This study presents an innovative approach to the planning of a critical highway sensor infrastructure - road weather information system RWIS. The problem is formulated to minimize the spatially averaged kriging variance of hazardous road surface conditions while maximizing the coverage of accident-prone areas. This optimization framework takes explicit account of the value of information from an RWIS network, providing the potential to enhance the overall efficacy of winter maintenance operations and the safety of the travelers. Spatial simulated annealing is used to solve the resulting optimization problem and its performance is demonstrated using a real-world case study from Minnesota, United States. The case study illustrates the distinct features of the proposed model, assesses the effectiveness of the current location setting, and recommends additional stations locations. The findings of our study suggest that the proposed model could become a valuable decision-support tool for planning a new RWIS network and evaluating the performance of alternative RWIS expansion plans.
['Tae Jung Kwon', 'Liping Fu', 'Stephanie J. Melles']
Location Optimization of Road Weather Information System RWIS Network Considering the Needs of Winter Road Maintenance and the Traveling Public