Disclosed is an apparatus for assisting driving of a vehicle including a camera installed in the vehicle to have a front field of view of the vehicle and obtain image data, and a controller to process the image data. The controller is configured to identify objects surrounding the vehicle and lanes defining a road on which the vehicle travels based on the processing of the image data, identify a lane in which the vehicle travels based on relative positions of the surrounding objects, and control the vehicle to change the lane based on a distance from the road on which the vehicle is traveling to an additional lane for entering an exit road.

A travel assistance method is executed by a processor and comprises: acquiring, from a device for storing map information, information on static traveling path boundaries between a traveling path of a subject vehicle and other than the traveling path; acquiring, from a sensor for detecting surrounding environment of the subject vehicle, information on dynamic traveling path boundaries different from the static traveling path boundaries; generating, based on the information on the static traveling path boundaries, a static traveling path on which the subject vehicle can travel; generating, based on the information on the static traveling path and the dynamic traveling path boundaries, a dynamic traveling path which is shorter than the static traveling path and corresponds to the surrounding environment; and controlling the subject to travel along a traveling path including the static traveling path and the dynamic traveling path.

Provided is an apparatus for assisting in driving a vehicle, the apparatus including: a camera installed in the vehicle to have a front field of view and configured to acquire image data; and a controller configured to process the image data, wherein the controller is configured to: detect a vehicle parked in a direction opposite to a driving direction of the vehicle, based on the processed image data, and when the parked vehicle is detected, generate a control signal for providing a notification to a driver.

A detection method and a device based on a laser radar, and a computer readable storage medium are disclosed. The detection method includes: obtaining scanning data of the laser radar (S101); performing algorithm splitting on a feature algorithm for detection based on the scanning data to obtain at least one sub-algorithm capable of parallel processing in the feature algorithm (S102); and performing heterogeneous acceleration for the at least one sub-algorithm to process the scanning data and to obtain a processing result; and obtaining a detected position of an obstacle and a detected drivable area based on the processing result (S103).

A navigation system for a host vehicle may include a processing device including circuitry and a memory storing instructions that when executed by the circuitry cause the at least one processing device to receive images acquired by a camera representative of an environment of the host vehicle, and analyze the images to identify a double merge scenario including a first flow of traffic and a second flows of traffic in a same direction that merge to form a merged flow of traffic in a merged lane. The instructions that when executed by the circuitry may further cause the processing device to cause a navigational change in the host vehicle based on a trajectory of a first target vehicle in the first flow of traffic and a trajectory of a second target vehicle in the second flow of traffic.

A method for supplying data for an at least partially automated vehicle. The method including: detecting the sensor data of an infrastructure; fusing the sensor data to form an environment model; wireless transmission of the environment model data to the at least partially automated vehicle; and wireless transmission of context data, relating to a location of the at least partially automated vehicle, to the at least partially automated vehicle, it being possible to evaluate the environment model data in a defined manner with the aid of the context data.

The invention relates to a method for automated calibration of sensors of a vehicle, wherein at least one first passive optical sensor and at least one second active optical sensor are calibrated by a calibration unit based on a matching spatial orientation of recognised environmental features in transformed sensor data of the first sensor and the sensor data captured by the second sensor.

A controller causes a host vehicle to decelerate when a velocity of an oncoming vehicle corresponding to a position of the oncoming vehicle distant from a stationary object by a predetermined distance is greater than or equal to a velocity threshold corresponding to the position of the oncoming vehicle distant from the stationary object by the predetermined distance in a case in which a passing position is present within a predetermined region, and causes the host vehicle to keep the velocity or accelerate when the velocity of the oncoming vehicle corresponding to the position of the oncoming vehicle distant from the stationary object by the predetermined distance is less than the velocity threshold corresponding to the position of the oncoming vehicle distant from the stationary object by the predetermined distance in the case in which the passing position is present within the region.

A braking control system includes obstacle detection means for detecting an obstacle ahead of a vehicle, first collision determination means for determining whether the vehicle would collide with the obstacle ahead of the vehicle, following vehicle detection means for detecting a following vehicle traveling behind the vehicle, information acquisition means for acquiring a maximum deceleration set in the following vehicle, second collision determination means for determining whether the following vehicle would collide with the vehicle based on the maximum deceleration, and braking control means for controlling braking means of the vehicle so that an absolute value of a deceleration of the vehicle does not exceed an absolute value of the maximum deceleration of the following vehicle when the first collision determination means determines that the vehicle would collide with the obstacle and the second collision determination means determines that the following vehicle would collide with the vehicle.

A computer-implemented method of estimating a 6D pose and shape of one or more objects from a 2D image, comprises the steps of: detecting, within the 2D image, one or more 2D regions of interest, each 2D region of interest containing a corresponding object among the one of more objects; cropping out a corresponding pixel value array, coordinate tensor , and feature map for each 2D region of interest; concatenating the corresponding pixel value array, coordinate tensor, and feature map for each 2D region of interest; and inferring, for each 2D region of interest, a 4D quaternion describing a rotation of the corresponding object in the 3D rotation group, a 2D centroid, which is a projection of a 3D translation of the corresponding object onto a plane of the 2D image given a camera matrix associated to the 2D, image, a distance from a viewpoint of the 2D image to the corresponding object a size and a class-specific latent shape vector of the corresponding object.