An apparatus for assisting driving of a host vehicle includes a camera mounted to the host vehicle and having a field of view outside of the host vehicle, the camera configured to obtain image data; and a controller configured to process the image data, identify at least one object obstructing the host vehicle's driving based on the image data, predict a collision with the at least one object, identify whether the host vehicle is moving forward or backward based on the image data and control a braking device of the host vehicle to brake the host vehicle depending on whether the host vehicle is moving forward or backward.

Determining yaw parameter(s) (e.g., at least one yaw rate) of an additional vehicle that is in addition to a vehicle being autonomously controlled, and adapting autonomous control of the vehicle based on the determined yaw parameter(s) of the additional vehicle. For example, autonomous steering, acceleration, and/or deceleration of the vehicle can be adapted based on a determined yaw rate of the additional vehicle. In many implementations, the yaw parameter(s) of the additional vehicle are determined based on data from a phase coherent Light Detection and Ranging (LIDAR) component of the vehicle, such as a phase coherent LIDAR monopulse component and/or a frequency-modulated continuous wave (FMCW) LIDAR component.

A method for distance control of a subject vehicle in relation to a front vehicle. The method includes setting, by an adaptive cruise control of the subject vehicle, an automatic distance control mode, wherein: a front object in front of the subject vehicle is detected by an environmental detection system of the subject vehicle, the front object is recognized as the front vehicle, and a distance to the front vehicle is regulated to an adaptive cruise control (ACC) target distance. The method further includes establishing that a safe following driving situation is present based on at least one criteria being met. The method additionally includes outputting, to a driver upon establishing that the safe following driving situation is present, a display signal, and setting, upon input of a confirmation signal by the driver, an automatic distance control platooning mode.

A device for blind spot detection of a vehicle, a method thereof and a steering wheel device are provided. The device includes a steering wheel, a lighting device, a blind spot detector, and a controller. The steering wheel comprises a configuration area including a fixed point, and the fixed point is represented as a virtual location of the vehicle. The lighting device includes a luminous light strip and a dimming driver. The luminous light strip assembled on the steering wheel surrounds the fixed point. The dimming driver controls lamp signals of the luminous light strip. The controller obtains a detection result of whether at least one object is approaching the vehicle, and controls the lamp signals to present a relative position between the vehicle and the at least one object and a degree of proximity between the vehicle and the at least one object according to the lamp signals.

A system configured to avoid a rear-cross traffic collision includes an obstacle detection unit detecting a position of an obstacle by receiving electromagnetic waves reflected off a reflection point of the obstacle; a direction estimation unit estimating a traveling direction of the obstacle on the basis of the position of the obstacle detected by the obstacle detection unit; and a collision determination unit determining possibility of a collision with the obstacle on the basis of the traveling direction of the obstacle estimated by the direction estimation unit.

A driving control apparatus for a vehicle is disclosed. The driving control apparatus includes: an object detection device configured to detect objects in the vicinity of the vehicle and generate information on the objects; a sensing unit configured to detect a state of the vehicle and generate vehicle state information; and a processor configured to: based on the vehicle state information and the information on the objects, generate information on collision with a first object out of the objects, and based on the information on the collision, generate a control signal for at least one of steering, partial braking, and partial driving of the vehicle and provide the generated control signal so as to control operation of the vehicle after the collision through at least one of a steering control action, a partial braking control action, and a partial driving control action.

An object detection device detects an object moving in the area surrounding an own object. The object detection device includes: an information obtainment unit which obtains an object speed value that is at least one of a speed and an acceleration of the object in a lateral direction which is orthogonal to a predetermined direction of the area surrounding the own object; and an upper limit setting unit which sets an upper limit of the object speed value on the basis of angle information that is the relationship indicating an angle of a moving direction of the object with respect to the predetermined direction.

When a vehicle heads from a first road toward a second road which at least partially intersects with the first road while traveling, other vehicle heads from the second road to a first road side, and a future trajectory in which the vehicle travels and a future trajectory in which the other vehicle travels intersect with each other, a vehicle control device determines whether to cause the vehicle to pass through an intersection area in which the first road and the second road intersect with each other with priority over the other vehicle on the basis of the state of the vehicle and the future position of the other vehicle and controls the vehicle on the basis of a result of the determination.

Image data are input to a machine learning program. The machine learning program is trained with a virtual boundary model based on a distance between a host vehicle and a target object and a loss function based on a real-world physical model. An identification of a threat object is output from the machine learning program. A subsystem of the host vehicle is actuated based on the identification of the threat object.

A driving control apparatus and method may include collecting driving information related to a subject vehicle, wherein the driving information related to the subject vehicle includes a driving lane and a vehicle width of the subject vehicle, and driving information related to another vehicle, wherein the driving information related to another vehicle includes a driving lane and a vehicle width of at least one another vehicle around the subject vehicle, generating one or more imaginary lines indicating positions in a corresponding driving lane of the another vehicle based on the driving information related to the another vehicle, determining a deflection value by which the subject vehicle needs to be deflected in the driving lane of the subject vehicle based on the imaginary line, and determining a driving path of the subject vehicle based on the determined deflection value.