Patent ID: 9266533
Filing Date: 2016-02-23
CPC Classification: B60K,B60W

Claim Text:
1. An adaptive cruise control system, comprising: an adaptive cruise mode selection circuit configured to select adaptive cruise modes to control speeds and relative distances for a host vehicle in different modes; at least one data acquisition sensor configured to acquire vehicle state information x(t), the vehicle state information x(t) including information indicative of a relative distance and of a relative speed; a control circuit configured to generate a vehicle control signal u(t) based on the vehicle state information x(t); a critic circuit configured to evaluate a control performance according to the vehicle state information x(t) and the vehicle control signal u(t) to drive the host vehicle; and a gas pedal and a brake, which, in operation, are controlled respectively by using the vehicle control signal u(t) output from the control circuit and a vehicle pedal and brake control inverse dynamics model, wherein: an output of the critic circuit is an approximate performance index for determining whether the control performance complies with a determined performance requirement, if the control performance complies with the determined performance requirement, the critic circuit is configured to continue to execute evaluation based on the vehicle control signal; if the control performance does not comply with the determined performance requirement, the control circuit and the critic circuit execute respective online training processes; the adaptive cruise control system is turned off to switch to a manual control mode in response to manual activation of the gas pedal or the brake so as to execute the online training processes of the control circuit and the critic circuit; the online training process of the critic circuit is designed using a three layered feed-forward neural network so as to decrease a learning error objective function to a predefined threshold or a number of performing the online training process reaches a predetermined value; the approximate performance index J(t) is defined as where γ is a discount factor, 0<γ≦1, r(t) is an instant reward at time t and defined as a quadratic form, where ρ wherein a learning error for the online training process of the critic circuit is defined as  where e where e a (t)=J(t)−U c (t), and U c (t) is set as a value closest to the approximated performance index.