Disclosed is a beam steering device capable of adjusting a reflection angle of incident light and reflecting the incident light to a desired location. Also disclosed is an optical apparatus configured to detect light reflected from an external object and to extract information with respect to the external object. The beam steering device includes: a substrate; an antenna layer disposed on the substrate; a dielectric layer covering the antenna layer; a refractive index changing layer disposed on the dielectric layer; and an electrode layer disposed on the refractive index changing layer.

A method is provided to control a first vehicle when the first vehicle is being overtaken. The method comprises determining whether a rear vehicle is overtaking; and controlling a speed of the first vehicle when it is determined that the rear vehicle is overtaking.

Aspects of the disclosure relate to detecting vehicle movement. For example, one or more computing devices may receive first image data representative of a vehicle's wheel and second image data representative of the wheel captured subsequent to the capture of the first image data. The one or more computing devices may determine a first location of a first portion of the wheel based on the first image data, and a second location of the first portion of the wheel based on the second image data. The one or more computing devices may calculate a value based on the angular distance between the first location and the second location of the first portion, and based on the value, determine whether the vehicle is in motion. Upon determining the vehicle is in motion the one or more computing devices may provide a signal that the vehicle is in motion.

Systems and methods for implementing one or more autonomous features for autonomous and semi-autonomous control of one or more vehicles are provided. More specifically, image data is obtained from an image acquisition device and processed utilizing one or more machine learning models to identify, track, and extract one or more features of the image utilized in decision making processes for providing steering angle and/or acceleration/deceleration input to one or more vehicle controllers. In some instances, techniques are employed such that the autonomous and semi-autonomous control of a vehicle changes between lane follow and vehicle follow modes. Further, a vehicle may determine whether to continue to follow a vehicle after the followed vehicle moves in relation to the following vehicle.

Systems and methods for implementing one or more autonomous features for autonomous and semi-autonomous control of one or more vehicles are provided. More specifically, image data may be obtained from an image acquisition device and processed utilizing one or more machine learning models to identify, track, and extract one or more features of the image utilized in decision making processes for providing steering angle and/or acceleration/deceleration input to one or more vehicle controllers. In some instances, techniques may be employed such that the autonomous and semi-autonomous control of a vehicle may change between vehicle follow and lane follow modes. In some instances, at least a portion of the machine learning model may be updated based on one or more conditions.

An image processing system includes: an image acquiring unit that acquires an image picked up by a camera, the camera being provided in a vehicle; and a quality changing unit that performs a quality changing process of decreasing a quality of the image to equal to or lower than a predetermined standard, based on at least one of a vehicle position at a time when the image is picked up, a vehicle position at a time when the image is output to an external device or a display device, and requestor information that indicates a requestor of an output request of the image.

A control method for improving fuel efficiency in an adaptive cruise control system includes: setting a target velocity profile based on a current velocity and position when a vehicle is driven by the adaptive cruise control system; determining, by the controller, whether the preceding vehicle exists while driving by the target velocity profile; comparing, by the controller, a minimum distance for preventing a collision between the preceding vehicle and the following vehicle in a case of applying the target velocity profile with a first distance between the preceding vehicle and the following vehicle when the preceding vehicle exists; and performing, by the controller, fuel efficiency driving of the following vehicle when the minimum distance is larger than the first distance and performing driving of the following vehicle according to the target velocity profile when the minimum distance is smaller than the first distance.

System, methods, and other embodiments described herein relate to preemptively modifying operation of a trailing vehicle according to predicted acceleration inputs. In one embodiment, a method includes, in response to identifying that a lane ahead of the trailing vehicle has cleared of a leading vehicle, determining an acceleration profile for the trailing vehicle that indicates a predicted acceleration that is anticipated to be provided by a driver as a function of an environmental context. The environmental context characterizes at least current surroundings of the trailing vehicle. The method includes adjusting operating parameters of the trailing vehicle according to the acceleration profile to preemptively optimize the trailing vehicle in anticipation of an acceleration input from the driver that correlates with the predicted acceleration. The method includes controlling the trailing vehicle to accelerate based, at least in part, on the operating parameters upon receiving the acceleration input.

A vehicle drive control apparatus includes: an object detection unit which detects positions, speeds, and sizes of objects around an own vehicle; and a speed control unit which detects a moving object existing in a place adjacent to a scheduled travelling path of the own vehicle and a speed change induction obstacle inducing a future speed vector change of the moving object from the objects detected by the object detection unit and changes a speed of the own vehicle, on the basis of a relative position relation of the own vehicle and the detected moving object and the speed change induction obstacle.

Aspects of the disclosure relate to detecting vehicle movement. For example, one or more computing devices may receive first image data representative of a vehicle's wheel and second image data representative of the wheel captured subsequent to the capture of the first image data. The one or more computing devices may determine a first location of a first portion of the wheel based on the first image data, and a second location of the first portion of the wheel based on the second image data. The one or more computing devices may calculate a value based on the angular distance between the first location and the second location of the first portion, and based on the value, determine whether the vehicle is in motion. Upon determining the vehicle is in motion the one or more computing devices may provide a signal that the vehicle is in motion.