The present disclosure relates to a driving control system and a method of controlling the same using sensor fusion between vehicles, and the driving control system allows vehicles to share sensor data, fuses the sensor data, matches the adjacent vehicle and the sensor data, improves recognition performance in respect to a periphery, controls driving in accordance with a change in peripheral environment and a traveling state of another vehicle, receives sensor data of another vehicle, converts a coordinate of sensor data of the matched vehicle, and fuses host vehicle sensor information, which makes it possible to improve recognition performance and accuracy in respect to a surrounding environment and object, enable stable autonomous driving, and improve stability of the vehicle.

A method and a system for generating a mesh representation of a surface. The method includes receiving a three-dimensional (3D) point cloud representing the surface, generating a reconstruction dataset having a higher resolution than the 3D point cloud in one or more regions corresponding to the surface from the 3D point cloud, and generate a polygon mesh representation of the surface by using a fine-to-coarse hash map for building polygons at a highest resolution first followed by progressively coarser resolution polygons, using the reconstruction dataset.

A dynamic sensor model is implemented by a vehicle to adapt sensor behavior to vehicle modifications and transformations. Responsive to impairment of a feature of the vehicle due to initial conditions for a target sensor being outside a range of current readings and further to receiving signals indicative of a upfit to the vehicle, an upfit zone of the vehicle is identified. The upfit zone corresponds to the target sensor. One or more reconfigurations of sensors of the vehicle within the upfit zone are performed to address the impairment of the feature.

An apparatus includes a processor configured to be disposed with a vehicle and a memory coupled to the processor. The memory stores instructions to cause the processor to receive, at least two of: radar data, camera data, lidar data, or sonar data. The sensor data is associated with a predefined region of a vicinity of the vehicle while the vehicle is traveling during a first time period. At least a portion of the vehicle is positioned within the predefined region during the first time period. The method also includes detecting that no other vehicle is present within the predefined region. An environment of the vehicle during the first time period is classified as one state from a set of states that includes at least one of dry, light rain, heavy rain, light snow, or heavy snow, based on at least two of the sensor data to produce an environment classification. An operational parameter of the vehicle based on the environment classification is modified.

Some embodiments include a method of generating an environment reference model for positioning comprising: receiving multiple data sets representing a scanned environment including information about a type of sensor used and data for determining an absolute position of objects or feature points represented by the data sets; extracting one or more objects or feature points from each data set; determining a position of each object or feature point in a reference coordinate system; generating a three-dimensional vector representation of the scanned environment aligned with the reference coordinate system including representation of the objects or feature points at corresponding locations, creating links between the objects or feature points in the three dimensional vector model with an identified type of sensor by which they can be detected in the environment; and storing the three-dimensional vector model representation and the links in a retrievable manner.

An ECU captures an image of an imaging region around an own vehicle, and acquires image data, the imaging region being configured by a plurality of imaging areas. The ECU determines whether the object is present in the imaging areas, on the basis of detection results of an object present around the own vehicle. The ECU selects a target area to be displayed in an easy-to-see state from among the plurality of imaging areas, on the basis of determination results. The ECU reduces and corrects the image data of each imaging area such that an image of the target area is displayed in the easy-to-see state compared to an image of each imaging area to generate display image data.

Ray tracing and static obstacle maps can be used in the operation of a vehicle. Sensor data of at least a portion of an external environment of the vehicle can be acquired. A dynamic obstacle in the external environment of the vehicle can be detected based on the acquired sensor data. In response to detecting a dynamic obstacle, it can be determined whether a secondary occluded area is located behind the dynamic obstacle relative to a current location of the vehicle based on a static obstacle map. Responsive to determining that a secondary occluded area is located behind the dynamic obstacle relative to a current location of the vehicle based on a static obstacle map, a driving maneuver for the vehicle can be determined based on at least the dynamic obstacle and the secondary occluded area. The vehicle can be caused to implement the determined driving maneuver.

A vehicle analysis environment includes one or more display screens, such as a display screen wall or an array of display screens. While a vehicle is in the vehicle analysis environment, a vehicle analysis system renders and displays one or more vehicle sensor calibration targets and/or one or more simulated events on the one or more display screens. Vehicle sensors of the vehicle capture sensor data while in the vehicle analysis environment. The sensor data depict the vehicle sensor calibration targets and/or the simulated events that are displayed on the one or more display screens. The vehicle can output actions based on the simulated event and/or can calibrate its vehicle sensors based on the vehicle sensor calibration targets.

Provided herein is a system on a vehicle, the system comprising an active Doppler sensor; one or more processors; and a memory storing instructions that, when executed by the one or more processors, causes the system to perform: obtaining a Doppler signature from each of one or more entities; and determining one or more calibration parameters of the active Doppler sensor based on the Doppler signature from at least a portion of the one or more entities.

An electronic system for a vehicle includes: a first module including: a first circuit board having a predetermined form factor; a first module on the first circuit board and including a plurality of pins; a first electrical connector disposed on a first surface of the first circuit board and including a plurality of pins; and a plurality of electrical conductors connecting the pins of the first electrical connector with the pins of the first module, respectively; and a second module including: a second circuit board having the predetermined form factor; a second module on the second circuit board and including a plurality of pins; a second electrical connector disposed on a first surface of the second circuit board and including a plurality of pins, the second electrical connector coupled to the first electrical connector.