Abstract: An apparatus for a motor vehicle driver assistance system for an ego vehicle is provided. The apparatus implements a state estimator configured to use a first state of the ego vehicle to calculate a subsequent second state of the ego vehicle, wherein calculating the second state from the first state includes a prediction element and an update element, wherein calculating the second state from the first state includes using an artificial neural network (“ANN”).

Abstract: A vehicle radar system (3) and method including a first and second radar sensor arrangement (4a, 4b). Each radar sensor arrangement (4a, 4b) includes at least two transmitter antenna devices (10a1, 10a2) and at least two receiver antenna devices (13a1, 13a2, 13a3, 13a4), where each receiver antenna device (13a1, 13a2, 13a3, 13a4) has a corresponding boresight extension (46a, 46b) that is perpendicular to an antenna plane (57). Each receiver antenna device (13a1, 13a2, 13a3, 13a4) has a corresponding antenna radiation pattern (47a, 47b) that has a lower gain (48a, 48b) in its boresight extension (46a, 46b) than at a certain corresponding first maximum gain azimuth angle (?1a, ?1b) where there is a first maximum gain (49a, 49b). Each radar sensor arrangement (4a, 4b) is mounted such that each first maximum gain (49a, 49b) is directed along a corresponding first maximum gain extension (51a, 51b), such that an overlap part (56) of the antenna radiation patterns (47a, 47b) is formed.

Abstract: A vision system (10) for a motor vehicle includes a stereo imaging apparatus (11) adapted to capture images from a surrounding of the motor vehicle, a disparity calculation block (17) adapted to calculate a stereo disparity of left/right images captured by the stereo imaging apparatus (11), and a processing device (14) adapted to perform image processing of images captured by the imaging apparatus (11). The vision system is adapted to perform time sharing of the disparity calculation block (17) between the stereo disparity calculation and calculation of a one-dimensional optical flow of captured images in a horizontal direction only.

Abstract: An apparatus for a motor vehicle driver assistance system is provided. The apparatus is configured to optimise object clusters, where each object cluster includes a sequence of position measurements for at least one object in the vicinity of the vehicle. Initially, in a pre-clustering phase, the assignment of the measured object positions to the object clusters may be based on the relative proximity of the measured object positions. The apparatus identifies a rogue object cluster on the basis of a first diagnostic, and a rogue object track from the measurements within the rogue object cluster. The position measurements from the rogue object track are removed from the clusters, and remaining position measurements in the rogue object cluster are reassigned to the other object clusters. The rogue object cluster is removed. Thus the object clusters are optimised.

Abstract: Techniques for controlling a protection apparatus are provided. An example method includes detecting an offset collision or diagonal collision, and activating a suitable protection apparatus for protecting the side or head of a passenger at a timing in accordance with the degree of collision. An example controller may include a level calculation part for calculating a level of a front face collision, a ?Voffset calculation part for making an offset adjustment of a speed (?V), and a determination part for determining an offset collision or diagonal collision based on the level of the front face collision and the ?Voffset.

Abstract: A driver assistance system for an ego vehicle, and a method for a driver assistance system is provided. The system is configured to refine a coarse geolocation method based on the detection of the static features located in the vicinity of the ego vehicle. The system performs at least one measurement of the visual appearance of each of at least one static feature located in the vicinity of the ego vehicle. Using the at least one measurement, a position of the ego vehicle relative to the static feature is calculated. The real world position of the static feature is identified. The position of the ego vehicle relative to the static feature is calculated, which is, in turn, used to calculate a static feature measurement of the vehicle location. The coarse geolocation measurement and the the static feature measurement are combined to form a fine geolocation position. By combining the measurements, a more accurate location of the ego vehicle can be determined.

Abstract: A vehicle radar system (3) which, for each one of a plurality of radar cycles, is arranged to, provide a measured azimuth angle (?m) and radial velocity (vdm) for a first plurality of detections (9, 20). For each one of the plurality of radar cycles, the radar system (3) is arranged to select one of these detections for each one of two velocity components (vx, vy) in a set of components (vx, vy, ax, ay; a) to be determined; select one detection from a second plurality of detections (9, 20) for each one of at least one corresponding acceleration component (ax, ay; a); calculate the components (vx, vy, ax, ay; a) for the selected detections; determine a calculated radial velocity (vdc) for each one of at least a part of the other detections in the first plurality of detections (9, 20) using the calculated components (vx, vy, ax, ay; a); determine an error between each calculated and measured radial velocity (vdc, vdm); and determine the number of inliers.

Abstract: A vehicle environment detection system (40) in an ego vehicle (1), including a sensor arrangement (4) and a main control unit (8) is arranged to detect and track at least one oncoming vehicle (9), and to determine whether the ego vehicle (1) has entered a curve (17). The main control unit (8) is arranged to determine a common curve (12) with a radius (R), along which common curve (12) the ego vehicle (1) is assumed to travel, determine a measured oncome direction (13, 13?) of the oncoming vehicle (9) on the common curve (16), corresponding to an outcome angle (?track), determine a difference angle (?) between the measured oncome direction (13, 13?) and an oncome direction (13) corresponding to if the oncoming vehicle (9) would be moving along the common curve (12), compare the difference angle (?) with a threshold angle (?max), and to determine that the oncoming vehicle (9) is crossing if the difference angle (?) exceeds the threshold angle (?max).

Abstract: A vehicle environment detection system (40) in an ego vehicle (1), including a sensor arrangement (4) and a main control unit (8) is arranged to detect and track at least one oncoming vehicle (9), and to determine whether the ego vehicle (1) has entered a curve (17). When this is the case. The main control unit (8) is arranged to, determine an ego direction (21) along which the ego vehicle (1) travels with a corresponding ego direction angle (?ego) with respect to a predetermined axis (xglob), determine a measured oncoming direction (18) of the tracked oncoming vehicle (9) with a corresponding oncoming angle (?track, glob) with respect to the predetermined axis (xglob) during a plurality of radar cycles, determine a difference angle (?) between the measured oncoming direction (18) and the ego direction (21), and compare the difference angle (?) with a threshold angle (?max), and to determine that the oncoming vehicle (9) is crossing if the difference angle (?) exceeds the threshold angle (?max).

Abstract: A vision system for detecting free space in front of a motor vehicle includes a mono imaging apparatus (11) adapted to capture images (30) from the surrounding of a motor vehicle, and an electronic processing device (14) adapted to perform image processing of images (30) captured by the mono imaging apparatus (11) in order to detect objects in the surrounding of a motor vehicle. The electronic processing device (14) is adapted to calculate a horizontal component of the optical flow (31), and to determine transitions (33, 35) between regions of essentially constant horizontal optical flow and regions of essentially non-constant horizontal optical flow.