A vehicle control device includes a recognizer configured to recognize situations around a vehicle; a determiner configured to determine any of lanes included in a road on which the vehicle travels as a reference lane; and a driving controller configured to control at least one of a speed and steering of the vehicle according to the situations recognized by the recognizer and the reference lane determined by the determiner, wherein the determiner is configured to, when the vehicle moves from a first road to a second road different from the first road, among a plurality of lanes included in the first road, according to a relative position of a first reference lane determined at a time before the vehicle moves to the second road with respect to the plurality of lanes, determine a second reference lane on the second road.

A method for determining an avoidance path of a motor vehicle includes the steps of:—acquiring data relating to an obstacle located in the surroundings of the motor vehicle by means of a detection system,—determining a final position to be reached according to the position of the obstacle and an initial position of the motor vehicle,—calculating a theoretical impact position located between the initial position and the final position, and—developing the avoidance path such that the motor vehicle passes through the initial position and the final position and avoids the theoretical impact position around the outside.

A travel route generation device (4) includes a travel route acquisition unit (4) configured to acquire position information (Pc) about a travel route (H) for a moving object (M) to perform autonomous travel or remotely controlled travel, a surrounding environment information acquisition unit (22) configured to acquire surrounding environment information, a dangerous location detection unit (23) configured to detect dangerous locations (Pd1 to Pd3) where there is a risk of an accident from the surrounding environment information, and an information processing unit (24) configured to add dangerous location information including first information indicating the dangerous locations (Pd1 to Pd3) to the position information (Pc) corresponding to the dangerous locations (Pd1 to Pd3).

A system comprises a computer having a processor and a memory, the memory storing instructions executable by the processor to access sensor data of a first sensor of a vehicle while an adaptive cruise control feature of the vehicle is active, detect, based on the sensor data of the first sensor, a stationary object located along a path of travel of the vehicle, wherein the stationary object is located outside of a range of a second sensor of the vehicle, determine a presence of an intersection within a threshold distance of the stationary object that is along the path of travel of the vehicle, and responsive to a determination that the stationary object is a stopped vehicle of the intersection, adjust, by the adaptive cruise control feature, the speed of the vehicle.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for predicting near-curb driving behavior. One of the methods includes obtaining agent trajectory data for an agent in an environment, the agent trajectory data comprising a current location and current values for a predetermined set of motion parameters of the agent; processing a model input generated from the agent trajectory data using a trained machine learning model to generate a model output comprising a prediction of whether the agent will exhibit near-curb driving behavior within a predetermined timeframe, wherein an agent exhibits near-curb driving behavior when the agent operates within a particular distance of an edge of a road in the environment; and using the prediction to generate a planned path for a vehicle in the environment.

A driving assistance control device includes an active pedal configured to control a driving and braking force of a vehicle, an electronic control unit configured to detect a potential risk area in which an obstacle entering a scheduled traveling route of the vehicle is likely to be present, and determine a reference speed at which contact between the vehicle and the obstacle can be avoided even when the obstacle enters the scheduled traveling route of the vehicle from the detected potential risk area based on a positional relationship between the vehicle and the potential risk area, and a force feedback unit configured to apply an assistance reaction force in a direction in which the amount of manipulation is reduced, to the active pedal when a current speed of the vehicle exceeds the reference speed.

Systems, methods, and autonomous vehicles may obtain one or more images associated with an environment surrounding an autonomous vehicle; determine, based on the one or more images, an orientation of a head worn item of protective equipment of an operator of a vehicle; determine, based on the orientation of the head worn item of protective equipment, a direction of a gaze of the operator and a time period associated with the direction of the gaze of the operator; determine, based on the direction of the gaze of the operator and the time period associated with the direction of the gaze of the operator, a predicted motion path of the vehicle; and control, based on the predicted motion path of the vehicle, at least one autonomous driving operation of the autonomous vehicle.

Systems and methods for virtual vehicle parking assistance are disclosed herein. An example method includes determining a current vehicle position and vehicle dimensions of a vehicle, determining parking space dimensions of a parking space, receiving a desired parking position for the vehicle through an augmented reality interface, the augmented reality interface including a three-dimensional vehicle model based on the vehicle dimensions, the augmented reality interface being configured to allow a user to virtually place the three-dimensional vehicle model in the parking space to determine the desired parking position, determining a virtual parking procedure for the vehicle based on the desired parking position selected by the user and the parking space dimensions of a parking space and causing the vehicle to autonomously park based on the virtual parking procedure.

A vehicle collision avoidance assist apparatus keeps stopping a collision avoidance control to avoid a collision of an own vehicle with an object ahead of the own vehicle when the own vehicle turns, a predetermined condition is satisfied, and a collision condition is satisfied. While the own vehicle turns, the apparatus acquires an own vehicle turning angle which is an angle which the own vehicle has turned about a turning center from when the own vehicle starts turning and change the predetermined condition, depending on the own vehicle turning angle.

A method for controlling operation of a motor vehicle includes an electronic controller receiving, e.g., from a vehicle-mounted sensor array, sensor data with dynamics information for a target vehicle and, using the received sensor data, predicting a lane assignment for the target vehicle on a road segment proximate the host vehicle. The electronic controller also receives map data with roadway information for the road segment; the controller fuses the sensor and map data to construct a polynomial overlay for a host lane of the road segment across which travels the host vehicle. A piecewise linearized road map of the host lane is constructed and combined with the predicted lane assignment and polynomial overlay to calculate a lane assignment for the target vehicle. The controller then transmits one or more command signals to a resident vehicle system to execute one or more control operations using the target vehicle's calculated lane assignment.