Abstract: A self-position estimation method includes: detecting a relative position between a target present in surroundings of a moving object and the moving object; storing a position where the relative position is moved by the moved amount of the moving object, as target position data; selecting the target position data on the basis of reliability of the relative position of the target position data with respect to the moving object; and comparing the selected target position data with map information including the position information on the target present on a road or around the road, thereby estimating a self-position which is a current position of the moving object.

Abstract: A self-position estimation method includes: detecting a relative position of each target existing around a moving body relative to the moving body; estimating a movement amount of the moving body; correcting the relative position on a basis of the movement amount of the moving body and accumulating the corrected relative position as target position data; detecting a slope amount of a traveling road of the moving body; selecting, from among the accumulated target position data, the target position data of one or more targets in one or more sections having a slope amount less than a threshold value; and collating the selected target position data with map information indicating positions of the targets on a two-dimensional map to estimate a present position of the moving body.

Abstract: A travel control method comprises: learning points which a vehicle has traveled over based on images of the surroundings of the vehicle captured with a camera mounted on the vehicle; learning the travel trajectory of the vehicle based on vehicle signals obtained from the vehicle; determining whether the vehicle has passed the points based on the images captured with the camera; and performing travel control of the vehicle by using the travel trajectory learned based on the vehicle signals as a target trajectory between the points.

Abstract: A travel control method comprises: learning points which a vehicle has traveled over based on images of the surroundings of the vehicle captured with a camera mounted on the vehicle; learning the travel trajectory of the vehicle based on vehicle signals obtained from the vehicle; determining whether the vehicle has passed the points based on the images captured with the camera; and performing travel control of the vehicle by using the travel trajectory learned based on the vehicle signals as a target trajectory between the points.

Abstract: A self-position estimation method includes: detecting a relative position of a target existing around a moving body relative to the moving body; estimating a movement amount of the moving body; correcting the relative position on a basis of the movement amount of the moving body and accumulating the corrected relative position as target position data; detecting a behavior change amount of the moving body; selecting, from among the accumulated target position data, the target position data of the relative position detected during a period in which the behavior change amount is less than a threshold value; and collating the selected target position data with map information indicating a position on a map of the target to estimate a present position of the moving body.

Abstract: A travel lane detection method overlaps a plurality of travel lane boundary point groups parallel to each other, extracted according to continuity of a plurality of travel lane characteristic points detected by a target detection sensor installed in a vehicle, estimates a travel lane outline according to the travel lane characteristic points included in the overlapped travel lane boundary point groups, and determines travel lane boundaries based on lateral positions of the travel lane boundary point groups parallel to each other and the estimated travel lane outline.

Abstract: A self-position estimation method includes: detecting a relative position between a target present in surroundings of a moving object and the moving object; storing a position where the relative position is moved by the moved amount of the moving object, as target position data; selecting the target position data on the basis of reliability of the relative position of the target position data with respect to the moving object; and comparing the selected target position data with map information including the position information on the target present on a road or around the road, thereby estimating a self-position which is a current position of the moving object.

Abstract: A step detection device, including a distance measurement unit which detects the height of the road surface around a vehicle, approximates with a curve, the gradient of the road surface in a travelable region in the vehicle width direction, based on the height of the road surface, and detects a step on the road surface, based on the agreement degree of the height of a measurement point relative to the curve and the agreement degree of the height of a measurement point relative to a curve with which the gradient of the road surface in an extended region defined by extending the travelable region in the vehicle width direction is approximated.

Abstract: A self-position estimation method includes: detecting a relative position of a target existing around a moving body relative to the moving body; estimating a movement amount of the moving body; correcting the relative position on a basis of the movement amount of the moving body and accumulating the corrected relative position as target position data; detecting a behavior change amount of the moving body; selecting, from among the accumulated target position data, the target position data of the relative position detected during a period in which the behavior change amount is less than a threshold value; and collating the selected target position data with map information indicating a position on a map of the target to estimate a present position of the moving body.

Abstract: A self-position estimation method includes: detecting a relative position of each target existing around a moving body relative to the moving body; estimating a movement amount of the moving body; correcting the relative position on a basis of the movement amount of the moving body and accumulating the corrected relative position as target position data; detecting a slope amount of a traveling road of the moving body; selecting, from among the accumulated target position data, the target position data of one or more targets in one or more sections having a slope amount less than a threshold value; and collating the selected target position data with map information indicating positions of the targets on a two-dimensional map to estimate a present position of the moving body.

Abstract: A travel lane detection method detects travel lane boundaries according to a plurality of travel lane characteristic points detected by a target detection sensor installed in a vehicle. When a lane change of the vehicle is detected, the method determines continuity of the travel lane characteristic points detected before the lane change is completed with respect to the travel lane characteristic points detected after the lane change is completed while taking account of a lane change amount so as to detect the travel lane boundaries according to the continuity of the travel lane characteristic points.

Abstract: A travel lane detection method detects travel lane boundaries according to a plurality of travel lane characteristic points detected by a target detection sensor installed in a vehicle. When a lane change of the vehicle is detected, the method determines continuity of the travel lane characteristic points detected before the lane change is completed with respect to the travel lane characteristic points detected after the lane change is completed while taking account of a lane change amount so as to detect the travel lane boundaries according to the continuity of the travel lane characteristic points.

Abstract: A travel lane detection method overlaps a plurality of travel lane boundary point groups parallel to each other, extracted according to continuity of a plurality of travel lane characteristic points detected by a target detection sensor installed in a vehicle, estimates a travel lane outline according to the travel lane characteristic points included in the overlapped travel lane boundary point groups, and determines travel lane boundaries based on lateral positions of the travel lane boundary point groups parallel to each other and the estimated travel lane outline.

Abstract: A step detection device, including a distance measurement unit which detects the height of the road surface around a vehicle, approximates with a curve, the gradient of the road surface in a travelable region in the vehicle width direction, based on the height of the road surface, and detects a step on the road surface, based on the agreement degree of the height of a measurement point relative to the curve and the agreement degree of the height of a measurement point relative to a curve with which the gradient of the road surface in an extended region defined by extending the travelable region in the vehicle width direction is approximated.

Abstract: An aspect of the present invention provides a moving obstacle detecting device installed in or on a moving body for detecting moving obstacles in the vicinity of the moving body, the moving obstacle detecting device that includes an image capturing unit configured and arranged to capture an image of the surroundings of the moving body, an optical flow calculating unit configured to find an optical flow corresponding to characteristic points in the image captured with the camera, a focus of expansion calculating unit configured to calculate focus or foci of expansion of the motion vectors in the optical flow found by the optical flow calculating unit, a histogram creating unit configured to create a histogram of the distribution of the focus or foci of expansion calculated by the focus of expansion calculating unit, a peak test unit configured to detect at least one moving obstacle to test peaks in the histogram, the test determining whether or not the peaks correspond to the same object if two or more peaks e

Abstract: An apparatus for image processing. An image processor includes an image input device for capturing a pickup image and a controller. The controller is operable to select a target image corresponding to the pickup image by comparing the pickup image with a plurality of prepared target images. A type of the pickup image is identified based on the target image selected.

Abstract: A behavior detector and a behavior detection method for a vehicle. A controller extracts multiple characteristic points out of an image captured using a camera and computes the velocities and the directions that the respective extracted characteristic points move in the image. Then, the controller computes the times (TTC) until vehicle collision with the respective characteristic points based on the computed velocities and the directions that the respective extracted characteristic points move in the image. Distant characteristic points are designated based on the computed TTCs, and movements of the distant characteristic points are monitored in order to detect pitching and yawing of the vehicle.

Abstract: An aspect of the present invention provides a moving obstacle detecting device installed in or on a moving body for detecting moving obstacles in the vicinity of the moving body, the moving obstacle detecting device that includes an image capturing unit configured and arranged to capture an image of the surroundings of the moving body, an optical flow calculating unit configured to find an optical flow corresponding to characteristic points in the image captured with the camera, a focus of expansion calculating unit configured to calculate focus or foci of expansion of the motion vectors in the optical flow found by the optical flow calculating unit, a histogram creating unit configured to create a histogram of the distribution of the focus or foci of expansion calculated by the focus of expansion calculating unit, a peak test unit configured to detect at least one moving obstacle to test peaks in the histogram, the test determining whether or not the peaks correspond to the same object if two or more peaks e