A driving support Electronic Control Unit (ECU) initializes a target trajectory calculation parameter at a start of Lane Change Assist Control (LCA), calculates, based on the target trajectory calculation parameter, a target trajectory function representing a target lateral position in accordance with an elapsed time from the start of LCA; and calculates a target control amount according to the target trajectory function. When it is determined that the own vehicle has crossed a boundary white line, the driving support ECU again initializes the target trajectory calculation parameter, and calculate the target trajectory function based on the target trajectory calculation parameter.

Radar sensor, having an antenna assembly and a monolithic microwave integrated circuit that is arranged on a circuit board of the radar sensor and comprises at least one antenna connection that is to be connected to the antenna assembly, in particular is implemented in a ball grid, provides radar signals to be emitted, which can be generated by the microwave circuit, or accepts received radar signals from the antenna assembly, the connection of the antenna connection to the antenna assembly being formed at least in part by a waveguide, wherein, for connecting the at least one antenna connection to the waveguide designed as a wave duct, the circuit board comprises, at the position of the antenna connection, a through-opening leading to the side of the circuit board opposite the microwave circuit, through which the antenna connection is connected to a radiation element projecting into the waveguide arranged on the opposite side of the circuit board at the position of the antenna connection.

The present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle by comparing current image feature data to previously classified image features.

The present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle by comparing current image data to previously classified image data.

The present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle by comparing current image feature data to previously classified image features.

The present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle by comparing current image data to previously classified image data.

A driving support Electronic Control Unit (ECU) initializes a target trajectory calculation parameter at a start of Lane Change Assist Control (LCA), calculates, based on the target trajectory calculation parameter, a target trajectory function representing a target lateral position in accordance with an elapsed time from the start of LCA; and calculates a target control amount according to the target trajectory function. When it is determined that the own vehicle has crossed a boundary white line, the driving support ECU again initializes the target trajectory calculation parameter, and calculate the target trajectory function based on the target trajectory calculation parameter.

The present disclosure is directed to apparatuses, systems and methods for automatically compressing digital image data. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically compressing digital image data that is representative of a series of digital images.

According to various aspects, a vehicle may include: an external structure; an assembly configured to allow a movement of at least a part of the assembly relative to the external structure at least from a first position to a second position, wherein the assembly protrudes from the external structure with a first distance in the first position and with a second distance less than the first distance in the second position; one or more sensors configured to receive obstacle information associated with one or more obstacles in a vicinity of the vehicle; one or more processors configured to determine a collision threat to the assembly based on the obstacle information, and trigger the movement of at least the part of the assembly from the first position into the second position in the case that the collision threat is determined.

In accordance with one embodiment, a braking-system suitable for use on an automated vehicle is provided. The braking-system includes a ranging-sensor, a braking-actuator, and a controller in communication with the ranging-sensor and the braking-actuator. The ranging-sensor is used to detect a range-rate, a range, and a direction of an object proximate to a host-vehicle when the object resides in a field-of-view of the ranging-sensor. The field-of-view defines a conflict-zone and a conflict-buffer separate from the conflict-zone. The braking-actuator is used to control movement of the host-vehicle. The controller determines a trail of the object based on the range and the direction. The controller further classifies the object as slow-moving based on a rate-threshold. The controller further determines a tangent-vector based on the trail. The controller activates the braking-actuator when the object is slow-moving, the object is detected within the conflict-buffer, and the tangent-vector intersects the conflict-zone.