Reliable Data Systems is developing a video-based odometry system that enables trains to measure velocities and distances travelled without the need for trackside infrastructure. A camera is fixed in the cab, taking images of the track immediately ahead, at rates in the range 25–50 frames per second. The images in successive frames are ‘unwarped’ to provide a plan view of the track and then matched, to produce an ‘optical flow’ that measures the distance travelled. The Study Group was asked to investigate ways of putting bounds on the accuracy of such a system, and to suggest any improvements that might be made. The work performed in the week followed three strands: (a) an understanding of how deviations from the camera’s calibrated position lead to errors in the train’s calculated position and velocity; (b) development of models for the train suspension, designed to place bounds on these deviations; and (c) the performance of the associated image processing algorithms.

Problem presented by
Richard Shenton, Reliable Data Systems

Study Group contributors
Maurice Blount (University of Cambridge)
Paul Dellar (University of Oxford)
Jens Gravesen (Technical University of Denmark)
James MacLaurin (University of Oxford)
Sarah McBurnie (University of Oxford)
Andrew Stewart (University of Oxford)
David Szotten (University of Manchester)
Robert Whittaker (University of Oxford)
Dave Wood (University of Warwick)

Further developments
2011: RDS has announced the launch of its Zume-X range of forward-facing cameras at Railtex 2011, 14-16 June at Earls Court in London.