Fuzzy logic inference-based Pavement Friction Management and real-time slippery warning systems: A proof of concept study

• A real-time slippery road warning system is proposed under a proof of concept.
• The proposed system can be applied in snow removal operation and connected vehicles.
• The fuzzy logic system is a reliable tool for the PFM decision-making process.
• Friction is a significant factor affecting the rate of wet and dry vehicle crashes.

Minimizing roadway crashes and fatalities is one of the primary objectives of highway engineers, and can be achieved in part through appropriate maintenance practices. Maintaining an appropriate level of friction is a crucial maintenance practice, due to the effect it has on roadway safety. This paper presents a fuzzy logic inference system that predicts the rate of vehicle crashes based on traffic level, speed limit, and surface friction. Mamdani and Sugeno fuzzy controllers were used to develop the model. The application of the proposed fuzzy control system in a real-time slippery road warning system is demonstrated as a proof of concept. The results of this study provide a decision support model for highway agencies to monitor their network’s friction and make appropriate judgments to correct deficiencies based on crash risk. Furthermore, this model can be implemented in the connected vehicle environment to warn drivers of potentially slippery locations.