Developing Statewide Optimal RWIS Density Guidelines Using Space-Time Semivariogram Models

Abstract EN

Preventing weather-related crashes is a significant part of maintaining the safety and mobility of the travelling public during winter months.

To help mitigate detrimental effects of winter road conditions, transportation authorities rely on real-time and near-future road weather and surface condition information disseminated by road weather information systems (RWIS) to make more timely and accurate winter road maintenance-related decisions.

However, the significant costs of these systems motivate governments to develop a framework for determining a region-specific optimal RWIS density.

Building on our previous study to facilitate regional network optimization, this study is aimed at considering the nature of spatiotemporally varying RWIS measurements and integrating larger case studies comprising eight different US states.

Space-time semivariogram models were developed to quantify the representativeness of RWIS measurements and examine their effects on regional topography and weather severity for improved generalization.

The optimal RWIS density for different topographic and weather severity regions was then determined via one of the most successful combinatorial optimization techniques—particle swarm optimization.

The findings of this study revealed a strong dependency of optimal RWIS density on varying environmental characteristics of the region under investigation.

It is anticipated that the RWIS density guidelines developed in this study will provide decision makers with a tool they need to help design a long-term RWIS implementation plan.