A method for reducing a risk of collision with an obscured object. The method includes detecting, by a detector, the object in proximity of the detector, and determining, by the detector, object data of the detected object in response to the detection. The method further includes determining, by the detector, any vehicle in motion in a direction towards an area where the detected object is or may be present, and transmitting, by the detector, the determined object data of the detected object to the vehicle. The method furthermore includes receiving, by the vehicle, the transmitted object data, processing, by the vehicle, the received object data to assess a collision risk based on a predicted route of the vehicle, and mitigating the collision risk, in the vehicle, based on the processed object data when the collision risk has been assessed.

Disclosed is a vehicle control method, including: obtaining a first velocity planned for an intelligent vehicle to travel in a first area; and obtaining a second velocity planned for the vehicle to travel in the first area, where the second velocity is obtained based on a collision potential energy, the first velocity and the second velocity each include a direction and a magnitude, and the first velocity, the second velocity, and a risk of a collision between the vehicle and a surrounding obstacle are used to determine an optimal velocity of the vehicle, so that the vehicle can effectively avoid the obstacle, thereby improving traveling safety of the vehicle. Also disclosed are a vehicle control apparatus, a vehicle controller, and a vehicle.

A vehicle for performing avoidance control of the vehicle according to a position and a relative speed of an object, may include a sensing device mounted to the vehicle and having a field of view in front of the vehicle and a field of view in a lateral side of the vehicle, the sensing device configured to obtain object data related to the object; a dynamics sensor configured to detect a motion of the vehicle and obtain motion data based on the motion of the vehicle; and a controller including a processor configured to process the object data and the motion data.

An object-tracking method includes: using the velocity of a track for tracking an object, generated from a point cloud related to the object, in a current recognition period (T) to obtain a current velocity-based heading angle of the track; accumulating scores associated with information about the current velocity-based heading angle and incorporating the accumulated scores into a heading history having regions sectioned for respective heading angles of the track; obtaining a history-based heading angle of the track using the heading history; and correcting the history-based heading angle using information about the shape of the track and determining the result of correction to be a final heading angle in the current recognition period (T).

A method of autonomous driving for low-speed or zero-speed maneuvering of a motor vehicle includes modifying the orientation of the steerable wheels of the vehicle while the speed of the vehicle is zero or substantially zero, or less than or equal to a threshold, in particular a threshold equal to 1 km/h.

A method and system for target detection of a vehicle is proposed. In the method and system, when the vehicle is turning, a warning signal according to a risk level of collision is generated at the right timing as a risk level of collision between the host vehicle and the other vehicle behind the host vehicle may be accurately identified by correcting a driving path of the host vehicle and position of the other vehicle on the basis of a driving state of the host vehicle.

Disclosed are a track mergence module and a method by which track deletion conditions are set to be varied depending on various situations and a track corresponding to the set track deletion conditions is deleted. The track mergence module includes a track deletion condition generation and storage unit, a phenomenon determination unit and a track mergence unit. A track to be deleted may be accurately deleted by generating the track deletion conditions so as to adaptively correspond to the performance of a sensor and various situations in which a host vehicle is placed, thereby being capable of erroneous braking of the autonomously driving host vehicle.

A control system is suitable for use in a motor vehicle and is configured and intended for using information concerning objects and/or driving-related information about another motor vehicle in order to distinguish real objects in the surroundings of the motor vehicle from erroneously detected objects, based on surroundings data that are obtained from at least one surroundings sensor situated on the motor vehicle and provided to the control system. Based on these surroundings data, an object in the surroundings of the motor vehicle is detected, and a distance and/or a relative speed and/or an angle between the motor vehicle and the object are/is determined. The object is then classified as an actually existing object or as an erroneously detected object, based on the determined distance and/or based on the determined relative speed and/or based on the determined angle.

A behavior prediction method includes: determining a position of a host vehicle; determining a position of another vehicle in a second travel lane, the second travel lane being an opposite lane to a first travel lane in which the host vehicle travels; detecting an intersecting passage intersecting the second travel lane at a position ahead of the host vehicle; and determining whether or not the another vehicle is located within a predetermined range from an intersection position of the intersecting passage and the second travel lane to a point away from the intersection position by a predetermined distance in an opposite direction to a traveling direction of a vehicle in the second travel lane and the another vehicle is in either state of a stopped state and a decelerated state to predict that there is a probability that a mobile unit enters the first travel lane from the intersecting passage.

Lane level localization techniques for a vehicle utilize a plurality of perception sensor systems each configured to perceive a position of the vehicle relative to its environment, a map system configured to maintain map data that includes lane lines, and a controller configured to detect a position of the vehicle and a first set of lane lines using the plurality of perception sensors, detect a second set of lane lines using the position of the vehicle and the map data, obtain an aligned set of lane lines based on the first and second sets of lane lines, and use the aligned set of lane lines for an autonomous driving feature of the vehicle.