Preview Horizon Analysis for Vehicle Rollover Prevention Using the Zero-Moment Point

Abstract

This research estimates the minimum preview time needed to prevent untripped wheel lift events by analyzing simple maneuvers that are idealizations of a human driver's response in collision avoidance situations. To predict a vehicle's future rollover propensity, the zero-moment point (ZMP) metric is applied to projected vehicle trajectories. Comparing different amounts of preview, the results show that short-range predictions, ranging from 0.1 s to 0.7 s, are sufficient to prevent nearly all dynamics-induced rollovers in typical highway curves. These results are useful to determine the minimum preview horizons, with respect to rollover, that may be necessary for more advanced vehicle control methods, such as model predictive control (MPC).