Disclosed is a simulation learning-based drowsy driving simulation platform system for detecting careless driving in conjunction with deep learning, the simulation learning-based drowsy driving simulation platform system comprising: a drive state warning device configured to determine a driver's careless driving from a captured image, determine a driver's careless driving determination level, and output the determined level; a smart cruise control interworking part configured to transmit the driver's careless driving determination level outputted from the drive state warning device; and a smart cruise control processing part configured to control a vehicle according to the driver's careless driving determination level transmitted by the smart cruise control interworking part, during a smart cruise control operation.

A learning device includes a planner configured to generate information indicating an action of a vehicle, and a reward deriver configured to derive a plurality of individual rewards obtained by evaluating each of a plurality of pieces of information to be evaluated, which include feedback information obtained from a simulator or an actual environment by inputting information based on the information indicating the action of the vehicle to the simulator or the actual environment, and derive a reward for the action of the vehicle on the basis of the plurality of individual rewards. The planner performs reinforcement learning that optimizes the reward derived by the reward deriver.

A control method is provided for controlling a lateral position of a motor vehicle. The control method includes calculating a sighting distance of a detector means embedded in the vehicle, calculating a first component of a steering angle setpoint of a steered wheels of the vehicle, and calculating a second component of the steering angle setpoint. The first component is an open loop component of a control system, while the second component is a closed loop component of the control system. The first component is weighted by a gain that is a decreasing function of the sighting distance.

Systems and methods are disclosed for reducing second order dynamics delays in a control subsystem (e.g. throttle, braking, or steering) in an autonomous driving vehicle (ADV). A control input is received from an ADV perception and planning system. The control input is translated in a control command to a control subsystem of the ADV. A reference actuation output is obtained from a storage of the ADV. The reference actuation output is a smoothed output that accounts for second order actuation dynamic delays attributable to the control subsystem actuator. Based on a difference between the control input and the reference actuation output, adaptive gains are determined and applied to the input control signal to reduce error between the control output and the reference actuation output.

Provided are a hybrid power vehicle range extender power following control method and system. The method includes: when a vehicle satisfies range extender power closed-loop control conditions, an actual charge-discharge power of a power battery and a charge-discharge power expectation value of the power battery are taken as control errors to adjust a total range extender electric power requirement, an engine torque requirement is calculated according to the total range extender electric power requirement, and an engine is controlled to perform the engine torque requirement; and when it is detected that a drive motor electric power suddenly changes and/or a load power suddenly changes, engine quick torque control is activated, and an engine quick torque requirement is taken as a feed-forward value of a generator speed setting controller to control a generator.

An embodiment method for controlling a hybrid vehicle includes driving a motor that starts an engine of the hybrid vehicle and controlling the motor to generate an engine starting torque to prevent a vibration of the engine, wherein the engine starting torque is generated by a feedforward control method. An embodiment device for controlling a hybrid vehicle includes a motor configured to start an engine of the hybrid vehicle, and a controller configured to drive the motor and control the motor to generate an engine starting torque to prevent a vibration of the engine, wherein the engine starting torque is generated by a feedforward control method.

Systems and methods are provided for adjusting the creep torque to maneuver a vehicle to a target location. In various embodiments, the creep torque adjustment mode is deactivated when the driver changes the direction of travel. The change in direction also causes the parameters of the creep torque control to be reinitiated to their initial values. In various embodiments, the creep torque mode is increased from a low creep towards a target creep. If the driver engages the brakes, the input torque is set to zero, and when the driver releases the brake, the minimum creep torque is set to the value that creep torque had risen to just before the brake was applied. This allows the driver to control the acceleration and speed, by just braking. In various embodiments, the creep control controls reverse creep to aid in hooking up a vehicle to a trailer.

A controller and a method for controlling motion of a vehicle is provided. The method comprises acquiring motion information including a current state of the vehicle and a desired state of the vehicle, determining a combination of a steering angle of the wheels and motor forces for moving the vehicle from the current state into the desired state by using a first model of the motion of the vehicle and a second model of the motion of the chassis of the vehicle, determining a cost function of the motion of the vehicle, optimizing the cost function of the motion of the vehicle to compute a command signal for controlling the steering wheel and the plurality of electric motors, and controlling the steering angle of the wheels and the motor forces based on the command signal.

A number of illustrative variations may include a system including brake-to-steer algorithms may achieve lateral control of a vehicle without longitudinal compensation but may also force a vehicle to slow down too rapidly before appropriate lateral movement can be achieved and may deliver an unnatural driving experience for vehicle occupants. A more natural feeling deceleration may be achieved by optimally selecting appropriate transmission shifts to allow for optimal engine speed or electric motor speed and torque based on current vehicle speed thereby reducing undesirably longitudinal disturbance.

An optimal lane keeping assistance device of an articulated vehicle (100), in which a tractor (200) and a trailer (300) are connected via a fifth wheel coupling (400), includes a first sensor (520,540) which detects a tractor state variable, a second sensor (560) which detects a fifth wheel coupling (400) state variable, and an electric control unit (500) incorporating a microcomputer. The electric control unit (500) calculates a control variable (Uc) according to a target lateral displacement value (Yd), an output signal of the first sensor (520, 540), and an output signal of the second sensor (560), taking into account a feedback gain of an optimal control rule, to calculate a target steering angle (δf) of the tractor (200) according to the calculated control variable (Uc) and the output signal of the first sensor (520,540), and to assist steering of the tractor (200) based on the calculated target steering angle (δf).