title: Fuzzy logic inference-based Pavement Friction Management and real-time slippery warning systems: A proof of concept study.
abstract: 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.
authors.affiliation: Virginia Department of Transportation (VDOT), Salem, USA. Electronic address: Shahriar.Najafi@VDOT.Virginia.gov.
authors.forename: Shahriar
authors.initials: S
authors.lastname: Najafi
authors.affiliation: Virginia Tech Transportation Research Institute (VTTI), Blacksburg, USA.
authors.forename: Gerardo W
authors.initials: GW
authors.lastname: Flintsch
authors.affiliation: Department of Bio-medical Engineering and Mechanics, Virginia Tech, Blacksburg, USA.
authors.forename: Seyedmeysam
authors.initials: S
authors.lastname: Khaleghian
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control*; D004738:Engineering; D004779:Environment Design; D017276:Friction; D017143:Fuzzy Logic; D006801:Humans; D008962:Models, Theoretical; D012449:Safety; D013499:Surface Properties
keywords: Connected vehicles; Friction; Fuzzy logic; HSIP; Locked-wheel; Pavement Friction Management (PFM)