A study on the perception-action network for automatic lane keeping of a vehicle

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A study on the perception-action network for automatic lane keeping of a vehicle

Boo, K. / Lee, J.W. / Lee, S.

The objective of this research is to monitor and control the vehicle motion in order to remove out the existing safety risk based upon the human-machine cooperative vehicle control. A new perception-action network is proposed to estimate the vehicle pose parameters and control the steering wheel of the vehicle for the vehicle to keep the lane. Desired angle of the steering wheel to control the vehicle motion could be calculated through toe Action Net based upon vehicle dynamics, current and estimated pose of the vehicle every sample steps. The vehicle pose and the road curvature were also calculated by geometrically fusing sensor data from camera image, tachometer and steering wheel encoder though the Perception Net. In the networks, not only the state variables, but also the corresponding uncertainties were propagated in forward and backward direction 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 lane keeping control performance. A car like robot was utilized an quit unwanted safety problem for this experimentation. As the results, the robot was keeping very well a given lane with arbitrary shape at moderate speed.