A Developed Methodology for Determining Gravel Roads' Level of Service: A Case Study of Wyoming

The focus of this research is to develop a systematic method for ascertaining the level of service (LOS) of gravel roads in the US. To date, such a method does not exist in the highway capacity manual (HCM). In this research, a methodology comprising eight criteria that affect gravel road traffic operations is developed. For each criterion, a rating is assigned. It is either "Good", "Fair" or "Poor". The results of each individual criterion rating are combined to develop an overall LOS rating. Furthermore, a non-parametric machine learning technique, namely the classification and regression tree (CART) modeling structure, is employed to quantify the contribution of each criterion to the overall gravel roads' LOS. As a case study, the developed methodology is implemented to assess traffic operations of gravel roads in Laramie County, Wyoming. The studied gravel road network is compiled and managed in a Geographic information system (GIS) shapefile prepared for the purpose of this research. That is to provide decision-makers in local agencies a computerized tool to efficiently track the performance of their gravel road network. Roughly 63.5% of the gravel road segments are operating at an LOS "Fair", while 19% are operating at an LOS "Poor" and unexpectedly 17.5% are operating at an LOS "Good". All gravel roads assessed are low-volume roads with 400 vpd or less. The developed methodology is intended to benefit traffic engineers, decision-makers, and any other stakeholders. The gravel road LOS methodology was developed and applied to Wyoming's conditions. Minor adjustments might be needed for implementation in other jurisdictions.