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55 will then be used to predict ride quality over measured track not used in the training. The neural network output will be compared to NUCARS simulation predictions and measured ride quality to determine the accuracy of the neural network predictions. If neural networks are determined to be a viable option for predicting ride quality, a different vehicle on a different transit system will be selected for additional investigation. Vehicle characterization and ride quality testing will be performed on the selected vehicle, and the data will be used to train and validate neural networks for the selected vehicle/system. ACKNOWLEDGMENT The authors thank DART for supporting the PBTG project, especially R.K. Rogers (assistant vice president, technical services), Michael Holbrook (senior manager, track & ROW), Darryl E. Spencer (director, fleet engineering), and Ron Foster (manager, rail fleet). TCRP D-7 panel members are Anthony Bohara, Steven Abramopaulos, Michael O. Brown, Michael K. Couse, James Dwyer, William H. Moorhead, Jeffrey G. Mora, James Nelson, Jerome M. Nery, Terrell Williams, Anne D. Aylward, Louis F. Sanders, Ann Purdue, and Stephan A. Parker (senior program officer). Dingqing Li is the TTCI TCRP program manager.
