A method to control, while driving along a curve, a road vehicle with a variable stiffness and with rear steering wheels. The method comprises the steps of: determining an actual attitude angle of the road vehicle; establishing a desired attitude angle; determining an actual yaw rate of the road vehicle; establishing a desired yaw rate; and changing, in a simultaneous and coordinated manner, the steering angle of the rear wheels and the distribution of the stiffness of the connection of the four wheels to the frame depending on a difference between the actual attitude angle and the desired attitude angle and depending on a difference between the actual yaw rate and the desired yaw rate.

Systems and methods for operating autonomous vehicles are described. An autonomous vehicle may detect strategy modes and/or actions of other vehicles in a local environment. The autonomous vehicle may then select a strategy mode for its operations based on the detected strategy modes and/or actions of other vehicles, and based on an operational goal for the autonomous vehicle. The strategy modes may include an uncoupled strategy mode, a permissive strategy mode, an assistive strategy mode, and a preventative strategy mode. The autonomous vehicle may further select an action for its operations based on the selected strategy mode.

A vehicle (10) includes a VP (120) that carries out vehicle control in accordance with a command from an autonomous driving system (202) and a vehicle control interface (110) that interfaces between the autonomous driving system (202) and the VP (120). A tire turning angle command that requests for a wheel steer angle is transmitted from the autonomous driving system (202) to the VP (120). A signal indicating an estimated wheel angle which is an estimated value of the wheel steer angle is transmitted from the VP (120) to the autonomous driving system (202). The VP (120) steers the vehicle in accordance with the tire turning angle command set based on a wheel estimation angle while the vehicle (10) is in a straight-ahead travel state.

In one embodiment, in response to a request to make a three-point turn for an autonomous driving vehicle (ADV), a forward turning path is generated using a first spiral function based on a maximum forward curvature change rate. A backward turning path is generated using a second spiral function based on a maximum backward curvature change rate. The forward and backward curvature change rates may be determined based on the maximum forward and backward turning angles associated with the ADV, which may be specified as a part of vehicle specification or vehicle design of the ADV. The backward turning path is initiated from an end point of the forward turning path. A three-point turn path is then generated based on the forward turning path and the backward turning path. The ADV is then driven according to the three-point turn path by issuing one or more proper control commands.

Methods and systems for operating axles of a vehicle are provided. In one example, a propulsion source of a first axle is operated in a torque control mode at a first torque and a propulsion source of a second axle is operated in a torque control mode at a second torque. Torque of the propulsion sources may be adjusted as a function of steering angle.

A drive force control system for a vehicle configured to allow a driver to find out a steering angle at which a wheel grips a road surface. In the vehicle, a torque distribution ratio to a pair of wheels turned by a steering wheel and another pair of wheels is changeable. A controller restricts a control to change the torque distribution ratio in the event of a slip of the pair of wheels, if a steering angle of the pair of wheels is changed to allow the pair of wheels to grip a road surface.

A system for detecting a vehicular crash (i) receives data from the at least one sensor; (ii) determines that a potential vehicular crash is imminent based upon the received data; and (iii) performs at least one action to reduce a severity of the potential vehicular crash prior to impact. As a result, at least one of the potential injuries to passengers and the potential damage to a vehicle involved in the potential vehicular crash is reduced.

A system for analyzing the environment of a vehicle (i) receives a plurality of data from at least one sensor associated with a vehicle, such that the plurality of data includes at least one environmental condition; (ii) analyzes the plurality of data to determine the at least one environmental condition; (iii) determines at least one actionable item based upon the at least one environmental condition; (iv) determines at least one provider based upon the actionable item; and (v) transmits a message to the at least one provider, such that the message includes the at least one actionable item. As a result, the speed and accuracy of providers learning about potential actionable items is increased.

A vehicle control method includes recognizing a vicinity of a vehicle, setting a risk index for a traffic participant, and controlling a vehicle-mounted instrument of the vehicle based on the risk index which is set by the setter, and setting a risk index for a position at which the traffic participant will be present in the future based on ease of entry of the traffic participant from a sidewalk to a roadway adjacent to the sidewalk in a region that the traffic participant traveling on the sidewalk will enter in the future, and increasing a risk index to be set on the roadway side as there is a greater tendency for the traffic participant to enter the roadway.

Provided is a vehicle control device including: a recognition unit configured to recognize an object which is located near a vehicle; a calculation unit configured to calculate an area of risk which is distributed around the object; a generation unit configured to generate a target trajectory for the vehicle to travel along on the basis of the area; and a driving control unit configured to automatically control at least one of a speed or steering of the vehicle on the basis of the target trajectory, wherein the generation unit selects one or a plurality of models from a plurality of models that output the target trajectory in a case where the area is input, inputs the area calculated by the calculation unit to the selected model, and generates the target trajectory on the basis of an output result of the model to which the area is input, and the calculation unit changes a range of the area in accordance with a type of model selected by the generation unit.