To be able to handle the statewide mobile lidar data ODOT collects efficiently, there is a need for a robust workflow with significant automation that can extract many types of features by effectively leveraging various feature extraction tools and algorithms to support applications. In particular, road characterization has been identified as a key application for information extraction from mobile lidar data. In this literature review, the team first provides a brief overview of the model inventory of roadway elements (MIRE 2.0) to help identify the attributes that are of interest as well as feasible to extract from mobile lidar data. Next, a review of the existing commercial software summarizes the common challenges in using these solutions for feature extraction and characterization tasks. Lastly, the existing work related to road characterization is reviewed covering the topics of ground filtering and road extraction, cross slopes and grades, and horizontal curve, followed by a summary of the benefits of using mobile lidar data as well as the challenges of the existing studies.