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Integrated driver and active steering control for vision-based lane keeping. (English) Zbl 1292.93089

Summary: 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) over-riding 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 lateral and longitudinal tine 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.

MSC:

93C85 Automated systems (robots, etc.) in control theory
93C15 Control/observation systems governed by ordinary differential equations
93B35 Sensitivity (robustness)

Software:

ARGO; Carsim
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References:

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