The article investigates how to detect as quickly as possible whether the driver
will lose control of a vehicle, after a disturbance has occurred. Typical
disturbances refer to wind gusts, obstacle avoidance, a sudden steer, traversing
a pothole, a kick by another vehicle, and so on. The driver may be either human
or non-human. Focus will be devoted to human drivers, but the extension to
automated or autonomous cars is straightforward.
Since the dynamic behavior of vehicle and driver is described by a saddle-type
limit cycle, a proper theory is developed to use the limit cycle as a reference
trajectory to forecast the loss of control. The Floquet theory has been used to
compute a scalar index to forecast stable or unstable motion. The scalar index,
named degree of stability (DoS), is computed very early, in the
best case, in a few milliseconds after the disturbance has ended. Investigations
have been performed at a dynamic driving simulator. A 14 DoF vehicle model,
virtually driven by a real human driver, was employed. A number of evasive
maneuvers have been examined, both for understeer and oversteer vehicles.
The early detection of the loss of control is possible. The sensing of the loss
of control could be enhanced with respect to a classical ESP, although a more
in-depth investigation is needed. Some issues referring to the robustness of the
computation of the DoS are still to be investigated. Nonetheless the DoS seems
already applicable for motorsport vehicle and drivers.
