A biased driving system and a biased driving method are capable of controlling biased driving of a vehicle in consideration of host vehicle location recognition accuracy, nearby vehicle risk, driving style, road curvature, and road shape. The biased driving system includes a control parameter creation unit configured to extract an object causing biasing of a host vehicle using converged object information, which is map information including location and speed of a vehicle around the host vehicle, to create an imaginary line of the extracted object by reflecting at least one of risk of a nearby vehicle, location recognition accuracy, driving style of a driver of the host vehicle, road curvature, or road shape, and to create a control parameter using the imaginary line.

An autonomous system includes a vehicle operable to travel from a first point to a second point, a first actuator operable to adjust a speed of the vehicle, and a second actuator operable to adjust a direction of travel of the vehicle. A controller is operable to send control signals to the first actuator and the second actuator to facilitate the transition of the system from a first state to a second state during travel between the first point and the second point. A reachability controller is coupled to the controller to receive the first state and the control signals and to analyze the first state and the control signals to determine if the second state is a safe state.

A method for controlling a vehicle using a toy device in an Automated Vehicle & Highway system (AVHS). The method is performed by a control device and includes: identifying the toy device in the vehicle; when the toy device is identified, receiving GUI information from the toy device or a GUI server device; preparing a specific scenario or driving mode based on the GUI information; controlling a vehicle state based on information on the specific scenario or driving mode; and when termination information is received, controlling the vehicle state based on autonomous driving information. Implementations disclosed herein enable moving to a desired destination and enjoying 4D content at the same time through the vehicle in the AVHS. An autonomous vehicle, user terminal, and/or server according to the present invention may be associated with an artificial intelligence module, robot, augmented reality (AR) device, virtual reality (VR) device, etc.

Techniques for generating trajectories and drivable areas for navigating a vehicle in an environment are discussed herein. The techniques can include receiving a reference trajectory representing an initial trajectory for a vehicle, such as an autonomous vehicle, to traverse the environment. Portions of the reference trajectory can be identified as corresponding to actions to navigate around a double-parked vehicle or to change lanes, for example. In some cases, a portion of the reference trajectory can be identified based on a proximity to an object in the environment. A weight can be associated with the portions of the reference trajectory, and the techniques can include evaluating a reference cost function at points of the reference trajectory based on the associated weights to generate a target trajectory. Further, the techniques can include controlling the autonomous vehicle to traverse the environment based at least in part on the target trajectory.

Provided is a vehicle control device configured to execute, when a driver is in an abnormal state, deceleration control for decelerating a vehicle to stop the vehicle, the vehicle control device being further configured to determine whether the vehicle is likely to stop at a specific spot based on an image acquired by an image sensor during the execution of the deceleration control, the specific spot being a spot at which another physical body moves in a direction intersecting with a travel direction of the vehicle, and the vehicle control device being further configured to, when the vehicle is likely to stop at the specific spot, execute control for causing the vehicle to pass through the specific spot and stop the vehicle thereafter.

A processor-implemented method of performing an operation using a complex-valued attention network includes: extracting a complex-valued attention weight from complex-valued input data; and determining complex-valued attention data by applying the extracted complex-valued attention weight to the complex-valued input data.

A vehicle steering control method, device and system, and a vehicle are provided. The vehicle steering control method includes: in a case where a current vehicle speed is less than a turning vehicle speed threshold, steering of a vehicle is controlled by an Electric Power Steering (EPS) to implement cornering of the vehicle; in a case where a cornering condition of the vehicle is not reached during the cornering of the vehicle, the vehicle is controlled by an Electrical Park Brake (EPB) to perform single-side parking to assist in the cornering of the vehicle; and after the single-side parking of the vehicle is implemented, closed-loop control is performed on an electric control booster, the EPB and the EPS, and the vehicle is controlled to turn under the cornering condition.

A vehicle electronic control device includes a detection device configured to detect a state of an occupant, a first control device, and a second control device. The second control device is configured to refer to a database defining a relationship between the state of the occupant and a first time and to autonomously drive the vehicle at speeds equal to or lower than the maximum allowable speed from a switching time that is the time at which the first control device becomes unable to control the vehicle. The database is set in such a manner that the maximum allowable speed corresponding to a second state of the occupant is lower than the maximum allowable speed corresponding to a first state of the occupant when the first time corresponding to the second state is longer than the first time corresponding to the first state.

The technology relates to planning trajectories for self-driving vehicles in order to transport passengers or cargo from a pickup location to a destination. Trajectory planning includes generating a speed plan for an upcoming portion of the trip in view of one or more constraints. The constraints may be due to proximity to an adjacent vehicle or other road user, and can include projected overlaps between the vehicle and other objects in the vehicle's nearby environment. Certain constraints may be binary or otherwise discontinuous in nature, in which a condition either exists at a given point in time or it does not. Noise in sensor data or prediction models may trigger such binary conditions, which in turn may cause the vehicle to alter the speed plan. Aspects of the technology employ permeable speed constraints that enable the vehicle to avoid problems associated with discontinuous constraints.

An embodiment vehicle includes a collecting device for collecting environment information, a user input for automatic parking of the vehicle, an automatic parking controller for performing the automatic parking based on the environment information and the user input, and a behavior controller for controlling a behavior of the vehicle in response to control of the automatic parking controller. The automatic parking controller calculates a first progress corresponding to determination of whether the user input is a wake-up request, a second progress corresponding to acquisition of a control right for the behavior controller, a third progress corresponding to whether the user input is an execution request for the automatic parking, a fourth progress corresponding to generation of control information for the behavior controller, and a fifth progress corresponding to control of the vehicle's behavior.