Highway roughness is a concern for both the motoring public and highway authorities. Roughness may even increase the risk of crashes. Rail-highway grade crossings are particularly problematic. Roughness may be due to deterioration or simply due to the way the crossing was built to accommodate grade change, local utilities, or rail elevation. With over 216,000 crossings in the US, maintenance is a vast undertaking. While methods are available to quantify highway roughness, no method exists to quantitatively assess the condition of rail crossings. Conventional inspection relies on a labor-intensive process of qualitative judgment. A quantifiable, objective and extensible procedure for rating and prioritizing improvement of crossings is thus desired. In this dissertation, a 3D infrastructure condition assessment model is developed for evaluating the condition and performance of rail highway grade crossings. Various scanning techniques and devices are developed or used to obtain the 3D “point cloud” or surface as the first step towards quantifying crossing roughness. Next, a technique for repeatable field measurement of acceleration is presented and tested to provide a condition index. Acceleration-based metrics are developed, and these can be used to rate and compare crossings for improvement programs to mitigate potential vehicle damage and provide passenger comfort. A vehicle dynamic model is next customized to use surface models to estimate vertical accelerations eliminating the need for field data collection. Following, crossing roughness and rideability is estimated directly from 3D point clouds. This allows isolation of acceleration components derived from the surface condition and original design profile. Finally, a practice ready application of the 3D point cloud is developed and presented to address hump crossing safety. In conclusion, the dissertation presents several methods to assess the condition and performance of rail crossings. It provides quantitative metrics that can be used to evaluate designs and construction methods, and efficiently implement cost effective improvement programs. The metrics provide a technique to measure and monitor system assets over time, and can be extended to other infrastructure components such as pavements and bridges.