In order to reliably assess the expected benefits of any new system, it is important to have an accurate estimate of the baseline condition. However, there is limited baseline data for highway capacity and speeds in rural environments during weather events, major traffic incidents, construction, or similar activities. This limits how confident one can be about the extent to which transportation system improvements, including intelligent transportation systems (ITS), may enhance system capacity and reduce traveler delay. There have been studies conducted to assess the impact of weather events on highway capacity; however, the results have not proven very conclusive. For example, a 1991 investigation concluded that reductions in highway capacity due to adverse weather ranged from 7 to 56 percent. This represents a very wide range of possibilities, and does little to lend credibility to any estimated benefits resulting from ITS deployment. The goal of this project is to find a better way to estimate road, capacities with greater accuracy. A couple of recent studies, in Idaho and Iowa, have sought to address this question through the correlation of data collected from various detection technologies combined with information about weather conditions, such as visibility, snow and rain. These efforts represent a promising start in this area. This work will be built upon, also with consideration given to the grades experienced in the Rural California/Oregon Advanced Transportation Systems (COATS) project, where the terrain is often mountainous and mountain passes represent some of the most significant safety challenges in the region.