Each year thousands of people are killed and injured due to weather-related crashes. While outcomes of many incidents could not be changed, many accidents could be avoided through implementation of intelligent transportation systems. Road Weather Information Systems (RWIS) have been adopted by transportation agencies to provide better information about the impact of current weather conditions on the roadway. However, RWIS can only provide data for a specific location, and there is a need for continuous road weather condition reporting. In response, the Connected Vehicle Initiative proposed using vehicles to communicate current roadway conditions, especially in inclement weather events. The advanced road condition data would allow travelers to better prepare for road conditions. This report illustrates efforts from the University of Wyoming to collect and analyze vehicle CAN-Bus vehicle data to extrapolate road conditions and determine usefulness of this data in providing realtime, weather information acceptable as input to Variable Speed Limit (VSL) algorithms. The results of this research indicate that standardization of vehicle data between vehicle makes and models is required. In addition, current vehicle data manipulation programs are not adequate for providing segmented road weather condition data need for implementation into VSL algorithms. (Author/publisher)
Abstract