A system includes a processor and a memory. The memory stores instructions executable by the processor to detect an object exterior to a vehicle, and to actuate a fluid dispenser device based on an opacity of a window and a location of the detected object.

A vehicle control apparatus is provided which includes position detecting means for detecting a position of a detected target using reflection information derived from a radar device 21, first determining means for determining whether the detected target is expected to be an obstacle not based on an intensity of a received reflected wave contained in the reflection information, and second determining means for determining whether an obstacle exists at the position, as detected by the position detecting means, or not using the image information. When the second determining means determines that the obstacle exists, and when a distance between an own vehicle and the detected target is smaller than a given threshold value, the detected target is determined as a target with which collision should be avoided regardless of a result of determination made by the first determining means. Alternatively, when the distance to the detected target is greater than the given threshold value, and when the first determining means determines that the detected target is expected to be the obstacle, the detected target is determined as a target with which collision should be avoided. This minimizes an unnecessary operation in control to avoid the collision when it is determined whether the target is an obstacle to movement of the own vehicle or not.

A system and method for online real-time multi-object tracking is disclosed. A particular embodiment can be configured to: receive image frame data from at least one camera associated with an autonomous vehicle; generate similarity data corresponding to a similarity between object data in a previous image frame compared with object detection results from a current image frame; use the similarity data to generate data association results corresponding to a best matching between the object data in the previous image frame and the object detection results from the current image frame; cause state transitions in finite state machines for each object according to the data association results; and provide as an output object tracking output data corresponding to the states of the finite state machines for each object.

A system includes a lidar, a camera, and a controller communicatively coupled to the camera and the lidar. The lidar includes a laser configured to emit pulses of light, a scanner configured to direct the emitted pulses in accordance with a scan pattern, and a receiver configured to detect the emitted pulse of light scattered by one or more remote targets to collect a set of lidar pixels of a scan frame, in a sequence defined by the scan pattern. The camera has a field of regard that at least partially overlaps the field of regard of the lidar. The controller is configured to cause the camera to capture images while the receiver of the lidar module collects the complete set of lidar pixels of the scan frame, and align lidar pixels with corresponding pixels in the captured images.

A method for controlling an automatic liftgate in a vehicle includes detecting a garage door frame of a garage using a front camera or a rear camera mounted on the vehicle, determining a garage height of the garage door frame, determining whether the vehicle has entered the garage, and setting a custom height to which the automatic liftgate can open to the garage height of the garage door frame when the vehicle has entered the garage.

In a method for ascertaining a triggering event for an airbag in a vehicle, an imminent collision is ascertained with the aid of a surroundings sensor, an error signal being generated if no signal is established in a collision sensor within a defined time window.

A camera system including: an image sensor that is controlled by one or more camera parameters; and a pre-processing circuit adapted to associate weights respectively with cells of a grid, wherein the weights differ from the one or more camera parameters, wherein the cells respectively include a plurality of contiguous picture elements of the image sensor.

A method for controlling an automatic liftgate in a vehicle includes detecting a garage door frame of a garage using a front camera or a rear camera mounted on the vehicle, determining a garage height of the garage door frame, determining whether the vehicle has entered the garage, and setting a custom height to which the automatic liftgate can open to the garage height of the garage door frame when the vehicle has entered the garage.

The present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle by comparing current image data to previously classified image data.

There is provided an automatic parking system according to an exemplary embodiment of the present disclosure. The automatic parking system includes: a smart key recognition processor recognizing a smart key positioned in a first area; a sensor unit acquiring images around a subject vehicle if the smart key is recognized, and converting the acquired image into external images and synthesizing the images; a parking space recognizing sensor periodically receiving the external images and sequentially comparing the consecutive external images using an image recognition technology to recognize parking areas; and a controller calculating a moving path between a current position of the subject vehicle and an optimal parking area among the parking areas and controlling the subject vehicle based on the moving path, in which the parking space recognizing sensor may detect the parking areas in consideration of a length and a width of the subject vehicle.