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.

Sound signals that are not audible are generated by one or more speakers disposed in the vehicle. Reflected sound signals from a driver or a passenger of the vehicle that are not audible are received by one or more microphones disposed in the vehicle. A behavior-induced acoustic pattern is detected based on the reflected ultrasound signals. The behavior-induced acoustic pattern is analyzed to recognize a behavior of the driver or the passenger of the vehicle. A response or an alert is generated according to the recognized behavior of the driver or the passenger in the vehicle.

A vehicle control device executes, when a driver is in an abnormal state, deceleration control for decelerating a vehicle to stop the vehicle, and the vehicle control device determines 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 is a spot at which another physical body moves in a direction intersecting with a travel direction of the vehicle. When the vehicle is likely to stop at the specific spot, the vehicle control device executes control for causing the vehicle to pass through the specific spot and stops the vehicle thereafter.

A method for controlling a first sensor configured to sense an environment through which a vehicle is moving includes receiving sensor data generated by one or more sensors of the vehicle as the vehicle moves through the environment, identifying, by one or more processors and based on at least a portion of the received sensor data, one or more road portions along which the vehicle is expected to travel, and determining, by one or more processors, a configuration of the identified road portions, at least in part by determining a slope of at least one of the identified road portions. The method also includes determining, by one or more processors analyzing at least the determined configuration, an elevation of a field of regard of the first sensor that satisfies one or more visibility criteria, and causing the first sensor to be adjusted in accordance with the determined elevation.

A computer-implemented method is disclosed for controlling a speed of a vehicle. The method comprises acquiring information from a plurality of vehicle sensors, wherein the acquired information comprises image information acquired from one or more visual sensors, wherein the image information includes a driver of the vehicle. The method further comprises using one or more computer processors to perform image processing on the image information. The method further comprises dynamically determining an upper speed limit for the vehicle using the acquired information, wherein the upper speed limit is based in part on the image processing. The method further comprises receiving an acceleration input from a vehicle inceptor, and responsive to determining that application of the acceleration input would cause the speed of the vehicle to exceed the upper speed limit, transmitting a control signal to a vehicle actuator to avoid exceeding the upper speed limit.

A method for controlling at least a first sensor of a vehicle, which senses an environment through which the vehicle is moving by producing a plurality of scan lines arranged according to a spatial distribution, includes receiving sensor data generated by one or more sensors. The one or more sensors are configured to sense the environment through which the vehicle is moving. The method also includes identifying, by one or more processors and based on the received sensor data, one or more areas of interest in the environment, and causing, by one or more processors and based on the areas of interest, the spatial distribution of the plurality of scan lines produced by the first sensor to be adjusted.

A system for obtaining a prediction an action (a.sub.t) of a vehicle (V), including a camera for acquiring a sequence of images (F.sub.t) a convolutional neural network visual encoder which obtains a corresponding visual features vector (v.sub.t), one or more sensor that obtains a position of the vehicle (s.sub.t) at the same time step (s.sub.t), a Recurrent Neural Network configured to receive the visual features vector (v.sub.t) and position of the vehicle (s.sub.t) at the time step (t) and to generate a prediction of the action (a.sub.t) of the vehicle (V). The system comprising a command conditioned switch configured upon reception of a control command (c.sub.i) to select a corresponding branch of the Recurrent Neural Network. The system is configured to operate the selected corresponding branch to process the visual features vector (v.sub.t) and position of the vehicle (s.sub.t) at the time step (t) to obtain the prediction of the action (a.sub.t) of the vehicle (V).

This disclosure provides a method, apparatus, and storage medium for processing a driving simulation scenario. The method includes: acquiring a plurality of route points in a road network model for driving simulation; determining one or more departure points and one or more destination points from the plurality of route points; generating a background vehicle at the one or more departure points; and controlling the background vehicle to travel in the road network model from the one or more departure points to a corresponding destination point of the one or more destination points, where the background vehicle is removed.

Various examples are directed to systems and methods for controlling an autonomous vehicle comprising a tractor and a trailer. For example, a system may determine that a line from a position of a first sensor on the autonomous vehicle to a position of a first actor in an environment of the autonomous vehicle intersects the trailer. The system may determine that the first actor is in a blind spot of the autonomous vehicle, generate a motion plan for the autonomous vehicle, and control the autonomous vehicle in accordance with the motion plan.

The vehicle control device is a vehicle control device that executes autopilot control of a vehicle for securing a lateral distance between an object 8 existing within a predetermined distance from the driving lane and in front of the vehicle outside the driving lane of the vehicle that is the autonomous vehicle. The vehicle control device includes a type determination unit that determines a type of an object based on a detected result of a front sensor mounted on the vehicle, and a driving control unit that changes a target lateral speed in the autopilot control according to the type of the object.