Abstract: A vehicle control method causes a controller to execute: vehicle speed determination processing of determining whether or not vehicle speed of an own vehicle is reduced to less than a predetermined speed threshold; lateral deviation detection processing of detecting lateral deviation of the own vehicle with respect to a lane center or a lane boundary line; target trajectory generation processing of, when determining that the vehicle speed is reduced to less than the speed threshold, generating a first target travel trajectory of the own vehicle in such a way as to suppress change in the lateral deviation at and after a vehicle speed reduction time point; avoidance target detection processing of detecting an avoidance target; and avoidance processing of avoiding the avoidance target by, after the vehicle speed reduction time point, adjusting deceleration of the own vehicle while the own vehicle travels along the first target travel trajectory.

Abstract: A vehicle control method causes a controller to execute: processing of determining whether or not a first other vehicle traveling on a second lane, the second lane merging with a first lane on which an own vehicle travels in front of the own vehicle, is traveling diagonally in front of the own vehicle; and processing of, when determining that the first other vehicle is traveling diagonally in front of the own vehicle, controlling vehicle speed of the own vehicle in such a way that a front-rear direction distance from a rear-end position of the first other vehicle to a front-end position of the own vehicle in a front-rear direction of the first lane is shorter than a first target inter-vehicle distance in vehicle speed control to maintain an inter-vehicle distance to a preceding vehicle traveling in front of the own vehicle on the first lane.

Abstract: A vehicle control method causes a controller to execute: processing of determining whether or not a first other vehicle traveling on a second lane, the second lane merging with a first lane on which an own vehicle travels in front of the own vehicle, is traveling diagonally in front of the own vehicle; and processing of, when determining that the first other vehicle is traveling diagonally in front of the own vehicle, controlling vehicle speed of the own vehicle in such a way that a front-rear direction distance from a rear-end position of the first other vehicle to a front-end position of the own vehicle in a front-rear direction of the first lane is shorter than a first target inter-vehicle distance in vehicle speed control to maintain an inter-vehicle distance to a preceding vehicle traveling in front of the own vehicle on the first lane.

Abstract: A vehicle control method causes a controller to execute: vehicle speed determination processing of determining whether or not vehicle speed of an own vehicle is reduced to less than a predetermined speed threshold; lateral deviation detection processing of detecting lateral deviation of the own vehicle with respect to a lane center or a lane boundary line; target trajectory generation processing of, when determining that the vehicle speed is reduced to less than the speed threshold, generating a first target travel trajectory of the own vehicle in such a way as to suppress change in the lateral deviation at and after a vehicle speed reduction time point; avoidance target detection processing of detecting an avoidance target; and avoidance processing of avoiding the avoidance target by, after the vehicle speed reduction time point, adjusting deceleration of the own vehicle while the own vehicle travels along the first target travel trajectory.

Abstract: A vehicle control method executed by a processor for controlling a subject vehicle includes: acquiring, from a sensor for detecting a state of surroundings of the subject vehicle, detection data of another vehicle traveling in an adjacent lane adjacent to a travel lane in which the subject vehicle is traveling, and setting, on the adjacent lane, a target point for the subject vehicle to change a lane from the travel lane to the adjacent lane based on a position relationship between the subject vehicle and the other vehicle, specifying the other vehicle that is located behind the target point as a rear vehicle, and starting blinking of the direction indicator of the subject vehicle when a rear end of the subject vehicle is located ahead of the front end of the rear vehicle.

Abstract: An autonomous driving control method carried out by an autonomous driving control system having an autonomous driving control unit that executes an autonomous driving control for causing a host vehicle to travel along a target travel route generated on a map, comprising setting one or a plurality of target passage gates through which the host vehicle is scheduled to pass during passage through a toll plaza, determining the presence or absence of a preceding vehicle that has the predicted passage gate that matches the target passage gate of the host vehicle from among a plurality of preceding vehicles, and carrying out following travel using the preceding vehicle that has the predicted passage gate that matches the target passage gate as a follow target.

Abstract: An autonomous driving control method carried out by an autonomous driving control system having an autonomous driving control unit that executes an autonomous driving control for causing a host vehicle to travel along a target travel route generated on a map, comprising setting one or a plurality of target passage gates through which the host vehicle is scheduled to pass during passage through a toll plaza, determining the presence or absence of a preceding vehicle that has the predicted passage gate that matches the target passage gate of the host vehicle from among a plurality of preceding vehicles, and carrying out following travel using the preceding vehicle that has the predicted passage gate that matches the target passage gate as a follow target.

Abstract: A vehicle control method executed by a processor for controlling a subject vehicle includes: acquiring, from a sensor for detecting a state of surroundings of the subject vehicle, detection data of another vehicle traveling in an adjacent lane adjacent to a travel lane in which the subject vehicle is traveling, and setting, on the adjacent lane, a target point for the subject vehicle to change a lane from the travel lane to the adjacent lane based on a position relationship between the subject vehicle and the other vehicle, specifying the other vehicle that is located behind the target point as a rear vehicle, and starting blinking of the direction indicator of the subject vehicle when a rear end of the subject vehicle is located ahead of the front end of the rear vehicle.

Abstract: A driving plan display method controls an in-vehicle road surface image display device that can display an image on a road surface is controlled using a display controller to display driving plan-related information of a host vehicle on the road surface. In the method, the driving plan-related information of the host vehicle and information relating to prediction of a pedestrian's crossing is acquired. Based on the acquired information, a predicted crossing point is obtained at which the pedestrian's crossing is predicted on a planned travel route of the host vehicle. Then, an image of the driving plan-related information of the host vehicle from a current position of the host vehicle to the crosswalk as the predicted crossing point is displayed on the road surface of the crosswalk as the predicted crossing point with the road surface image display device.

Abstract: A 3D-object recognition device includes: a matching unit to compare a 3D-object in an image based on the image data with a 3D-shape model corresponding to the 3D-object to associate correlated feature points with each other by pattern matching; a model updating unit to update the 3D-shape model based on the feature points associated by the matching unit; a motion estimation unit to estimate motion of the 3D-object based on a history of the position and attitude of the 3D-shape model updated by the model updating unit to estimate a 3D-shape model at an arbitrary time in the future; and a validity determination unit to compare the feature points associated by the matching unit with the 3D-shape model estimated by the motion estimation unit and cause the model updating unit to update the 3D-shape model based on only the feature points determined to be valid.

Abstract: A 3D-object recognition device includes: a matching unit to compare a 3D-object in an image based on the image data with a 3D-shape model corresponding to the 3D-object to associate correlated feature points with each other by pattern matching; a model updating unit to update the 3D-shape model based on the feature points associated by the matching unit; a motion estimation unit to estimate motion of the 3D-object based on a history of the position and attitude of the 3D-shape model updated by the model updating unit to estimate a 3D-shape model at an arbitrary time in the future; and a validity determination unit to compare the feature points associated by the matching unit with the 3D-shape model estimated by the motion estimation unit and cause the model updating unit to update the 3D-shape model based on only the feature points determined to be valid.

Abstract: (A) One or both of an object and a robot are measured by measuring units to acquire sensor information. (B) The internal state of one or both of the object and the robot is predicted and updated by a state estimation unit on the basis of the sensor information. (C) The internal state is stored by a data storage unit. (D) The robot is controlled by a robot control unit. At (B), the internal state is updated by the state estimation unit at an arbitrary timing that is independent of the control cycle of the robot. At (D), a prediction value necessary for controlling the robot is calculated by the robot control unit at a control cycle on the basis of the latest internal state stored in the data storage unit.

Abstract: (A) One or both of an object and a robot are measured by measuring units to acquire sensor information. (B) The internal state of one or both of the object and the robot is predicted and updated by a state estimation unit on the basis of the sensor information. (C) The internal state is stored by a data storage unit. (D) The robot is controlled by a robot control unit. At (B), the internal state is updated by the state estimation unit at an arbitrary timing that is independent of the control cycle of the robot. At (D), a prediction value necessary for controlling the robot is calculated by the robot control unit at a control cycle on the basis of the latest internal state stored in the data storage unit.