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.

Early Detection of the Loss of Control of Motorsport Vehicles

Della Rossa, Fabio;Giacintucci, Samuele;Gobbi, Massimiliano;Previati, Giorgio
2025-01-01

Abstract

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.
2025
Active safety; AI; Crash avoidance; Driver; Driver model; Dynamic driving simulator; ESP; Evasive maneuver; Floquet theory; Limit cycle; Stability;
Active safety
AI
Crash avoidance
Driver
Driver model
Dynamic driving simulator
ESP
Evasive maneuver
Floquet theory
Limit cycle
Stability
File in questo prodotto:
File Dimensione Formato  
10-09-03-0029.pdf

accesso aperto

: Publisher’s version
Dimensione 6.71 MB
Formato Adobe PDF
6.71 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1296749
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact