at a constant speed in real time at any point, resulting in dynamic headway between two consecutive trains. As a result existing simulation modelling approaches using fixed headways cannot be used to represent dynamic headway control.  Thus, we propose a new simulation model for a PTC system together with a dynamic headway control rule taking the train’s dynamics into consideration. 

Moreover, PTC technology provides finer monitoring and control over a train’s velocity. It leads to a better estimation of travel time over one segment. In contrast, most all of the previous research focuses on constant velocity when considering travel time over one segment. The introduction of a dynamic headway framework brings new problems that previous scheduling and routing models cannot deal with. One of the most challenging problems is routing trains with velocity control at each segment since the travel time over one segment is dependent on the entering velocity and exiting velocity. This type of velocity dependent routing is seldom considered in the previous research.  The ability to develop models to allow velocity control is especially important for rail operations in urban areas where there are multiple track segments which have varying speed limits and furthermore there are multiple train types using these segments that can travel at different speeds (e.g., freight and passenger trains travel at significantly different speeds).

The purpose of this research is to further the state-of-the-art of the train scheduling and routing problem taking into consideration the new capabilities that the newly introduced technologies such as PTC provide. Specifically, the contribution of this research is (1) we develop a simulation framework to represent dynamic headway, (2) given the headway distance and the speed limits, we develop an algorithm to determine the optimal velocities, and (3) using these models, estimate the additional amount of freight that the rail system can handle if dynamic headway control is used to control rail movement in Southern California.

To evaluate the proposed dynamic headway model and solution procedure, we conducted simulation experiments on an actual railway network. The chosen railway network is from Downtown Los Angeles to Pomona.   The railway trackage configuration in this area consists of single-, double- and triple- tracks with varying speed limits.  Also two types of trains (freight train and passenger train) are tested on this area.   The simulation analysis shows that with dynamic headway control the rail capacity could be increased by 20%, allowing for a significant amount of freight flow that could shift from truck to rail.  Also, the dynamic headway control also results in 40% less average delay at the rail network train count saturation point under constant headway control. 

Funding Source(s) and
Amounts Provided (by each agency or organization)

Volvo Research and Education Foundation


Total Project Cost


Agency ID or Contract Number


Start and End Dates

9/30/2013 to 9/30/2017

Describe Implementation of Research Outcomes (or why not implemented)


Impacts/Benefits of Implementation (actual, not anticipated)


Web Links, Reports, Project website