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: A travel lane marking probability calculating unit calculates a travel lane marking probability of each of travel lane marking candidates based on a calculation condition. A travel lane marking recognizing unit recognizes, as a travel lane marking, a travel lane marking candidate having a travel lane marking probability that is a threshold value or higher, among the travel lane marking candidates. A lane change detecting unit detects that an own vehicle is in the midst of a lane change. When the own vehicle is in the midst of a lane change, a condition changing unit changes the calculation condition to allow the travel lane marking probability to be more easily increased compared to when the own vehicle is not in the midst of a lane change, or changes the threshold value to be lower than that when the own vehicle is not in the midst of a lane change.

Abstract: An on-board camera captures an image of a travel lane ahead of an own vehicle. At least one state acquisition apparatus acquires an acquired value indicating a state of the own vehicle. A travel lane marking recognition system recognizes a travel lane marking that demarcates the travel lane from an image captured by the on-board camera. The travel lane marking recognition system sets a reliability level of the recognized travel lane marking based on the acquired value of the at least one state acquisition apparatus. When the reliability level is higher than a first predetermined threshold, the travel lane marking recognition system performs driving control of the own vehicle based on the recognized travel lane marking. When the reliability level is lower than the first predetermined threshold, the travel lane marking recognition system performs a deviation warning of deviation from the travel lane based on the recognized travel lane marking.

Abstract: An apparatus for recognizing lane partition lines on opposite sides of a traveling lane in a processing area of a forward image captured by a camera mounted in a vehicle. In the apparatus, a lane change determiner is configured to determine whether or not there is a lane change made by the vehicle. A processing area changer is configured to, while it is determined by the lane change determiner that there is a lane change, change the processing area from a predefined processing area to a processing area that can accommodate the lane change.

Abstract: An apparatus for recognizing lane partition lines on opposite sides of a traveling lane of a vehicle based on a forward image captured by a camera mounted in the vehicle. In the apparatus, an allowable range limiter is configured to, based on a learned value of a lane width learned by a lane width learner, limit allowable ranges for the respective lane partition lines, where in the allowable ranges the respective lane partition lines are allowed to be detected in the forward image. A lane change determiner is configured to determine whether or not there is a lane change made by the vehicle. The allowable range limiter is further configured to, if it is determined by the lane change determiner that there is a lane change, enlarge at least one of the allowable ranges limited by the allowable range limiter based on the learned value of the lane width.

Abstract: A cruising zone division line recognition apparatus has an image acquisition device that acquires an image including a road surface ahead of a vehicle, and an image recognition device. The image recognition device adds blurring to an area including the road surface in the acquired image and recognizes a cruising zone division line from the image to which blurring has been added. When blurring is added, a cruising zone division line that is an intermittent double line included in a captured image can be made unclear. Therefore, the recognized cruising zone division line can be prevented from becoming a discontinuous, disjointed line.

Abstract: In a lane boundary line information acquiring device, a detection unit detects lane boundary lines. A driving environment acquiring unit acquires a driving environment. A probability information acquiring unit acquires probability information containing a probability of presence of a lane boundary line, etc. based on the detected lane boundary lines and the acquired driving environment. A position information acquiring unit acquires position information of the own vehicle. A memory unit associates the probability information with the position information of the own vehicle. Where the position information is acquired by the position information acquiring unit at a time when the probability information acquiring unit acquires the probability information, and stores the probability information associated with the position information into the memory unit. A readout unit reads out the probability information associated with the position information at a location in front of the own vehicle.

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: A parking space recognition apparatus includes an onboard camera, a wireless receiver, and a parking space determination portion. The onboard camera is mounted to a first vehicle and captures a peripheral image around the first vehicle. The wireless receiver is mounted to the first vehicle and receives a parking-space related information that is transmitted from an outside of the first vehicle. The parking space determination portion is mounted to the first vehicle and determines a parking space to park the first vehicle on a basis of the peripheral image and the parking-space related information.

Abstract: An apparatus for recognizing a lane is provided. The apparatus performs a near-field white line recognition process and calculates road parameters (lane position, lane inclination, lane curvature and lane width) near the vehicle. The road parameters are calculated using the extended Kalman filter. In the calculation, the calculated lane curvature is used as a lane curvature to be included in predicted values. The apparatus outputs the calculated road parameters to a warning/vehicle-control apparatus.

Abstract: In a lane boundary line recognition device, a calculation section calculates a degree of uncertainty which affects a correct recognition of white lines on a roadway of a vehicle. A learning section updates a learning value of the degree of uncertainty. A recognition suppression section suppresses execution of a recognition process of recognizing white lines on the roadway when the updated learning value is more than a threshold value. An environment change judgment section judges whether or not a road environment has changed. A learning resetting section resets the learning value of the degree of uncertainty to a previous learning value when the detection result of the environment change judgment section indicates an occurrence of change of the road environment.

Abstract: A traffic lane marking recognition apparatus includes a candidate detecting unit, a gap detecting unit, and a recognition reducing unit. The candidate detecting unit detects a lane dividing line candidate which is a candidate for a lane dividing line that defines a traffic lane on a road, based on an image of the road captured by an on-board camera that is mounted in a vehicle. The gap detecting unit detects a gap included in the lane dividing line candidate detected by the candidate detecting unit. When the gap is detected by the gap detecting unit, the recognition reducing unit reduces a probability of recognition of the lane dividing line candidate as a lane dividing line to a first probability that is lower than the probability when the gap detecting unit does not detect the gap, in a region from the gap closest to the vehicle towards a direction away from the vehicle.

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.

Abstract: In a lane boundary line recognition device, an extraction unit extracts lane boundary line candidates from image acquired by an in-vehicle camera. A position estimation unit estimates a position of each lane boundary line based on drive lane information containing a number of drive lanes on a roadway and a width of each drive lane when (a) and (b) are satisfied, (a) when an own vehicle drives on an own vehicle lane specified by the drive lane specifying unit, and (b) when the lane boundary line candidate corresponds to lane boundary lines of the own vehicle lane. A likelihood calculation unit increases a likelihood of the lane boundary line candidate when a distance between a position of the lane boundary line candidate and an estimated position of the lane boundary line candidate obtained by the drive lane boundary line position estimation unit is within a predetermined range.

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 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 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: In a travel path estimation apparatus, a calculating unit calculates coordinates of edge points configuring a division line on a travel path, from an image captured by an on-board camera. An estimating unit estimates a travel path parameter of a state of the travel path and a shape of the travel path using a predetermined filter, based on the calculated coordinates of edge points. A setting unit sets a filter parameter of the predetermined filter of responsiveness of estimation of the travel path parameter. A detecting unit detects a sharp curve based on information giving advance notice of a sharp curve before the vehicle enters the sharp curve. The setting unit sets the filter parameter so that the responsiveness increases from that before detection of the sharp curve, during a period from detection of the sharp curve until the vehicle enters the sharp curve.

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.