Evaluation of PTC Braking Enforcement Algorithms for Passenger and Commuter Trains
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2020-04-01
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Edition:Technical Report 8/26/2014-2/28/2019
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Abstract:Software algorithms used in Positive Train Control (PTC) systems designed to predict passenger train stopping distance and enforce a penalty brake application must be evaluated to verify their performance, which can be challenging due to variations in operational and equipment characteristics. The Federal Railroad Administration contracted Transportation Technology Center, Inc. to evaluate several PTC braking enforcement algorithms used in passenger and commuter train operations by implementing a previously established Monte Carlo simulation methodology supported by limited and focused field testing. Additionally, as PTC braking enforcement algorithms have been shown to be overly conservative, which can lead to operational inefficiencies by interfering with normal train operations, the project also included development of a framework to investigate approaches to improving these algorithms and reducing the associated operational inefficiencies, as was done with freight braking algorithms in previous projects. As part of this task, a baseline algorithm was developed, which can be altered to realize operational improvements while still maintaining safety standards in forthcoming projects.
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