Integrated Driver and Active Steering Control for Vision-Based Lane Keeping

Autor: Stefano Scalzi, Mariana Netto, Riccardo Marino
Přispěvatelé: University of Rome 'Tor Vergeta', Laboratoire sur les Interactions Véhicules-Infrastructure-Conducteurs (IFSTTAR/LIVIC), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)
Rok vydání: 2012
Předmět:
Zdroj: European Journal of Control
European Journal of Control, Elsevier, 2012, 18 (5), pp 473-484. ⟨10.3166/ejc.18.473-484⟩
ISSN: 0947-3580
DOI: 10.3166/ejc.18.473-484
Popis: A nested PID steering control for autonomous vehicles equipped with artificial vision systems is designed so that the driver can override the automatic lane-keeping action and obtain a complete control of the vehicle lateral dynamics without any switching strategy. The control input is the steering wheel angle: it is designed on the basis of the yaw rate, which is measured by a gyroscope, and the lateral offset, which is measured by the vision system as the distance between the road centerline and a virtual point at a fixed distance ahead from the vehicle. No lateral acceleration and no lateral speed measurements are required. A PI active front steering control on the basis of the yaw rate tracking error is designed to compensate for constant disturbances while improving vehicle steering dynamics and reducing the influence of parameter variations. The yaw rate reference is viewed as the control input in an external control loop: it is designed using a PID control based on the lateral offset measurements to reject the disturbances on the curvature during autonomous control, i.e., when the driver is not exerting any torque on the steering wheel. A third control block is designed to allow the driver to control the vehicle (for example, lane change for passing purposes or obstacle avoidance) overriding the automatic lane-keeping action while maintaining the advantages of the yaw rate feedback. Several simulations are carried out on a standard big sedan CarSim vehicle model to explore the robustness with respect to unmodelled effects such as combined latera land longitudinal tire forces, pitch and roll and parameters variations. The simulations show reduced path following errors and new stable manoeuvres in comparison with the model predictive steering controller implemented by CarSim in both cases of autonomous and non autonomous control. Integrated automotive control; Active steering; Lane keeping
Databáze: OpenAIRE