A method for providing a positive decision signal for a vehicle which is about to perform a traffic scenario action. The method includes receiving information about at least one surrounding road user, which information is indicative of distance to the surrounding road user with respect to the vehicle and at least one of speed and acceleration of the surrounding road user; calculating a value based on the received information; providing the positive decision signal to perform the traffic scenario action when the calculated value is fulfilling a predetermined condition. The value is calculated based on an assumption that the surrounding road user will react on the traffic scenario action by changing its acceleration.

A parking assist system includes: an imaging device configured to capture an image of a surrounding of a vehicle; a display device configured to display a surrounding image of the vehicle based on the image captured by the imaging device; and a control device configured to control a display of the display device based on the surrounding image and to calculate a trajectory of the vehicle from a current position to a target position. In a case where the trajectory includes a switching position for steering the vehicle and changing a moving direction thereof and the vehicle is moving toward the switching position, the control device causes the display device to superimpose the switching position on the surrounding image and to hide at least a first part of the trajectory, the first part connecting the switching position and the target position.

A vehicle control device is mountable on a vehicle. The vehicle control device includes: a processor; and a memory storing instructions that, when executed by the processor, cause the vehicle control device to perform operations. The operations includes: acquiring detection information obtained by detecting an obstacle around the vehicle; performing collision determination of evaluating a possibility of collision with the obstacle, generating, based on the detection information, information on an approaching object that is an obstacle approaching the vehicle and information on a detection point group that is a set of detection points indicating an obstacle that does not move; and excluding the approaching object from collision determination in a case in which the detection point group has a shielding effect of shielding the vehicle from the approaching object. The shielding effect is evaluated by using a gap threshold that is set based on a vehicle width.

A method for supporting a user of a first vehicle to follow a second vehicle includes obtaining a picture, by a camera, of at least a part of a surrounding of the first vehicle, detecting vehicles in the obtained picture, displaying a representation of the detected vehicles on a user interface to the user, obtaining input from the user from the user interface of which of the detected vehicles that is the second vehicle and that the user would like to follow, obtaining, via the camera, at least one identification data of the second vehicle, tracking the position of the second vehicle, and transmitting the position of the second vehicle to a navigation system of the first vehicle.

The present disclosure relates to a method and system for integrated path planning and path tracking control of an autonomous vehicle. The method includes: obtaining five input control variables and eleven system state variables of an autonomous vehicle at current time; constructing a vehicle path planning-tracking integrated state model according to the obtained variables at the current time; enveloping external contours of two autonomous vehicles using elliptical envelope curves to determine elliptical vehicle envelope curves of the two autonomous vehicles, respectively; determining time to collision (TTC) between the vehicles according to elliptical vehicle envelope curves and vehicle driving states; establishing an objective function of a model prediction controller (MPC) according to the model; and solving the objective function based on the TTC, and determining input control variables to the MPC at the next time. Autonomous vehicle collision avoidance can be achieved according to the present disclosure.

Provided is a driving assistance apparatus that assists driving of a vehicle. The driving assistance apparatus includes: a training data generator that stores a traveling route traveled by the vehicle according to a driving operation of a user in a training traveling mode, and generates training data for a target route based on the traveling route. The training data generator generates the target route by connecting, for example, between a first point and a second point on the traveling route, in a case where a difference in orientation of the vehicle at the first point and the second point during training traveling is less than a first threshold and distance between the vehicle at the first point and the vehicle at the second point during the training traveling is less than a second threshold.

While operating a host vehicle in a lane, a target vehicle is detected entering the lane in front of the vehicle. A trajectory of the target vehicle is predicted based on sensor data. Upon determining that the target vehicle will pass through the lane based on the predicted trajectory, the host vehicle is operated based on determining a presence or an absence of a lead vehicle. Upon determining that the target vehicle will remain in the lane based on the predicted trajectory, the host vehicle is operated with the target vehicle as the lead vehicle.

While operating a vehicle on a travel path, a width of the travel path is determined based on a map. Upon detecting a presence or an absence of a target vehicle in the travel path, a lateral position for the vehicle on the travel path is determined based on the width of the travel path and the presence or absence of the target vehicle. The vehicle is controlled to operate according to the determined lateral position on the travel path and a speed of the vehicle that is based on the determined lateral position on the travel path.

A vehicle exterior environment recognition apparatus includes a travel path derivation unit, a speed derivation unit, and a follow-up controller. The travel path derivation unit estimates an own-vehicle travel path and derives a target-vehicle travel path that contains a point on a target vehicle and forms a parallel curve to the own-vehicle travel path. The speed derivation unit derives a target-vehicle speed vector. The follow-up controller makes a follow-up control based on the target-vehicle speed vector on the condition that an angle formed by the target-vehicle speed vector and a tangential line to the target-vehicle travel path at the point on the target vehicle falls within a predetermined angular range, and makes the follow-up control based on a tangential speed component of the target-vehicle speed vector on the condition that the angle falls out of the angular range.

A vehicle is provided to avoid a collision with a target object located in front of the vehicle by predicting an expected traveling path of the target object. The vehicle also predicts the possibility of a collision with the target object.