The railroad industry uses slow orders, sometimes referred to as speed restrictions, in areas where an elevated rail temperature is expected in order to minimize the risk and consequence of derailment caused by track buckling due to excessive rail temperature. Traditionally, rail temperature has been approximated by adding a constant offset, most often 30°F, to a peak ambient air temperature. When this approximated maximum rail temperature exceeds a given risk threshold, slow orders are usually issued for a predefined period of the day.

This “one size fits all” approach, however, is not effective and suitable in all situations. On very warm days, the difference between rail temperature and ambient air temperature can exceed railroad-employed offsets and remain elevated for extended periods of time. A given temperature offset may be well suited for certain regions and track buckling risk-related rail temperature thresholds but less accurate for others. Almost 160,000 hours of rail temperature measurements collected in 2012 across the eastern United States by two Class I railroads and predicted ambient air temperatures based on the National Weather Service’s National Centers for Environmental Prediction (NCEP) data were analyzed using detection theory in order to establish optimal values of offsets between air and rail temperatures as well as times when slow orders should be in place based on geographical location and the track buckling risk rail temperature threshold. This paper presents the results of the analysis and describes an improved procedure to manage heat-related slow orders based on ambient air temperatures.