A scenario aware perception system (10) suitable for use on an automated vehicle includes a traffic-scenario detector (14), an object-detection device (24), and a controller (32). The traffic-scenario detector (14) is used to detect a present-scenario (16) experienced by a host-vehicle (12). The object-detection device (24) is used to detect an object (26) proximate to the host-vehicle (12). The controller (32) is in communication with the traffic-scenario detector (14) and the object-detection device (24). The controller (32) configured to determine a preferred-algorithm (36) used to identify the object (26). The preferred-algorithm (36) is determined based on the present-scenario (16).

A vehicular sensing system includes at least one radar sensor disposed at a vehicle and having a field of sensing forward, rearward or sideward of the vehicle. Radar data captured by the radar sensor is received at an electronic control unit (ECU). Received transmitted signals reflected off objects and received at the receiving antennas are evaluated at the ECU to establish surface responses for the objects present in the field of sensing of the radar sensor. A data set of radar data that is representative of an object present in the field of sensing of the radar sensor is compared to stored data sets to determine if the data set corresponds to a particular stored data set of the stored data sets. Responsive to the data set of radar data being determined to correspond to the particular stored data set, the vehicular sensing system classifies the detected object.

Provided is an electronic device including: a sensing device selected from a group including a radar and a lidar and installed in a vehicle to have a sensing zone directed to outside of the vehicle, the sensing device configured to obtain sensing data about an object; an image obtainer installed in the vehicle to have a field of view directed to the outside of the vehicle, the sensing device configured to obtain image data; and a controller including at least one processor configured to process the sensing data obtained by the sensing device and the image data obtained by the image obtainer, wherein the controller generates a first virtual driving path and a second virtual driving path based on the sensing data and the image data, and when a first boundary of the first virtual driving path and a second boundary of the second virtual driving path are located at different positions, provides a virtual driving path having a boundary closest to the vehicle between the first virtual driving path and the second virtual driving path as an actual driving path.

The present disclosure relates to a device and a method for controlling a vehicle. The device may include a camera for obtaining an image of a region around the vehicle and outputting image information, a navigation for outputting a current location of the vehicle as map information, a front radar for sensing an object in front of the vehicle and generating front radar information, a front-lateral radar for sensing an object in front of and lateral to the vehicle and generating front-lateral radar information, a lamp controller that generates a shadow zone code based on at least one of the image information, the map information, the front radar information, or the front-lateral radar information, and a lamp for forming a shadow zone in a light irradiation pattern based on the shadow zone code.

Techniques are described herein that enable advanced gaming and virtual reality control using radar. These techniques enable small motions and displacements to be tracked, even in the millimeter or submillimeter scale, for user control actions even when those actions are optically occluded or obscured.

A vehicular forward-sensing system includes a radar sensor and a forward viewing image sensor disposed within a windshield electronics module that is removably installed within an interior cabin at a windshield of a vehicle. A control is responsive to outputs of the radar sensor and of the image sensor. The image sensor captures image data for an automatic headlamp control system of the vehicle and for a lane departure warning system of the vehicle. The image sensor views and the radar sensor senses an object present in the path of forward travel of the vehicle. The control determines that the object is an object of interest based at least in part on the image sensor viewing the object present in the path of forward travel of the vehicle and the radar sensor sensing the object present in the path of forward travel of the vehicle.

A method and apparatus for detecting an obstacle, an electronic device, and a storage medium. A specific implementation of the method includes: detecting, by a millimeter-wave radar, position points of candidate obstacles in front of a vehicle; detecting, by a camera, a left road boundary line and a right road boundary line of a road on which a vehicle is located; separating the position points of the candidate obstacles according to the left road boundary line and the right road boundary line of the road on which the vehicle is located, and extracting position points between the left road boundary line and the right road boundary line; projecting the position points between the left road boundary line and the right road boundary line onto an image; and detecting, based on projection points of the position points on the image, a target obstacle in front of the vehicle.

A vehicle includes a communicator that is mounted on the vehicle to perform wireless communication with a server and a controller operates the communicator to transmit an accident reception request signal and image data acquired by another vehicle to the server when the vehicle has an accident with an accident target vehicle. The controller operates the communicator to receive a fault ratio from the server when the server generates fault ratio data between the vehicle and the accident target vehicle based on the image data.

A method for radar detection of targets includes: determining digital data representative of the radar environment in real time, calculating a probability of existence of mock targets in a plurality of regions of the radar environment on the basis of the digital data representative of the radar environment, receiving digital data corresponding to at least one radar target, transmitted by the radar, including digital location data of the at least one radar target, calculating a reliable confidence index associated with the at least one radar target according to the probability of existence of mock targets in the region where the at least one radar target is located.

A method includes determining a target specification map that is associated with a task and that indicates, for each respective region of a plurality of regions around a vehicle equipped with a sensor, a target value of a parameter of the sensor. The method also includes determining a capability specification map that indicates, for each respective region, an attained value of the parameter that the sensor is configured to provide. The method additionally includes comparing the capability specification map to the target specification map to determine, for each respective region, a disparity between the target value and the attained value. The method further includes, based on the comparing, identifying one or more of: a first subset of the plurality of regions where the target value exceeds the attained value or a second subset of the plurality of regions where the attained value meets or exceeds the target value.