Provided herein is a system and method that acquires data and determines a driving action based on the data. The system comprises a sensor, one or more processors, and a memory storing instructions that, when executed by the one or more processors, causes the system to perform, determining data of interest comprising an object, feature, or region of interest, determining whether a sharpness of the data of interest exceeds a threshold, in response to determining that the sharpness does not exceed a threshold, operating the sensor to increase the sharpness of the data of interest until the sharpness exceeds the threshold, in response to the sharpness exceeding the threshold, determining a driving action of a vehicle based on the data of interest, and performing the driving action.

A system comprises a computer having a processor and a memory, the memory storing instructions executable by the processor to monitor conditions of a roadway as a vehicle travels the roadway while an adaptive cruise control feature of the vehicle is active, identify an expected condition change based on the monitoring the conditions of the roadway, determine a preferred power state for an engine of the vehicle based on the expected condition change, determine that an engine power state transition is planned for the engine, the engine power state transition including transitioning the engine from a current power state to a planned power state, and resolve the engine power state transition based on the preferred power state.

Methods and systems are disclosed for determining sensor degradation by actively controlling an autonomous vehicle. Determining sensor degradation may include obtaining sensor readings from a sensor of an autonomous vehicle, and determining baseline state information from the obtained sensor readings. A movement characteristic of the autonomous vehicle, such as speed or position, may then be changed. The sensor may then obtain additional sensor readings, and second state information may be determined from these additional sensor readings. Expected state information may be determined from the baseline state information and the change in the movement characteristic of the autonomous vehicle. A comparison of the expected state information and the second state information may then be performed. Based on this comparison, a determination may be made as to whether the sensor has degraded.

A driving assistance apparatus includes a controller programmed to perform a deceleration assistance process of assisting in decelerating a vehicle before the vehicle arrives at a deceleration object, and to control a display apparatus to display, in a first display area, first notification information for notifying an occupant of the vehicle of the deceleration object that is a target for the deceleration assistance process. When a first object and a second object that is different from the first object are both detected as the deceleration object and the second object is the target for the deceleration assistance process but the first object is not the target for the deceleration assistance process, the controller is programmed to control the display apparatus to display, in a second display area, second notification information for notifying the occupant of the first object, the second display area is different from the first display area.

An object-detection system for an automated vehicle includes an object-detector, a receiver, and a controller. The object-detector detects detectable-objects proximate to a host-vehicle. The receiver receives an indication of an object-presence from other-transmitters proximate to the host-vehicle. The controller is in communication with the object-detector and the receiver. The controller is configured to operate the host-vehicle to avoid interference with a hidden-object when the hidden-object is not detected by the object-detector and the object-presence is indicated by at least two instances of the other-transmitters.

A vehicle acquires position information of the obstacle, identifies a collision point that may collide with the obstacle based on the acquired position information of the obstacle, controls one of steering and braking based on the position information of the identified collision point, and when controlling the steering, acquires a collision avoidance margin distance value corresponding to the position information of the identified collision point, predicts the collision position based on the position information of the obstacle and the information detected by the velocity detector, acquires a distance value between the predicted collision position and the current position, acquires a lateral movement distance value based on the acquired distance value and a preset turning radius of the vehicle, acquires a steering angle based on the acquired lateral movement distance value and the acquired collision avoidance margin distance value and controls steering based on the acquired steering angle.

Information related to a vehicle can be displayed by projecting an image based on the information on a road surface or the like. An image projection apparatus that projects an image includes: an acquisition unit that acquires information to be displayed; and an image projection unit that projects the image based on the information to be displayed acquired by the acquisition unit.

Optical sensors and particularly gimbaled optical sensors transmit an active signal at a given wavelength(s) and receive passive signals over a range of wavelengths and the active signal in a common aperture. The sensor includes a Tx/Rx Aperture Sharing Element (ASE) configured with a center region that couples the active signal to the telescope for transmission and an annular region that couples the passive emissions and the returned active signal to the detector. A filter wheel may be positioned behind the ASE to present separate passive and active images to the detector. These optical sensors may, for example, be used with guided munitions or autonomous vehicles.

A method for determining presence of an object via a vehicular radar sensing system includes providing a radar sensor having a plurality of antennas, which includes a plurality of transmitting antennas and a plurality of receiving antennas. The plurality of antennas includes a plurality of sets of antennas, each set having a V shape or an X shape, and with each of the shaped sets of antennas having an apex. A signal feed is provided to the apex of each of the shaped sets of antennas. A radar beam is transmitted via the plurality of transmitting antennas and side lobes of the transmitted radar beam are reduced via the plurality of shaped sets of antennas. An output of the receiving antennas is communicated to a processor, and the processor determines presence of one or more objects exterior the vehicle and within the field of sensing of the radar sensor.

A method and system of determining whether a stationary vehicle is a blocking vehicle to improve control of an autonomous vehicle. A perception engine may detect a stationary vehicle in an environment of the autonomous vehicle from sensor data received by the autonomous vehicle. Responsive to this detection, the perception engine may determine feature values of the environment of the vehicle from sensor data (e.g., features of the stationary vehicle, other object(s), the environment itself). The autonomous vehicle may input these feature values into a machine-learning model to determine a probability that the stationary vehicle is a blocking vehicle and use the probability to generate a trajectory to control motion of the autonomous vehicle.