Case Study of Road Weather Information Systems: Vehicle Sensor Integration for Accurate Winter Road Condition Estimation

Abstract

The evaluation of winter road weather conditions poses a considerable difficulty for nations situated in high latitude areas, leading researchers to devise approaches aimed at enhancing the recognition of road conditions, enhancing travel safety, and minimizing winter road maintenance expenses. The successful combination of sensor data and advanced data processing techniques has been observed to effectively classify road conditions, specifically when using stationary Road Weather Information System (RWIS) stations. This approach is further enhanced by incorporating Geographic Information Systems (GIS) for interstation data interpolation. Consequently, a comprehensive framework is established for the continuous detection of winter road surface conditions. While the system generally proves effective, it faces limitations due to geographic constraints and the availability of RWIS stations. This thesis aims to explore potential solutions to address these challenges. The study proposes the use of dashcam images and the integration of On-Board Diagnostics II (OBDII) data to estimate winter road conditions. Additionally, it introduces a dynamic segmentation method to identify road segments with a high risk of hazards. To ensure the reliability of the findings, testing and validation are performed using real-world data from the Mobile Road Weather Information System (MRWIS) collected during the winter season of 2023. The culmination of this thesis involves performing a performance evaluation of our methodologies compared to the traditional stationary RWIS + GIS approach. This evaluation serves as a significant contribution to the advancement of winter road weather assessment. By overcoming existing limitations through the use of innovative technology and empirical analysis, our research has the potential to greatly enhance the accuracy and effectiveness of evaluating winter road conditions. Ultimately, this can lead to safer travel, especially in cold climate regions.