Abstract: In a boundary line recognition apparatus, based on luminance levels of an image captured by a camera, candidate edge points of a boundary line sectioning a travel road are extracted, and a candidate line of the boundary line is extracted. An apparent width of the candidate line on an image is calculated, from a width of the candidate line in a horizontal direction of the image and an angle of the candidate line relative to a vertical direction of the image. A probability of a candidate line being a boundary line is calculated to be higher, as a degree of the candidate line having characteristics as a boundary line is higher. The calculated probabilities are integrated in respect of a plurality of characteristics to recognize a boundary line. The characteristics include a ratio of the calculated apparent width to an image blur degree is larger than a predetermined value.

Abstract: A course estimator has a first estimating means, a second estimating means and a determining means. The first estimating means obtains first information and estimating a first radius of a first forward traveling path on the basis of the obtained first information, the first forward traveling path being a part of a forward traveling path to which a vehicle is going to travel. The second estimating means obtains second information and estimating a second radius of a second forward traveling path on the basis of the obtained second information, the second forward traveling path being a part of the forward traveling path to which a vehicle is going to travel, the second forward traveling path being farther from the vehicle than the first traveling being.

Abstract: A road surface information acquisition apparatus a lane line recognizer configured to, based on a road surface image of a carpool lane forward of a vehicle acquired by a camera, recognize lane lines of the carpool lane. The apparatus further includes a determiner configured to, based on a lane partition line recognized by the lane line recognizer, determine a start point and an end point of the entrance and exit, and a lane-width calculator configured to, based on the lane lines recognized by the lane line recognizer, calculate a lane width of the carpool lane. The apparatus further includes a lane-width corrector configured to, based on determinations made by the determiner, correct the lane width calculated by the lane-width calculator. Based on a broken line as the lane partition line, the determiner determines the start point and the end point of the entrance and exit of the carpool lane.

Abstract: In a boundary line recognition apparatus, based on luminance levels of an image captured by a camera, candidate edge points of a boundary line sectioning a travel road are extracted, and a candidate line of the boundary line is extracted. An apparent width of the candidate line on an image is calculated, from a width of the candidate line in a horizontal direction of the image and an angle of the candidate line relative to a vertical direction of the image. A probability of a candidate line being a boundary line is calculated to be higher, as a degree of the candidate line having characteristics as a boundary line is higher. The calculated probabilities are integrated in respect of a plurality of characteristics to recognize a boundary line. The characteristics include a ratio of the calculated apparent width to an image blur degree is larger than a predetermined value.

Abstract: In a boundary line recognition apparatus, based on luminance levels of an image captured by a camera, candidate edge points of a boundary line sectioning a travel road are extracted, and a candidate line of the boundary line is extracted. An apparent width of the candidate line on an image is calculated, from a width of the candidate line in a horizontal direction of the image and an angle of the candidate line relative to a vertical direction of the image. A probability of a candidate line being a boundary line is calculated to be higher, as a degree of the candidate line having characteristics as a boundary line is higher. The calculated probabilities are integrated in respect of a plurality of characteristics to recognize a boundary line. The characteristics include a ratio of the calculated apparent width to an image blur degree is larger than a predetermined value.

Abstract: A branching and merging determination apparatus includes a recognizer and a determiner. The recognizer recognizes a target present in front of an own vehicle. The determiner determines, based on a result of the recognition of the target by the recognizer, presence or absence of branching and merging of roads. Specifically, the determiner is configured to: estimate a traveling section where branching or merging of roads is probably present; and determine that no branching or merging of roads is present in a region of the estimated traveling section where there is a preceding vehicle traveling at a higher speed than the own vehicle.

Abstract: In a travel division line recognition apparatus, an extracting unit extracts a travel division line candidate from an image of a surrounding environment including a road, captured by an on-board camera. A calculating unit calculates a degree of reliability that the extracted travel division line candidate will be the travel division line. A recognizing unit selects the travel division line candidate based on the calculated degree of reliability, and recognizes the travel division line using the selected travel division line candidate. In the calculating unit, a solid object processing unit recognizes solid objects including vehicles, sets a suppression area including a frontal-face suppression area covering a frontal face of the other vehicle and a side-face suppression area covering a side face of the other vehicle, based on the recognized solid objects, and reduces the degree of reliability of the travel division line candidate present within the suppression area.

Abstract: An in-vehicle camera obtains image frames of a scene surrounding an own vehicle on a roadway. An extracting section in a lane boundary line recognition device extracts white line candidates from the image frames. The white line candidates indicate a degree of probability of white lines on an own vehicle lane on the roadway and a white line of a branch road which branches from the roadway. A branch judgment section calculates a likelihood of the white line as the white line of the branch road, and judges whether or not the white line candidate is the white line of the branch road based on the calculated likelihood. The branch judgment section decreases the calculated likelihood when a recognizable distance of the lane boundary line candidate monotonically decreases in a predetermined number of the image frames.

Abstract: A driving support apparatus installed in a host vehicle calculates an overlap ratio relating to a target object positioned ahead of the host vehicle within the same traffic lane, as the ratio of the width of the target object to its lateral distance from a lane marker line of the traffic lane, and also detects the motion condition of the object (i.e., stationary, moving towards, or in the same direction as the host vehicle, or moving laterally with respect to the forward direction of the host vehicle). An amount of compensation for retarding or advancing the commencement of a collision avoidance operation by the driving support apparatus is determined based on the overlap ratio and/or the motion condition of the target object.

Abstract: An apparatus for recognizing lane lines including a broken line. An image capture unit is configured to acquire an image of the surroundings including a roadway ahead of a subject vehicle. An edge-point extractor is configured to extract edge points in the image. An first-edge-point detector is configured to detect first edge points facing at least one missing section of a broken line in the edge points extracted by the edge-point extractor. A lane-line recognizes is configured to recognize a lane line using the edge points extracted by the edge-point extractor other than all or some of the first edge points.

Abstract: An apparatus for determining the presence or absence of a turnoff from a roadway. In the apparatus, a white-line candidate extractor applies image processing to an image of surroundings of a subject vehicle acquired by a vehicle-mounted camera to extract white-line candidates in the roadway. A white-line likelihood calculator calculates, for each of the white-line candidates extracted by the white-line candidate extractor, a likelihood of the white-line candidate. A white-line likelihood calculator calculates, for each of the white-line candidates extracted by the white-line candidate extractor, a likelihood of the white-line candidate. A turnoff determiner calculates a likelihood for one of a plurality of features of the white line selected by the white-line selector, and determines the presence or absence of a turnoff from the roadway based on the likelihood calculated by the turnoff determiner.

Abstract: In a lane line recognition apparatus, an abnormality determiner is configured to determine whether or not a width of a travel lane defined by left-side and right-side lane lines is abnormal, and a lane-line recognizer is configured to, when the width of the travel lane is not abnormal, recognize both of the left-side and right-side lane lines in a both-side line recognition mode, and when the width of the travel lane is abnormal, recognize one of the lane lines in a one-side line recognition mode. In the one-side line recognition mode, the lane-line recognizer is configured to, for each of the left-side and right-side lane lines, calculate two or more parameters of the lane line, and then integrate recognition results for the respective two or more parameters, and based on the integrated recognition results of the left-side and right-side lane lines, select one of the lane lines to be recognized.

Abstract: A lane boundary line recognition device detects lane boundary line candidates of a roadway from images captured by an in-vehicle camera, judges that the lane boundary line candidate is a lane boundary line of a branch road, and calculates a curvature of the lane boundary line candidate, and recognizes the lane boundary line based on the calculated curvature. The device removes the lane boundary line candidate, which has been judged as the lane boundary line of the branch road, is removed from a group of the lane boundary line candidates, and calculates the curvature of the lane boundary line candidate based on an estimated rate of change of the curvature. The device uses a past curvature calculated predetermined-number of images before when the lane boundary line candidate is the lane boundary line of the branch road, and resets the estimated rate of change of the curvature to zero.

Abstract: A driving support apparatus installed in a host vehicle calculates an overlap ratio relating to a target object positioned ahead of the host vehicle within the same traffic lane, as the ratio of the width of the target object to its lateral distance from a lane marker line of the traffic lane, and also detects the motion condition of the object (i.e., stationary, moving towards, or in the same direction as the host vehicle, or moving laterally with respect to the forward direction of the host vehicle). An amount of compensation for retarding or advancing the commencement of a collision avoidance operation by the driving support apparatus is determined based on the overlap ratio and/or the motion condition of the target object.

Abstract: An apparatus for recognizing a lane line. In the apparatus, when a three-dimensional object lies in the same lane as a subject vehicle and a distance between the three-dimensional object and the subject vehicle is small in an image acquired by an image capture unit, a masking area setter sets a masking area that is partially truncated at or near a lower end of the three-dimensional object in the image. A degree-of-belief calculator is configured to, for each of the edge points extracted by the edge-point extractor, calculate a degree of belief that the edge point is on the lane line. The degree of belief when the edge point is in the masking area is set less than the degree of belief when the edge point is outside the masking area. A lane-line recognizer is configured to recognize the lane line based on the degrees of belief calculated for the edge points.

Abstract: A driving support apparatus installed in a host vehicle calculates an overlap ratio relating to a target object positioned ahead of the host vehicle within the same traffic lane, as the ratio of the width of the target object to its lateral distance from a lane marker line of the traffic lane, and also detects the motion condition of the object (i.e., stationary, moving towards, or in the same direction as the host vehicle, or moving laterally with respect to the forward direction of the host vehicle). An amount of compensation for retarding or advancing the commencement of a collision avoidance operation by the driving support apparatus is determined based on the overlap ratio and/or the motion condition of the target object.

Abstract: A road surface information acquisition apparatus a lane line recognizer configured to, based on a road surface image of a carpool lane forward of a vehicle acquired by a camera, recognize lane lines of the carpool lane. The apparatus further includes a determiner configured to, based on a lane partition line recognized by the lane line recognizer, determine a start point and an end point of the entrance and exit, and a lane-width calculator configured to, based on the lane lines recognized by the lane line recognizer, calculate a lane width of the carpool lane. The apparatus further includes a lane-width corrector configured to, based on determinations made by the determiner, correct the lane width calculated by the lane-width calculator. Based on a broken line as the lane partition line, the determiner determines the start point and the end point of the entrance and exit of the carpool lane.

Abstract: In an apparatus for controlling a vehicle to track another vehicle, a controller causes the controlled vehicle to track one of other vehicles as a target vehicle if one of the other vehicles meets a target-vehicle selecting condition. The target-vehicle selecting condition is required for selecting one of the other vehicles as the target vehicle. The controller recognizes an environment of a predicted travel road on which the controlled vehicle is predicted to travel using conditions of the predicted travel lane. The controller determines whether the predicted travel road allows lane changes based on the recognized environment of the predicted travel road. The controller adjusts the target-vehicle selecting condition based on a result of the determination.

Abstract: An in-vehicle camera obtains image frames of a scene surrounding an own vehicle on a roadway. An extracting section in a lane boundary line recognition device extracts white line candidates from the image frames. The white line candidates indicate a degree of probability of white lines on an own vehicle lane on the roadway and a white line of a branch road which branches from the roadway. A branch judgment section calculates a likelihood of the white line as the white line of the branch road, and judges whether or not the white line candidate is the white line of the branch road based on the calculated likelihood. The branch judgment section decreases the calculated likelihood when a recognizable distance of the lane boundary line candidate monotonically decreases in a predetermined number of the image frames.

Abstract: A lane boundary line recognition device detects lane boundary line candidates of a roadway from images captured by an in-vehicle camera, judges that the lane boundary line candidate is a lane boundary line of a branch road, and calculates a curvature of the lane boundary line candidate, and recognizes the lane boundary line based on the calculated curvature. The device removes the lane boundary line candidate, which has been judged as the lane boundary line of the branch road, is removed from a group of the lane boundary line candidates, and calculates the curvature of the lane boundary line candidate based on an estimated rate of change of the curvature. The device uses a past curvature calculated predetermined-number of images before when the lane boundary line candidate is the lane boundary line of the branch road, and resets the estimated rate of change of the curvature to zero.