A vehicle control device of an embodiment includes a recognizer configured to recognize a surrounding situation of a vehicle, and a driving controller configured to execute driving control of controlling one or both of a speed and steering of the vehicle on the basis of the surrounding situation recognized by the recognizer, in which the recognizer recognizes a traffic participant present in front of the vehicle and a traffic participant priority section present in a traveling direction of the vehicle, and the driving controller sets a risk area for the traffic participant priority section on the basis of a position and a traveling direction of the traffic participant, and executes the driving control based on the set risk area and the position of the traffic participant.

A control device associated with an autonomous vehicle detects that an emergency personnel is altering traffic on a road using an emergency-related hand signal to divert the traffic from a road anomaly, such as a road accident. The control device determines an interpretation of the emergency-related hand signal. The control device determines a proposed trajectory for the autonomous vehicle according to the interpretation of the emergency-related hand signal. In certain embodiments, the control device may navigate the autonomous vehicle according to the interpretation of the emergency-related hand signal. In certain embodiments, the control device may transmit the proposed trajectory to an oversight server for confirmation. In certain embodiments, the oversight may confirm or override the proposed trajectory.

A system and method for providing assistance to vehicle occupants is disclosed. The method includes the steps of receiving a set of static information and a set of dynamic information associated with each of a vehicle, a set of Human Machine Interfaces (HMIs), and an occupant within the vehicle; processing the set of static information and the set of dynamic information through at least one of a first Artificial Neural Network (ANN) Model and a rule engine; determining an accessibility score for the occupant in response to an event based on an output of the processing; generating at least one of at least one accessibility compliant HMI content for at least one of the set of HMIs and vehicle control content for the vehicle based on the accessibility score; and executing at least one of the at least one accessibility compliant HMI content and the vehicle control content.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium that determine yield behavior for an autonomous vehicle, and can include identifying an agent that is in a vicinity of an autonomous vehicle navigating through a scene at a current time point. Scene features can be obtained and can include features of (i) the agent and (ii) the autonomous vehicle. An input that can include the scene features can be processed using a first machine learning model that is configured to generate (i) a crossing intent prediction that includes a crossing intent score that represents a likelihood that the agent intends to cross a roadway in a future time window after the current time, and (ii) a crossing action prediction that includes a crossing action score that represents a likelihood that the agent will cross the roadway in the future time window after the current time.

A vehicle control device includes a recognizer configured to recognize a surrounding environment of a vehicle including a moving object present around the vehicle and a controller configured to control at least one of a speed and steering of the vehicle. The controller restricts access to the moving object when the moving object is rotating around a vertical axis at a speed greater than or equal to a threshold value so that a front surface of the moving object recognized by the recognizer faces a position interfering with a position in a traveling direction of the vehicle as compared with when the moving object is not rotating.

Embodiments is disclosed to detect a locked heading direction of a pedestrian and to predict a path for the pedestrian using the locked heading direction. According to one embodiment, a system perceives an environment of an autonomous driving vehicle (ADV) using one or more image capturing devices. The system detects a pedestrian in the perceived environment. The system determines a facing direction of the pedestrian relative to the ADV as one of left/right side, front, or back. If the facing direction of the pedestrian is determined to be front or back facing, the system determines a lane nearest to the pedestrian. The system projects the pedestrian onto the nearest lane to determine a lane direction at the projection. The system determines a heading direction for the pedestrian locking to the lane direction of the nearest lane based on a predetermined condition.

A control system of the autonomous vehicle may generate multiple possible behavior control movements based on the driving goal and the assessment of the vehicle environment. In doing so, the method and system selects one of the best behavior control, among the multiple possible movements, and the selection is based on the quantitative grading of its driving behavior.

Provided are methods for generating high fidelity synthetic sensor data representing hypothetical driving scenarios for the vehicle. Some methods described include accessing sensor data associated with operation of a vehicle in an environment traversing a first path. Operation of a simulated vehicle is simulated along a synthetic driving scenario in the simulated environment along a second path different from the first path and in simulation with the plurality of simulated agents. Systems and computer program products are also provided.

A vehicle includes a display configured to emit light to a ground surface, a communicator configured to receive a movement signal of the vehicle through communication with an external terminal, and a controller communicatively connected to the communicator and configured to determine a moving area of the vehicle based on the received movement signal of the vehicle, determine a danger area and a safety area included in the moving area, and control the display to emit light to the danger area and the safety area.

A server includes: an interface that acquires a vehicle-mounted camera image from a vehicle traveling toward a target specified by a user; and a control unit that detects the target based on the vehicle-mounted camera image, generates recognition information that makes the target recognizable as an image or visually recognizable based on a detection result of the target, and outputs the recognition information to the vehicle.