Train localization and parting detection using data fusion

Data fusion schemes for train localization and parting detection for the Train Collision Avoidance System (TCAS) in Indian Railways are described and evaluated. The requirements and constraints for the application are reviewed and the relevance of related technologies reported with the TCAS problem is discussed. The autonomous component of train localization in TCAS should (i) determine the longitudinal (along track) position of the train, (ii) provide reliable velocity measurement for automated braking and (iii) detect accidental train parting by comparing the longitudinal positions of the engine and the last carriage. This paper examines whether the above duties can be performed during GPS outage and GPS dark regions, without using track-side aids. The system engineering issues for selecting sensors and short-listing of data fusion options are discussed in the context of the above requirements. A number of data fusion solutions including a new proposed scheme for longitudinal localization are discussed and compared with two solutions reported earlier. A novel scheme for detecting train parting situation, based on fusion-filters and fault detection approach is also described and its performance evaluated. All the reported schemes use odometer and accelerometer. Parametric performance analyses are performed to select appropriate algorithms, sensor specification and tuning parameters. Representative simulation results are included. (C) 2010 Elsevier Ltd. All rights reserved.