A backup control unit for controlling motion of a heavy-duty vehicle during a minimum risk maneuver, where the backup control unit is arranged to receive data indicative of a planned sequence of vehicle control commands from a main vehicle control unit. The backup control unit comprises a first vehicle model configured to map the planned sequence of vehicle control commands into a desired vehicle behavior and is arranged to obtain a measured vehicle behavior from one or more vehicle sensors. Also, the back-up control unit is arranged to determine an adjusted sequence of vehicle control commands based on the planned sequence of vehicle control commands and on a deviation between the desired vehicle behavior and the measured vehicle behavior, and to transmit the adjusted sequence of vehicle control commands to a motion support device, MSD, control unit of the vehicle.

An autonomous system for a vehicle, having a control device. The autonomous system, when there is a functional impairment of the autonomous system and/or of a controlled vehicle component, is in a transition mode for at least a specified minimum transition time, in which mode the controlled component and/or at least one additional vehicle component of the traveling vehicle is controllable by the control device corresponding to a specified transition program. After the elapse of the minimum transition time, the autonomous system is in its transition mode until either a specified maximum transition time has elapsed or at least one current speed of the vehicle is below a specified maximum speed, there is a request by the driver for the acceleration of the vehicle, a current transverse acceleration of the vehicle is below a specified maximum transverse acceleration, and/or at least one vehicle stabilization controller of the vehicle is inactive.

A method for providing instructions for controlling vehicle, the method comprising: predicting a near-future driving path for the vehicle using sensor data received from environmental sensors of the vehicle. Retrieving at least one acceptable spatial deviation value indicative of the acceptable deviation from the predicted driving path. Determining a limit velocity value or a longitudinal deceleration value based on predetermined relations between spatial deviations from the near-future driving path and vehicle motion parameters and corresponding error values. The limit velocity value and the longitudinal deceleration value are determined with the constraint that the acceptable spatial deviation is not violated along the predicted driving path. Providing an instruction signal comprising an instruction for the vehicle to travel below the limit velocity value, or comprising an instruction to decelerate according to the longitudinal deceleration value in the event of a safe stop procedure.

Systems and methods for controlling navigation of an autonomous vehicle for making an unprotected turn while traversing an intersection. The methods may include identifying a loiter pose of an autonomous vehicle for stopping at a point in an intersection before initiating an unprotected turn, initiating navigation of the autonomous vehicle to the loiter pose when a traffic signal is at a first state, determining whether the traffic signal has changed to a second state during or after navigation of the autonomous vehicle to the loiter pose, and in response to determining that the traffic signal has changed to the second state, generating a first trajectory for navigating the autonomous vehicle to execute the unprotected turn if the expected time for moving the autonomous vehicle from a current position to a position when the autonomous vehicle has fully exited an opposing conflict lane is less than a threshold time.

Systems and methods for controlling navigation of an autonomous vehicle through an intersection are disclosed. The methods include determining a loiter pose of an autonomous vehicle for stopping at a point within the intersection before initiating an unprotected turn for traversing the intersection. One or more distinct classes of trajectories are then identified, each of which is associated with multiple trajectories that take the same combination of discrete actions with respect to the loiter pose. A constraint set for each of the one or more distinct classes of trajectories is then be computed based on the loiter pose, and a candidate trajectory is determined for each of the one or more distinct classes based on the corresponding constraint set. A trajectory for the autonomous vehicle for executing the unprotected turn for traversing the intersection is selected from amongst the candidate trajectories.

A safety system for a vehicle may include one or more processors configured to determine, based on a friction prediction model, one or more predictive friction coefficients between the ground and one or more tires of the ground vehicle using first ground condition data and second ground condition data. The first ground condition data represent conditions of the ground at or near the position of the ground vehicle, and the second ground condition data represent conditions of the ground in front of the ground vehicle with respect to a driving direction of the ground vehicle. The one or more processors are further configured to determine driving conditions of the ground vehicle using the determined one or more predictive friction coefficients.

Systems and methods for controlling a vehicle are provided. The systems and methods include a sensor system and a processor configured to execute program instructions, to cause the at least one processor to: receive yaw rate values, lateral acceleration values and longitudinal velocity values for the vehicle from the sensor system, determine side slip angle parameter values based on the yaw rate values, lateral acceleration values and longitudinal velocity values, determine phase portrait angles based on the side slip angle parameter values and the yaw rate values, wherein the phase portrait angles each represent an angle between yaw rate and side slip angle for the vehicle in a phase portrait of yaw rate and side slip angle, detect or predict vehicle instability based at least on the phase portrait angles, and when vehicle instability is detected or predicted, control motion of the vehicle to at least partly correct the vehicle instability.

A vehicle driving support device executes lane deviation suppression control when there is a possibility that an own vehicle deviates from a lane and when an execution prohibition condition is not satisfied, and executes the lane deviation suppression control so as to steer the own vehicle such that a behavior parameter representing a behavior of the own vehicle during the execution of the lane deviation suppression control does not exceed a behavior parameter upper limit value. The vehicle driving support device reduces the behavior parameter upper limit value or changes the execution prohibition condition such that the execution prohibition condition is not unlikely to be satisfied when the own vehicle is traveling at a speed equal to or lower than a predetermined speed, compared to when the own vehicle is traveling at a speed higher than the predetermined speed.

A reactive path planner for vehicles is disclosed. The reactive path planner, based on a nominal path from A to B, generates alternative parallel paths which are displaced by a predefined lateral distance from the nominal path using constrained quintic polynomials. Constraints are imposed on the alternative paths to ensure safety and comfort based on dynamic and mechanical feasibilities of the vehicle. A cost function is applied to the nominal path and alternative paths select the path with the least cost. The reactive path planner achieves a complete path planning solution with high computational efficiency, even in highly cluttered and dynamic environments.

The present invention provides a driving assist apparatus, a driving assist method, and a driving assist system capable of realizing driving assist in consideration of a delay in a driver's operation regardless of a configuration of a vehicle. A driving assist apparatus includes a standard running route acquisition portion configured to acquire a standard running route calculated based on curve information ahead of a vehicle that is acquired by an external world recognition portion, and an actuator control output portion configured to acquire a standard vehicle motion amount when the vehicle runs the standard running route, calculate an instruction that guides a motion amount of the vehicle toward the standard vehicle motion amount based on the standard vehicle motion amount and a current vehicle motion amount of the vehicle, and output the instruction to an actuator portion configured to provide at least one of a curving force and a braking force to the vehicle.