A vehicle includes a vehicle body having a cabin area and a cargo area including a truck bed assembly. A tailgate assembly is pivotally connected to the truck bed assembly. The tailgate assembly is moveable between a raised configuration and a lowered configuration. A control unit includes logic that, when executed by a non-transitory processor, causes the processor to compare a first accelerometer signal from a first accelerometer mounted to the tailgate and another accelerometer signal from a second accelerometer located outside the tailgate to determine if the tailgate is in the raised configuration or the lowered configuration.

An autonomous vehicle is configured to detect an active turn signal indicator on another vehicle. An image-capture device of the autonomous vehicle captures an image of a field of view of the autonomous vehicle. The autonomous vehicle captures the image with a short exposure to emphasize objects having brightness above a threshold. Additionally, a bounding area for a second vehicle located within the image is determined. The autonomous vehicle identifies a group of pixels within the bounding area based on a first color of the group of pixels. The autonomous vehicle also calculates an oscillation of an intensity of the group of pixels. Based on the oscillation of the intensity, the autonomous vehicle determines a likelihood that the second vehicle has a first active turn signal. Additionally, the autonomous vehicle is controlled based at least on the likelihood that the second vehicle has a first active turn signal.

A vehicular vision system includes a camera disposed at a rear portion of a vehicle and operable to capture image data and an image processor for processing image data captured by the camera. The vehicle has a tailgate that is pivotable about a horizontal pivot axis and movable along a downward swing path from a closed position toward an opened position. Image data captured by the camera is processed by the image processor to detect presence of an object in a field of view of the camera. The system, responsive to detection of the object, determines location of the object relative to the downward swing path of the tailgate. The system, responsive to determination that the object is located within the downward swing path of the tailgate between the closed position and the opened position, limits movement of the tailgate of the vehicle toward the opened position.

An eye blink detection method and system are disclosed. The eye blink detection method comprises: photographing a face using a DVS camera to obtain a stream of DVS pixels; integrating DVS pixels of the stream of DVS pixels to form a plurality of DVS frames, wherein each of the plurality of DVS frames comprises a plurality of first and second color pixels, each being associated with one or more DVS pixels indicating a brightening event and each of the second color pixel being associated with one or more DVS pixels indicating a darkening event; and determining whether there exists an eye blink action in a DVS frame of the plurality of DVS frames, wherein the determining comprises: determining whether there exists a pattern in which a first and second color region are distributed one above the other in an eye region of the at least one DVS frame.

A method of checking wing position in a CMS includes performing a calibration of a wing position supporting a camera relative to a vehicle to provide a desired field of view by capturing multiple images at different lighting conditions, extracting and storing a reference feature from each of the multiple images, triggering a wing position check, capturing a current image from the camera having a current position of the reference feature; sensing a current lighting condition at which the current image is captured, determining that one of the different lighting conditions is more similar to the current lighting condition, comparing the current position of the reference feature to the stored reference feature from the one of the multiple images generated under the one of the different lighting conditions, and outputting a result of the wing position check if a difference from the comparing step exceeds a threshold value.

An embodiment vehicle includes a side mirror, a communicator, and a controller. The communicator may be configured to transmit a search signal to a remote controller through the plurality of antennas and to receive a response signal transmitted from the remote controller as a response to the search signal. The controller may be electrically coupled to the side mirror, configured to determine whether a driver is present within a search area of the first antenna according to the driver carrying the remote controller and approaching the parked vehicle being detected, determine a location of the driver based on an intensity of the response signal received from the remote controller as a response to the search signal transmitted from the first antenna, and signal the side mirror whether to convert into a folded state or an unfolded state based on the determined location of the driver.

A vehicular automatic braking system includes a forward-viewing camera, a rearward-viewing camera and a radar sensor disposed at an equipped vehicle. When the equipped vehicle is travelling in a traffic lane of a road and a leading vehicle is present forwardly of the equipped vehicle and travelling in the same traffic lane, braking of the equipped vehicle is automatically controllable to mitigate collision by the equipped vehicle with the leading vehicle. Responsive to determination by the vehicular automatic braking system that a following vehicle is following the equipped vehicle and when the determined following vehicle is within a threshold distance from the equipped vehicle and is approaching the equipped vehicle above a threshold rate of approach, automatic braking of the equipped vehicle to mitigate collision by the equipped vehicle with the leading vehicle is adjusted to mitigate collision at the rear of the equipped vehicle by the determined following vehicle.

A method for estimating a trailer wheel position includes identifying a first set of wheel locations in a first image. Each of the wheel locations in the first set of wheel locations is associated with a corresponding trailer angle. The first set of wheel locations is clustered and a primary cluster in the first set of wheel locations is identified. A best fit curve is applied to the primary cluster. The best fit curve is a curve associating wheel position to trailer angle. An estimated wheel position is determined by applying a determined trailer angle to the best fit curve in response to the wheel being hidden in the first image. The estimated wheel position is output to at least one additional vehicle system.

Systems and methods for attaching a snowplow to a vehicle are provided. Due to the size of the snowplow and the mounting bracket being located in front of the vehicle and closer to the ground, it is difficult for a user of the vehicle to correctly orient the vehicle with respect to the snowplow. The techniques described in this disclosure use virtual alignment features that are either programmed into the vehicle or learned by the vehicle to correctly align the vehicle to the snowplow. The virtual alignment features correspond to the attachment points of the snowplow mounting bracket of the vehicle. In some instances, the vehicle may autonomously detect a snowplow and orient itself to align with the snowplow using the virtual alignment markers and other alignment features of the snowplow. This makes the snowplow attachment process seamless and easy.