Intermodal (IM) trains are typically the fastest freight trains operated in North America. The aerodynamic characteristics of many of these trains are often relatively poor resulting in high fuel consumption. However, considerable variation in fuel efficiency is possible depending on how the loads are placed on railcars in the train. Consequently, substantial potential fuel savings are possible if more attention is paid to the loading configuration of trains. A wayside machine vision (MV ) system was developed to automatically scan passing IM trains and assess their aerodynamic efficiency. MV algorithms are used to analyse these images, detect and measure gaps between loads. In order to make use of the data, a scoring system was devel-oped based on two attributes – the aerodynamic coefficient and slot efficiency. The aerodynamic coefficient is calculated using the Aerodynamic Subroutine of the train energy model. Slot effi-ciency represents the difference between the actual and ideal loading configuration given the particular set of railcars in the train. This system can provide IM terminal managers feedback on loading performance for trains and be integrated into the software support systems used for loading assignment.

• A. Kumar, J. M. Hart, and N. Ahuja, Motion-Based Background Subtraction and Panoramic Mosaicing for Freight Train Analysis, Proceedings of the IEEE International Conference on Image Processing, Melbourne, Australia, Sept. 18, 2013.
• Tristan G. Rickett, Avinash Kumar, John M. Hart, J. Riley Edwards, C. P. L. Barkan and Narendra Ahuja, Machine Vision Analysis of Intermodal Loading Efficiency on Heavy-Haul Railroads [ppt], Proceedings of International Heavy Haul Association Conference (IHHA), June 2011, Calgary, Canada
• T.G. Rickettt, J.M. Hart, J.R. Edwards, A. Kumar, C.P.L. Barkan and N. Ahuja, Monitoring the Aerodynamic Efficiency of Intermodal Train Loading Using Machine Vision, Proceedings of Transportation Research Board Annual Conference, Washington, D.C., January 2011.
• A. Kumar, T.G. Rickett, A. Vemula, J. M. Hart, J.R. Edwards, N. Ahuja and C.P.L. Barkan, Aerodynamic Analysis of Intermodal Freight Trains Using Machine Vision, Proceedings of 9th World Congress on Railway Research, Lille, France, May 2011.
• Q. Kong, A. Kumar, N. Ahuja and Y. Liu, Robust Segmentation of Freight Containers in Train Monitoring Videos [ppt], Workshop on Applications of Computer Vision (WACV), Snowbird, Utah, December 2009.
• A. Kumar, N. Ahuja, J. Hart, U.K. Visesh, P.J. Narayanan, C.V. Jawahar, “A Vision System for Monitoring Intermodal Freight Trains,” Workshop on Applications of Computer Vision (WACV), Austin, TX, February 2007.
• Y-C Lai, C.P.L. Barkan, J. Drapa, N. Ahuja, J.M. Hart, P.J. Narayanan, C.V. Jawahar, A. Kumar, L.R. Milhon and M.P. Stehly, “Machine vision analysis of the energy efficiency oF intermodal freight trains,” Proc. IMechE Vol. 221 Part F: J. Rail and Rapid Transit, 2007.