EXPLORING WEATHER-RELATED CONNECTED VEHICLE APPLICATIONS FOR IMPROVED WINTER TRAVEL IN THE PACIFIC NORTHWEST

Abstract

The objectives of this project were to investigate how connected vehicle (CV) data could be integrated with existing infrastructure data, and how the integrated data could be utilized to improve decision-making for highway operations and to enhance traveler information during inclement winter weather events. Because of some unforeseen difficulties, this PacTrans project was unable to pilot test the CV solution on DOT vehicles or during winter weather. Instead, the project laid the foundation to address the innovative use of CV technologies for improving winter travel mobility. We started from a literature review and a national survey of transportation agencies to understand \ current practices and the needs of using CVs for improving winter travel, followed by the development of a vision (e.g., operational scenarios). Then we focused on the development of a road surface friction analysis and visualization platform. This methodology was based on time-aware recurrent gated neural networks. The RCM-411 friction sensing data were selected as the model input. Finally, we simulated the operational enhancement of highways through the deployment of vehicle communication technology during inclement weather by using a modified Intelligent Driver Model (IDM) to incorporate the effects of CVs in a mixed traffic scenario. For high market penetration of CVs (60 percent), the model showed less speed perturbation along the roadway, leading to stable traffic movement.