Aquaplaning Detection Using Effect-Based Methods: An Approach Based on a Minimal Set of Sensors, Electronic Stability Control, and Drive Torques

Abstract

Knowledge of actual tire-road friction potential is most relevant for safe operation of automated vehicles and for adjusting advanced driverassist systems. Aquaplaning may result in considerably reduced friction potential and unstable vehicle behavior for rear-wheel-drive vehicles; thus, awareness of risk of aquaplaning is crucial. Analysis of numerous measurements from driving on wet road surfaces, including, for example, different water levels, types of tires, tire inflation pressures, and tire wear, has revealed characteristic dynamic behavior of vehicles and their subsystems that could be related to an immediately approaching onset or the presence of aquaplaning. Thus, methods to detect such characteristic behavior are developed, and a combined detection algorithm based on effect-based criteria to detect the risk or presence of aquaplaning for rear-wheel-drive vehicles is proposed. The effectiveness and limitations of the individual methods, as well as the reliability of the presented algorithm, are shown based on measurements from test maneuvers.