A motor vehicle for operation by a driver has a frame with wheels and a motor connected to the frame. A steering control is connected to the wheels to establish a steering angle. A controller is operably connected to the steering control, to the motor, and to the wheels, and is operable to selectably drive the wheels in a forward direction in a drive mode and in a rearward direction in a reverse mode. The controller is operable to select a direction for driving the wheels in response to a pattern of steering angle movements, without operator indication of a direction.

A vehicle control apparatus includes a processor. Before the vehicle passes through an inflection point of a curvature of a target trajectory, the processor sets a first reference point before the inflection point. After the vehicle passes through the inflection point, the processor sets a second reference point at a position where a second distance from a current position of the vehicle after the vehicle passes through the inflection point to the second reference point is longer than a first distance from a current position of the vehicle before the vehicle passes through the inflection point to the first reference point when compared under travel conditions identical in a vehicle speed, an acceleration rate, a deceleration rate, or a steering angle. The processor sets a target steering angle based on the curvature of an arc passing through the current position and the first reference point or the second reference point.

A vehicle control apparatus sets a target speed of a vehicle such that a maximum value of the target speed is a first speed during a parking assist control. The vehicle control apparatus executes the parking assist control with maintaining a speed of the vehicle at a speed equal to or slower than a predetermined speed limit value slower than the first speed when a predetermined condition that the vehicle moves along a downward slope, is satisfied when a first electric power source device is in a normal state during the parking assist control. At least one of a braking apparatus and a shift change apparatus executes a stopping control of stopping the vehicle when a malfunction occurs in the first electric power source device during the parking assist control.

A vehicle includes a front axle having left and right front wheels and a rear axle having left and right rear wheels. A steering-wheel assembly is used to control at least the front wheels. Left and right driver-actuatable inputs are supported by the steering wheel assembly. A vehicle controller is programmed to, responsive to actuation of the driver-actuatable inputs, place the vehicle in one or more operating modes such as tank turn, trail turn assist, or diagonal driving mode.

A system for picking up, bundling and depositing agricultural material having a traction vehicle and a towed implement, the system comprising: an actuator associated with the implement; a control device configured to generate control data for controlling the orientation of the implement and steering of the traction vehicle, the control data including information relating to the orientation of the implement adjustable by the actuator, a desired orientation of the deposited agricultural material and at least one of a speed and a direction of travel of the traction vehicle; and wherein, using the control data, the actuator adjusts the orientation about a vertical axis of the implement relative to the traction vehicle to deposit the agricultural material.

The invention relates to a method for checking an AI-based information processing system used in the partially automated or fully automated control of a vehicle, wherein at least one sensor of the vehicle provides sensor data, the captured sensor data are evaluated by an AI-based information processing system arranged in a first control circuit of the vehicle and, from the evaluated sensor data, at least one output for controlling the vehicle is generated. The AI-based information processing system is checked by a testing circuit arranged in a second control circuit of the vehicle using at least one testing method, and wherein a test result of the at least one testing method is stored, with a reference to the tested AI-based information processing system and to the at least one testing method used, in a multi-dimensional data structure in a database arranged in the vehicle.

Systems and methods to perform behavioral planning in an autonomous vehicle from a reference state involve generating a set of actions of a fixed size and fixed order according to a predefined methodology. Each action is a semantic instruction for a next motion of the vehicle. A set of trajectories is generated from the set of actions as an instruction indicating a path and a velocity profile to generate steering angles and accelerations for implementation by the vehicle. A trajectory filter is applied to filter the set of trajectories such that unfiltered trajectories are candidate trajectories. Applying the trajectory filter includes assessing the path and velocity profile indicated by each of the set of trajectories. A selected trajectory is used to control the vehicle or the action that corresponds to the selected trajectory is used in trajectory planning to generate a final trajectory that is used to control the vehicle.

A steering device includes: a steering wheel which is rotatable over an angle range exceeding 180 degrees in each of leftward and rightward directions from a neutral position; a steering mechanism that steers a wheel according to a steering angle of the steering wheel, with a ratio of the steering angle to a steered angle being changeable; and a control device that controls the ratio of the steering mechanism. The control device sets the ratio to a first value during travel of a vehicle in the manual driving mode and sets the ratio to a second value smaller than the first value during travel of the vehicle in the automatic driving mode, wherein the second value is set such that the steering angle corresponding to a maximum steered angle of the wheel specified by the steering mechanism is less than 180 degrees.

A method for perception fields driving related operations, the method may include (i) obtaining object information regarding one or more objects located within an environment of a vehicle; (ii) determining, using one or more neural network (NNs), one or more virtual forces that are applied on the vehicle, wherein the one or more virtual forces represent one or more impacts of the one or more objects on a behavior of the vehicle; wherein the one or more virtual forces belong to a virtual physical model; and (iii) performing one or more driving related operations of the vehicle based on the one or more virtual forces.

A control method for a host vehicle (100), comprising a) acquiring a speed (Vx) of the host vehicle, a relative speed (Vr) and distance (Dr) between a preceding vehicle (200) and the host vehicle (100); b) calculating a perceived risk level (PRL) as a function of said speed Vx of the host vehicle, said relative speed Vr, said relative distance Dr, and at least one of variables Vx*Vr and Vx.sup.2; and c) controlling at least one vehicle device (32, 34, 36, 38) of the host vehicle as a function of the perceived risk level (PRL). A computer program, a non-transitory computer-readable medium, and an automated driving system for implementing the above method.