In this paper, the lateral control strategy for lane
keeping task, which is an important module in the advanced
assistant driver systems, is proposed based on the model-free
reinforcement learning. Different from the model-based methods,
our method only requires the generated data rather than the
accurate system model. Furthermore, the lateral control strategy
for driver model lane keeping is given, where driver controller
and direct yaw controller (DYC) are working at the same time to
maintain the vehicle stability. Note that the dynamic game theory
is considered for this task, where the steering wheel controller for driver and the DYC compensated controller are obtained based
on Nash game theory. Finally, we give simulation examples to
prove the validity of the proposed schemes.