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Monitoring the Aerodynamic Efficiency of Intermodal Train Loading Using Machine Vision TRB 11-2236

By Tristan G. Rickett, John M. Hart, J. Riley Edwards, Avinash Kumar, Christopher P. L. Barkan, Narendra Ahuja, Tristan G. Rickett, John M. Hart, J. Riley Edwards, Avinash Kumar, Christopher P. L and Barkan Narendra Ahuja


Paper revised from original submittal. Rickett et al. 11-2236 1 Intermodal freight generates one of the highest sources of revenue among all traffic types transported by North American railroads. Intermodal trains, however, use equipment that is not aerodynamically efficient compared to other types of rolling stock, and typically operate at higher speeds, creating significant aerodynamic drag. This high resistance associated with the movement of intermodal trains results in significant annual operating expenses in the form of fuel expenditures. However, opportunities exist to reduce the aerodynamic drag through improved equipment design and loading practices. The University of Illinois at Urbana-Champaign is developing a machine vision system to evaluate intermodal train energy efficiency based on container and trailer loading arrangement, the gap lengths between them, and the type of rolling stock used. A prototype machine vision system has been installed at BNSF Railway’s Logistics Park Chicago facility to demonstrate the feasibility of the system. This machine vision system consists of a camera, computer, and machine vision algorithms. The algorithms separate the train from the background and detect the edges of the containers and trailers to identify an

Year: 2010
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