Document Type

Journal Article

Publication Date


Subject Area

infrastructure - track, planning - methods, planning - surveys, ridership - forecasting, ridership - forecasting, mode - rail, literature review - literature review


Tracks, Scenarios, Railroad tracks, Projections, Mathematical models, Literature surveys, Literature reviews, Inspection, Geometry, Gauge (Railroads), Gage restraint, Gage (Rails), Forecasting, Empirical methods, Derailments, Degradation failures, Automated gage restraint measurement


Gage restraint is an important indicator of track condition and safety. In 1999, approximately 13% of derailments were caused by reductions in gage restraint and the resulting widening of the track gage. Existing techniques for the measurement of gage restraint allow identification of track sections with weak lateral support. However, little has been done to investigate the change in, or weakening of, gage restraint over time as a function of track, traffic, and environmental parameters. A track degradation assessment study is under way to develop models that can be used to predict changes in gage restraint by using data obtained from the automated Gage Restraint Measurement System. The degradation models will be useful for forecasting the future condition of the track, determining the appropriate frequency and timing of track inspections, and evaluating the effectiveness of maintenance strategies. A literature review of track degradation models and previous work on gage restraint analysis is presented. The rationale for adoption of an empirical approach to gage restraint degradation modeling is explained. The processing applied to the automatically collected data and the preliminary database program developed to store the information and estimate track degradation equations are also described. The track degradation analysis and database development study currently focuses on gage restraints and track geometry parameters as measures of condition. In the future, this can be extended to include other degradation parameters for a comprehensive track performance analysis.