Intelligent transportation-oriented estimation of pavement friction thresholds for cooperative active safety control

To enhance the situational awareness and decision-making capabilities of intelligent vehicle active safety systems, this study proposes a methodology for defining dynamic, scenario-based thresholds. In simulations of emergency braking maneuvers, the safe braking distance serves as the primary criterion for performance evaluation. This study quantifies the sensitivity of vehicle braking performance to the attenuation of the pavement skid resistance coefficient under a matrix of typical operational conditions (e.g., dry vs. wet surfaces) and highway scenarios (e.g., open sections, tunnels) with varying design speeds. Through this sensitivity analysis, we identify the minimum skid resistance coefficient required to guarantee vehicle safety under the most adverse, yet plausible, conditions. The primary contribution is a set of proposed scenariospecific skid resistance thresholds, which are directly correlated with roadway design speeds. These thresholds serve as critical input parameters for intelligent transportation systems (ITS). They can be used to inform vehicle-to-infrastructure safety alerts and enable onboard ADAS to adapt their control strategies—such as adjusting braking distance predictions or slip ratio limits—thereby bridging the gap between road infrastructure condition and intelligent vehicle control.