A parking assistance control device detects a parkable area, where a host vehicle can be parked, based on target information, causes the vehicle to move from the initial position, which is the vehicle's position when the parkable area is detected, to the parkable area by controlling a driving device, braking device, and steering device and, when the target information indicates that a stopper is installed in the parkable area, causes the vehicle to stop with its position and direction with respect to the stopper matching a predetermined position and direction. The parking assistance control device causes the vehicle to stop with the distance between the vehicle's predetermined first reference point and the stopper matching a first predetermined value so that the vehicle is forward-parked in the state where the front end of a part, provided on the vehicle's front side and lower than the stopper, is separated from the stopper.

A surrounding situation information acquisition device acquires surrounding situation information of a vehicle. A steering angle sensor detects a steering angle and a steering direction of the vehicle. A steering assist controller executes traveling control involving steering assist control based on information output from the surrounding situation information acquisition device and information output from the steering angle sensor. The steering assist controller recognizes, based on the information output from the surrounding situation information acquisition device, an oncoming vehicle in an oncoming lane adjacent to a traveling lane of the vehicle and an avoidance target on a road shoulder side of the traveling lane of the vehicle, estimates an avoidance priority level of the oncoming vehicle and an avoidance priority level of the avoidance target, and sets a new target lane keeping traveling path of the vehicle based on the avoidance priority levels.

The disclosure relates to a vehicle velocity control method. The method includes: determining, by an onboard sensor, drivable distances in different directions in front of a current vehicle, and obtaining, at least based on types of targets in the different directions, an area of a drivable space in front of the current vehicle; determining, based on the area of the drivable space and a current vehicle velocity, a result of a safety degree in a current driving scenario; and controlling the vehicle velocity of the current vehicle based on the result of the safety degree. The disclosure further relates to a vehicle control device, a computer storage medium, and a vehicle.

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.

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.

A method for inertia drive control is provided. The method includes performing advanced inertia drive control by an inertia drive controller. The controller detects a speed reduction event during road driving of a vehicle, lane division together with road type division for a road, and performs inertia drive control guide and the inertia drive control based on drive conditions of lane change and lane maintenance.

An apparatus for controlling autonomous parking and method thereof are provided. The apparatus for controlling autonomous parking according to embodiments of the present disclosure includes a sensor to detect surrounding information of a host vehicle; a transceiver to communicate with a control server to receive space information in a parking lot; a display to display a parking situation; and a controller communicatively connected to the sensor, the transceiver, and the display and configured to detect available parking spaces based on a detection result from the sensor and space information from the control server and perform autonomous parking by setting a position selected by a user's drag operation to a target parking space among the detected available parking spaces.

The present disclosure provides a vehicle behavior prediction method and apparatus, an electronic device, and a computer-readable storage medium, which relates to the field of intelligent driving. The method includes: determining a target traffic light corresponding to t a target vehicle a current intersection; determining a neighboring traffic light corresponding to the target traffic light and the indication status of the neighboring traffic light according to the target traffic light, the indication status of the target traffic light and a traffic light status mapping relationship table; acquiring a position of an obstacle vehicle and predicting each possible travel path of the obstacle vehicle, and determining a traffic light corresponding to each possible travel path; and determining a final possible travel path of the obstacle vehicle according to each possible travel path and the indication status of the traffic light corresponding to each possible travel path.

A motion planner performs motion planning with collision assessment, using a motion planning lattice that represents configuration states of a primary agent (e.g., autonomous vehicle) as nodes and transitions between states as edges. The system may assign cost values to edges, the cost values representing probability or likelihood of collision for the corresponding transition. The cost values may additionally or alternatively represent a severity of collision, for example generated via a parametric function with two or more parameters and one or more weights. A primary agent and/or dynamic obstacles may be represented as respective oriented bounding boxes. Some obstacles (e.g., road markings, edge of road) may be represented as curves. A trajectory of a primary agent and/or dynamic obstacle may be represented by respective sets of fitted polynomial functions, edges on the planning graph, which represent transitions in states of the primary agent, the system sets value representing a probability of collision, and optionally representing a severity of the collision. The system then causes the actuator system of the primary agent to implement a motion plan with the applicable identified path based at least in part on the optimization.

A method of controlling an electrified vehicle to prevent a collision thereof includes: determining whether an accelerator pedal is erroneously operated in the situation in which an obstacle is detected to be present in a traveling path; and when it is determined that the accelerator pedal is erroneously operated, performing braking control such that at least one of hydraulic braking or regenerative braking is selectively performed in a plurality of braking sections determined based on a current vehicle speed and a distance to the obstacle.