Blocking Capacity and Level of Service in Railway Hump Classification Yards

UIUC Project Information


NuRail Project IDNURail2014-UIUC-R15
Project TitleBlocking Capacity and Level of Service in Railway Hump Classification Yards
UniversityUniversity of Illinois at Urbana-Champaign
Project ManagerTyler Dick
Principal InvestigatorTyler Dick
PI Contact Information
Funding Source(s) and Amounts Provided (by each agency or organization)$0 NURail, $100,000 cost share
Total Project Cost$
Agency ID or Contract NumberDTRT13-G-UTC52 (Grant 2)
Start Date2016-08-16
End Date2018-08-15
Location
Brief Description of Research ProjectThe objective of this research is to determine the fundamental hump classification yard capacity relationship between level of service and throughput volume of railcars as a function of the number of blocks assembled in the yard. In designing a train plan for a railway network, one decision is to determine the number of blocks to be handled by each train and the number of blocks to be assembled at each classification yard while maintaining a certain level of service. Increasing the number of blocks per train typically increases the number of blocks to be made at classification yards. A trade-off exists as terminal managers can more effectively operate their facilities by making fewer larger blocks. Meanwhile, the overall line-haul network operates better if each yard is handling a greater number of smaller blocks; increasing routing options and shortening connection times allows for optimized car trip plans. This research will investigate the terminal aspect of this trade-off by designing a factorial experiment to determine the relationship between yard throughput volume, the total number of blocks processed and the level of service. The number of inbound and outbound trains will be held constant, with the number of blocks per train varied accordingly. The experiments will be conducted with the Hump Yard Simulation System (HYSS) tool and six-week car files based on actual railroad operations. Following this initial analysis, the factorial experiment will be expanded to include other yard operational factors that may influence yard capacity. Later analysis of different rail yard facilities will examine the influence of train arrival rate, yard layout and overall yard configuration on the developed capacity relationship. It is anticipated that the cumulative results of this research will yield a basic parametric relationship for yard capacity. This relationship can be used by industry practitioners to develop more effective train plans, manage classification yard operations and plan investments in hump yard capacity.
Describe Implementation of Research Outcomes (or why not implemented)capacity relationships. The scope of later tasks may be refined as the results of earlier tasks reveal interesting relationships to be investigated further. All project tasks will be completed by a student Graduate Research Assistant.
Task 1: Academic HYSS Setup
Prior to beginning any simulation experiments, RailTEC must gain access to the HYSS model server and a working dataset for a given hump classification yard. RailTEC will then work with the Access database files to develop base case car files suitable for academic research. Although the dataset will retain its origin-destination and train assignment structure, traffic in each block will be manipulated to normalize the size of each block and reduce daily fluctuation in total traffic volume and number of cars per block. The inbound train arrivals in the car file will also be altered such that inbound trains consistently arrive according to the inbound train plan. These inbound sources of variation will be reintroduced in later experiments (Task 6).
Task 2: Basic Factorial Experiment
A factorial experiment will be designed to determine the relationship between yard throughput volume, the total number of blocks processed and the level of service. The number of inbound and outbound trains will be held constant, with the number of blocks per train varied accordingly. The task deliverable will be the general relationship between the two factors and the level of service response. Different blocking patterns and traffic volumes will be created in the Access car file and outbound train plan.
Task 3: Sensitivity of Volume-Blocks-Service Relationship to Number of Outbound Trains
In Task 3, the initial factorial experiment will be revisited but for a given volume, the number of blocks will be held constant and the number/length of outbound trains will be varied. This will vary the average number of blocks per outbound train.
Task 4: Sensitivity of Volume-Blocks-Service Relationship to Other Operational Factors
In Task 4, the factorial experiment will be expanded to include different levels of other yard operational factors which may influence the relationship between volume, the number of blocks and the level of service. Factors may include the number of train makeup rule exceptions in the facility, the hump rate, the percent of missed couplings, the number of trim/pull-out engines, the time required to perform inspections and other factors. A partial factorial experiment will be designed and simulated. The response surface will be used to conduct a sensitivity analysis to determine the factors having the greatest influence on the relationship and the level of service response.
Task 5: Influence of Infrastructure Layout and Blocks per Track
In Task 5, the influence of the yard infrastructure will be investigated by holding the number of blocks handled in the yard constant while varying the number of classification tracks. Similarly, the number of departure tracks will be varied for a constant number of blocks. In both cases, this will increase the number of blocks that must be formed on each track. Depending on the properties of the initial yard, the influence of specific crossovers or addition/subtraction of pull-out leads on the volume-blocks-service relationship may also be investigated.
Task 6: Influence of Variation in Daily Train Arrival Schedule and Volumes
The previous tasks will be completed for a base case with no daily variation in volume and train arrival times. In Task 6, daily variation in volume and train arrival times will be introduced to the base case according to the original distribution of daily traffic volume observed in the yard.
The deliverable for this project will be a final report documenting the above tasks. This research will also be incorporated into multiple chapters of the Principal Investigator’s dissertation.
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Final Report