Risk indicators prediction based on the estimation of tire/road forces and the maximum friction coefficient: Experimental validation

Improving road safety, requires the assessment of risk indicators. The prediction of these indicators is of a major importance to enhance safety systems and to warn the driver on a possible risk situation. This paper presents a prediction algorithm for risk indicators, to expect possible risk situations in future instants. The algorithm consists in adopting hypotheses about the trajectory, velocity, and acceleration in future instants and uses these assumptions, allied to previous road information to calculate the future tire/road lateral and vertical efforts and side slip angle using a state observer. Once calculated, an estimation method is used to estimate the maximum friction coefficient. Then the risk indicators, which are the lateral load transfer (LTR) and the lateral skid indicator (LSI), based on these efforts and the maximum friction coefficient, could be predicted in order to expect and avoid possible dangerous situations. One contribution of this work is the application of a maximum friction coefficient estimator, used to predict the future risks. Experimental validations are shown using our laboratory vehicle in real situations.