The objective of this research is to monitor and control the vehicle motion in order to remove the existing safety risk based upon the human-machine cooperative vehicle control. A predictive control method is proposed to control the steering wheel of the vehicle to keep the lane. The desired angle of the steering wheel to control the vehicle motion can be calculated based upon vehicle dynamics, current and estimated pose of the vehicle every sample steps. The vehicle pose and the road curvature were calculated by geometrically fusing sensor data from camera image, tachometer and steering wheel encoder through the Perception Net, where not only the state variables, but also the corresponding uncertainties were propagated in forward and backward directions in such a way to satisfy the given constraint condition, maintain consistency, reduce the uncertainties, and guarantee robustness. A series of experiments was conducted to evaluate the control performance, in which a car like robot was utilized. The robot kept very well a given lane with arbitrary shape at moderate speed.
Automatic lane keeping of a vehicle based on Perception Net
2000
9 Seiten, 8 Quellen
Conference paper
English
A study on the perception-action network for automatic lane keeping of a vehicle
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