Patent classifications
B60W2720/103
Control systems and methods using parametric driver model
A control system of a vehicle includes: a target speed module configured to, using a parametric driver model and based on first driver parameters, second driver parameters, and vehicle parameters, determine a target vehicle speed trajectory for a future predetermined period; a driver parameters module configured to determine the first driver parameters based on conditions within a predetermined distance in front of the vehicle; and a control module configured to adjust at least one actuator of the vehicle based on the target vehicle speed trajectory and a present vehicle speed.
Method and device for controlling deceleration of environmentally friendly vehicle
A method for controlling deceleration of a vehicle includes determining, by a controller, a reference deceleration driving distance of the vehicle based on current speed information of the vehicle and stop signal residual time information of a traffic light located ahead of the vehicle, determining, by the controller, whether the reference deceleration driving distance is less than or equal to a distance between the vehicle and the traffic light, and determining, by the controller, a speed profile including an actual deceleration driving distance of the vehicle based on a waiting distance of a waiting vehicle that waits before the traffic light when it is determined that the reference deceleration driving distance is less than or equal to the distance between the vehicle and the traffic light.
Vehicle powertrain integrated predictive dynamic control for autonomous driving
Devices, systems, and methods for integrated predictive dynamic control of a vehicle powertrain in an autonomous vehicle are described. An example method for controlling a vehicle includes generating, based on performing an optimization on a blended smooth wheel domain fuel consumption map subject to a modified torque availability constraint, one or more wheel domain control commands, converting the one or more wheel domain control commands to one or more powertrain-executable engine domain control commands, and transmitting the one or more powertrain-executable engine domain control commands to a powertrain of the vehicle, the powertrain configured to operate a plurality of gears, wherein the one or more powertrain-executable engine domain control commands enable the vehicle to track a reference kinematic trajectory associated with a vehicle speed driving plan within a predetermined tolerance.
Method and device for controlling motion of vehicle, and vehicle
A power system of a vehicle includes an engine, a first motor and a second motor. A method for controlling motion of the vehicle includes: receiving a cruise speed, a speed fluctuation quantity and a preset traveling mileage of the vehicle, and obtaining an upper speed bound and a lower speed bound of the vehicle based on the cruise speed and the speed fluctuation quantity; adjusting a current speed of the vehicle to the lower speed bound, and controlling the vehicle to enter a first cruise phase of a two-phase cruise mode; and controlling the vehicle to enter a second cruise phase of the two-phase cruise mode when the current speed of the vehicle is greater than or equal to the upper speed bound and a current traveling mileage is less than the preset traveling mileage.
Ascertaining a Trajectory for a First Vehicle While Taking into Consideration the Drive Behavior of a Second Vehicle
A processor unit (3) is configured for accessing speed data of a second vehicle (18), the speed data generated by a sensor of a first vehicle (1). The processor unit is also configured for creating a driving behavior profile of the second vehicle (18) based on the speed data and making a prediction about the future driving behavior of the second vehicle (18) based on the driving behavior profile of the second vehicle (18). Moreover, the processor unit is configured for determining a trajectory for the first vehicle (1) by executing an MPC algorithm, which includes a longitudinal dynamic model of the first vehicle and a cost function, such that the cost function is minimized. The prediction about the future driving behavior of the second vehicle (18) is taken into account in the determination of the trajectory.
IMPLEMENTING MANOEUVRES IN AUTONOMOUS VEHICLES
A computer-implemented method of determining a series of control signals for controlling an autonomous vehicle to implement a planned speed change maneuver comprises: receiving from a maneuver planner a position target for the planned speed change maneuver; selecting, from a predetermined family of kinematic functions, a kinematic function for carrying out the planned speed change maneuver, each kinematic function being a first or higher order derivative of acceleration with respect to time; and using the selected kinematic function to determine a series of control signals for implementing the planned speed change maneuver; wherein the kinematic function is selected in a constrained optimization process as substantially optimizing a cost function defined for the speed change maneuver, subject to a set of hard constraints that: (i) require a final acceleration, speed and position corresponding to the selected kinematic function to satisfy, respectively, an acceleration target, a speed target and the position target, given an initial speed and acceleration of the autonomous vehicle, and (ii) impose a jerk magnitude upper limit on the selected kinematic function.
METHOD FOR THE PERFORMANCE-ENHANCING DRIVER ASSISTANCE OF A ROAD VEHICLE
A method for the performance-enhancing driver assistance of a road vehicle driven by a driver and provided with at least two drive wheels driven by at least one electric motor connected to a corresponding vehicular battery pack; the method comprises the steps of defining a dynamic model of the road vehicle; determining a route of a track travelled by the road vehicle; calculating, as a function of the dynamic model of the road vehicle and of the route, a convenience index relative to the use of energy of the vehicular battery pack by the electric motor; subdividing the route (R) into a plurality of sectors assigning to each a relative value of the calculated convenience index; delivering electrical power to the drive wheels according to the value of the convenience index assigned to each sector of the route.
Determining a Discrete Representation of a Roadway Section in Front of a Vehicle
A device (16) for determining a discrete representation (30) of a road section ahead of a vehicle (12) includes an input interface (22) for receiving sensor data (20) of a sensor (14) with information about the road section ahead of the vehicle, a setting unit (24) for ascertaining a control distance at which a property of the road section ahead of the vehicle that is relevant for an open-loop control of the vehicle changes based on the sensor data and for setting a support point in a discrete representation of the road section corresponding to the control distance. The setting unit is configured for setting a lower predefined second number (n2) of support points based on a predefined first number (n1) of support points. The device also includes an output interface (26) for outputting the lower predefined second number of support points to an optimizer (52) in order to determine a profile of at least one control parameter for the open-loop control of an open-loop system, a vehicle function based on the second number (n2) of support points.
Model-Based Predictive Control of a Vehicle Taking into Account a Time of Arrival Factor
A processor unit (3) for model-based predictive control of a vehicle (1) taking into account an arrival time factor is configured to calculate a trajectory for the vehicle (1) based at least in part on at least one arrival time factor, with the trajectory including an entire route (20) to a specified destination (19) at which the vehicle (1) is to arrive, and with the at least one arrival time factor influencing an arrival time of the vehicle (1) at the specified destination (19). Additionally, the processor unit (3) is configured to optimize a section of the trajectory for the vehicle (1) for a sliding prediction horizon by executing a model-based predictive control (MPC) algorithm (13), where the MPC algorithm (13) includes a longitudinal dynamic model (14) of a drive train (7) of the vehicle (1) and a cost function (15) to be minimized.
Apparatus for Controlling Vehicle, System Including Same and Method Thereof
An apparatus for controlling a vehicle includes an object selection device configured to select an object intersecting the vehicle at an intersection existing on a driving path of the vehicle, a risk determination device configured to determine a risk during driving of the vehicle based on a predicted path of the object, and a driving control device configured to determine a driving method of the vehicle based on a risk determination result.