In North America, many design guidelines for track components in shared-use railway infrastructure use historic wheel loads that may not necessarily be representative of those seen on rail networks today. With-out a clear understanding of the nature of these loads, it is impossible to evaluate the superstructure adequately to make design improvements. Therefore, researchers at the University of Illinois at Urbana–Champaign are conducting research to lay the groundwork for an improved and thorough understanding of the loading environment entering the track structure. Wheel impact load detectors (WILDs) have been used in North America for decades to identify defective wheels that could damage the rail infrastructure or result in a rolling stock failure. Information regarding loads obtained from a WILD can be used to identify trends that not only provide a clearer picture of the existing loading environment created by widely varied traffic characteristics but also can be used in future design and maintenance planning of infrastructure according to the anticipated traffic. The current trends in wheel loads across the North American rail network are discussed, and the effects of speed and other sources of load variability are investigated. In addition to WILD data, instrumented wheel set data were used to gain insight into loading conditions, and preliminary analyses of these data are included. Ultimately this work will lead to useful distinctions of loads for improved design methodologies that are specific to the intended type of traffic traversing a given route or network.