A driving assist apparatus for a vehicle includes a front-side-environment recognition camera, a front-side-environment recognition sensor, and a control device. The front-side-environment recognition camera is configured to recognize a driving environment ahead of the vehicle. The front-side-environment recognition sensor is configured to recognize the driving environment ahead of the vehicle. In a case where image recognition of the front-side-environment recognition camera for a leading vehicle for adaptive cruise control has deteriorated during execution of the adaptive cruise control, the control device is configured to continue executing the adaptive cruise control based on a distance from the vehicle to the leading vehicle obtained by the front-side-environment recognition sensor.

A method for operating a parking assistance function of a motor vehicle is described, wherein the motor vehicle comprises at least one sensor for detecting the road surrounding the motor vehicle. The method includes the following steps: Finding and specifying a free parking space; Determining a trajectory for parking the motor vehicle in the parking space and a sequence of an at least partially automated parking process; Determining at least one outer boundary line of the road surface required for parking along the identified trajectory; Detecting at least one road user approaching the determined outer boundary line on the road by means of at least one sensor; Determining the distance of the road user approaching the determined outer boundary line from the outer boundary line; if the determined distance falls below a specified first threshold, outputting a warning signal to the approaching road user.

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.

The present disclosure relates to an information processing apparatus, an information processing method, and a program that allow for appropriately pulling over to a safe road shoulder when an emergency occurs during automated driving. On the basis of distance information from a depth sensor or the like, a travelable region available for a vehicle to travel is set like an occupancy map, and image attribute information is generated from an image by semantic segmentation. On the basis of the image attribute information, an evacuation space is set in the travelable region in accordance with the situation of the road surface of the travelable region, and thus an evacuation space map is created. The present disclosure can be applied to a mobile object.

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.

Disclosed is a method for a vehicle transmitting a signal in a wireless communication system. The method may comprise: receiving information on a road environment; driving a vehicle along a selected path on the basis of the information on the road environment; and, on the basis of satisfying a predetermined condition, transmitting a message for reserving a lane change to a specific lane among at least one lane included in the path. In addition, the message may include information on a virtual vehicle corresponding to the vehicle when in the specific lane. In addition, whether or not the predetermined condition is satisfied may be determined on the basis of: i) the right of way of the vehicle with respect to the lane changing; or ii) a back-off counter.

A vehicle position estimation device includes an external information acquisition unit, a vehicle parameter acquisition unit, a map data acquisition unit, a lane change determination unit, and a position estimation unit. The external information acquisition unit acquires external information. The vehicle parameter acquisition unit acquires a vehicle parameter related to traveling. The map data acquisition unit acquires map data. The lane change determination unit determines whether the vehicle is changing lanes. The position estimation unit estimates a self-position of the vehicle on a map. When the lane change determination unit determines that the vehicle is changing lanes, the position estimation unit estimates the self-position using dead reckoning. When the lane change determination unit determines that the vehicle is not changing lanes, the position estimation unit estimates the self-position based on the external information and the map data.

Embodiments provide extracting information respectively corresponding to predetermined dimensions from environment information corresponding to an unmanned driving environment. In some embodiments, the information respectively corresponding to the dimensions is input into an identification model to obtain a driving feature. Then a risk value representing a driving risk degree of an unmanned device is determined, and a maximum variation of the information corresponding to at least one dimension is determined when a variation of the driving feature is less than a predetermined threshold. A maximum variation of the information corresponding to each dimension is used as a risk contribution feature. A variation representative value of the information corresponding to each dimension is determined from the risk contribution feature. According to the variation representative values of the dimensions, a driving risk factor corresponding to the risk value is determined based on the driving feature.

One or more processors may be configured to determine one or more prospective routes of an ego vehicle being at least partially controlled by a human driver; receive first sensor data, representing one or more attributes of a second vehicle; determine a danger probability of the one or more prospective routes of the first vehicle using the at least the one or more attributes of the second vehicle from the first sensor data; and if each of the one or more prospective routes of the first vehicle has a danger probability outside of a predetermined range, send a signal representing a safety intervention. Whenever a safety intervention signal is sent, the one or more processors may be configured to increment or decrement a counter.

Embodiments of this application provides example methods, media, and apparatuses for predicting moving trajectory of a target object. One example method includes obtaining a candidate moving trajectory, where the candidate moving trajectory is a motion trajectory that is of the target object in future period and that is obtained by using a prediction method, and the target object is in a sensing range of an ego vehicle. Environmental information is obtained within the sensing range. A constraint barrier is generated based on the environmental information, where the constraint barrier is used to indicate an area through which the target object is constrained to pass. The candidate moving trajectory is processed based on the constraint barrier.