Probabilistic Detection of Rollover Risk of Heavy Vehicles

The aim of this paper is to elaborate a reliable rollover risk evaluator of a heavy vehicle in order to supply reliable information to the warning or control system. This is done by calculating the probability of rollover risk. The evaluation is based on the load transfer ratio between the right and left sides. Sensitivity analysis is given to find the most influential parameters on the risk. Then, probabilistic modeling of these parameters is obtained by using Maximum Entropy Principle. After that, Unscented Kalman Filter is developed to estimate all dynamic states and to identify the height center of gravity that cannot be directly measured. Finally, the obtained probability laws are used in a reliability method to approximate the probability of rollover risk.