Honda Motor Co., Ltd.

Honda Giken Kogyo Kabushiki Kaisha

Honda Giken Gokyo Kabushiki Kaisha

Tomoyoshi Aoki

Sachio Kobayashi

Takuma Nakamori

Naoki Mori

Masakazu Saka

Hiromitsu Yuhara

Morimichi Nishigaki

Jun Tanaka

Shigeru Inoue

Kiyozumi Unoura

Tetsuo Ikeda

Daisuke Hanzawa

Horimitsu Yuhara

Hisaya Izawa

A trajectory tracking control unit carries out a trajectory tracking control in the event that a predetermined condition is satisfied. On the other hand, in the case that a preceding vehicle recognizing unit detects that a preceding vehicle has moved in a vehicle transverse direction, the trajectory tracking control unit predicts that the preceding vehicle will depart from a lane in which it is traveling. Therefore, even if the predetermined condition is satisfied after the preceding vehicle recognizing unit has detected that the preceding vehicle has moved in the vehicle transverse direction, the trajectory tracking control unit does not cause the driver's own vehicle to follow the trajectory of the preceding vehicle.

Driving support device

A driving support device includes: a preceding vehicle recognizer that recognizes a preceding vehicle; a lane mark recognizer that recognizes a lane mark; a path following controller that controls the own-vehicle; and a lane maintaining controller that controls the own-vehicle when a vehicle speed of the own-vehicle is greater than or equal to a predetermined speed. The driving support device further includes a prediction unit that predicts a shift of the own-vehicle to a running state with the predetermined speed or greater, and while the own-vehicle is under control of the path following controller, when the preceding vehicle ceases to be an object recognized by the preceding vehicle recognizer, the vehicle speed is less than the predetermined speed, and the prediction unit (control management unit) predicts the shift of the own-vehicle to the running state with the predetermined speed or greater, the lane maintaining controller controls the own-vehicle.

The lane mark recognition device is equipped with a lane mark detecting unit which executes a lane mark detection process in each predetermined control cycle, and adds a detection presence/absence data to a ring buffer, a detection presence/absence data addition inhibiting unit which inhibits addition of the detection presence/absence data to the ring buffer when the vehicle is traveling in the intersection, and a lane mark position recognizing unit which recognizes a relative position of the vehicle and the lane mark, when the lane mark is detected in the situation where a lane mark detection rate calculated from the data of the ring buffer is higher than a reliability threshold value.

Lane recognition device

A steering control device for a vehicle has a steering assistance means () which performs steering assistance processing for driving an actuator () so that a vehicle () travels along a lane recognized by a lane recognition means () from an image acquired by an image acquisition means (); a side displacement amount calculation means () which calculates a displacement amount in the lane width direction between the position of the vehicle () and the center of the recognized lane; a complexity calculation means () which calculates the complexity of the acquired image; and a steering assistance inhibition means () which inhibits, according to the displacement amount in the lane width direction calculated based on the lane recognized from the acquired image at a given time point and the complexity of the acquired image, steering assistance processing based on the lane by the steering assistance means (). This prevents inappropriate steering control based on an incorrectly recognized lane when performing the steering control of the vehicle so that the vehicle travels along the lane recognized from the road image.

Vehicle and steering control device for vehicle

An image processing system and the like capable of recognizing a lane mark in a road image with high accuracy are provided even if a light illumination state on a road surface is partially different. According to the image processing system () mounted on a vehicle (), a color component (Rij, Gij, Bij) of the first pixel (Pij) included in an area (Aij) set in the road image is corrected with reference to a color component (Rik, Gik, Bik) of a second pixel (Pik) in view of a fact that it is highly probable that the color component of the second pixel included in the area along with the first pixel is affected by a shadow or light on the road surface. This reduces the effect of the shadow or light on the road surface and the actual color of a road surface portion corresponding to the first pixel can be sufficiently reflected in the color components (Rij, Gij, Bij) of the first pixel (Pij) and consequently in a feature value (Qij). Therefore, a lane mark (M) and its edge (E) are recognized in the road image on the basis of the feature value (Qij) of each pixel (Pij) in the road image.

Systems and methods of vehicle image processing

There is provided an image acquisition means () for acquiring a color image of a road via an imaging means () mounted on a vehicle (), a lane mark detection means () for performing processing of detecting lane marks of a plurality of predetermined colors different from each other on the road based on color information of the color image, and outputting a result of the processing as lane mark candidate data, and a selection means () for selecting lane mark candidate data corresponding to a lane mark defining an actual lane on which the vehicle () is traveling from among at least the lane mark candidate data for the respective predetermined colors output from the lane mark detection means (), and determining and outputting lane data indicating information of the actual lane based on the selected lane mark candidate data. Therefore, even if there are lane marks of different colors on the road, the lane marks of the respective colors can be recognized appropriately from the color image of the road acquired via the imaging means such as a camera.

Vehicle and lane recognition device

An image processing system and the like capable of accurately recognizing lane edges defined by dotted lane marks are provided. According to an image processing system () of the present invention, a first processing unit () searches a road surface image captured by a vehicle-mounted camera for a 'small area,' which is composed of high- or low-luminance pixels and satisfies 'eligibility conditions' on the &#x201c;size,&#x201d; &#x201c;shape,&#x201d; and &#x201c;arrangement&#x201d; in the road surface image. Additionally, a second processing unit () recognizes &#x201c;lane edges&#x201d; of the lane along which the vehicle travels on the basis of the &#x201c;small area.&#x201d; Furthermore, a third processing unit () sets a &#x201c;search range&#x201d; of the small area searched by the first processing unit () on the basis of a result of the foregoing recognition of the lane edges by the second processing unit ().

Vehicle, image processing system image processing method, image processing program, method for configuring image processing system, and server

An image processing system and the like capable of improving recognition accuracy of a lane mark are provided. According to the image processing system of the present invention, a first processing unit () recognizes a lane mark candidate on the basis of the luminance of each pixel in a road image. Moreover, there are evaluated a first index which represents continuity of an edge of the lane mark candidate, a second index which represents conformance between the width of the lane mark candidate and a lane mark standard width, and a third index which represents uniformity of the luminance of pixels contained in the lane mark candidate. According to the first, second, and third indices, a second processing unit () recognizes a lane mark candidate most likely to be a true lane mark as a lane mark.

Method and system for in-vehicle image processing

A vehicle and road sign recognition device each includes: image capturing means () which captures a color image of a road via imaging means (); feature value calculation means () which calculates a feature value of each pixel corresponding to the color of a road sign on the road from the color components of each pixel in the color image so as to reduce the effect of brightness on the color components; and road sign detection means () which detects the road sign on the road from the feature image in which the feature value of each pixel in the color image is arranged so as to match with the position of each pixel in the color image. Thus, it is possible to accurately detect a road sign such as a lane mark from the color image of the road captured via the imaging means such as a camera even if the road illumination state is partially different.

Vehicle and road sign recognition device

The present invention includes: image capturing means () which captures a color image of a road via imaging means (); area extraction means () which extracts areas having a similar color feature value from the captured color image of the road; white balance processing means () which performs, for each of the extracted areas, a white balance process of correcting each pixel data in the extracted area so as to reduce the degree of divergence in the level between color components according to a level balance between the color components of the pixel data in the extracted area; and road sign detection means () which detects a road sign on the road from the color image subjected to the white balance process. Thus, even if the road illumination state is partially different, it is possible to accurately detect a road sign such as a lane mark from the captured color image of the road via the imaging means such as a camera.

A lane mark recognition apparatus includes an image capturing means () which captures a color image (IM) of a road via a color video camera (), a specific-color-extracted image generating means () which generates a luminance-extracted image (IM) obtained by extracting white-color data from the color image (IM) and a yellow-color-extracted image (IM) obtained by extracting yellow-color data from the color image (IM), and a lane mark detection means () which detects a white line and a yellow line from a composite image (IM_C) formed from the luminance-extracted image (IM) and the yellow-color-extracted image (IM) and outputs position data (Pd) of the white line and position data (Pd) of the yellow line.

Vehicle and lane mark recognition apparatus

A vehicle capable of preventing detection of stud-type lane marks from being impossible and a vehicle having a lane mark recognizer are provided. The vehicle includes installation interval recognizing means () which recognizes an interval (L) between Botts Dots, vehicle speed recognizing means () which recognizes a traveling speed (v) of the vehicle, image synthesizing means () which generates synthesized image data (M) by combining image data (M) stored in an image memory () through an image input circuit () and image data (M) stored in an image memory () through the same, imaging timing determining means () which determines the timing of imaging by a camera () on the basis of the interval (L) and the traveling speed (v) when acquiring the image data (M, M) in such a way that the positions of the Botts Dots in the image data (M, M) are different therebetween, and Botts Dots detecting means () which detects the Botts Dots from the synthesized image data (M).

Vehicle and lane mark recognizes

An object recognition system mounted on a vehicle comprises a camera and a controller. The camera captures an image in front of the vehicle. The controller divides the image into a plurality of windows. The controller measures distance to the road surface for each of the plurality of windows and thereby obtains a plurality of distances. The controller estimates a relative inclination of the road surface against the vehicle based on the plurality of distances. The controller judges, for each of the plurality of windows, based on the estimated inclination, whether the object is an obstacle or the road surface and thereby obtains a judgment result. The controller recognizes the object based on the judgment result. The system recognizes objects in front of the vehicle even when the vehicle is lopsided by pitching, rolling or else.

Object recognition system

An object recognition system including a position sensor, an image sensor and a controller is provided. The position sensor determines the position of an object, and the image sensor captures an image of the object. The controller sets a processing area within the image captured by the image sensor based on the position of the object determined by the position sensor and a predetermined size for the object to be recognized. The controller extracts horizontal edges from the processing area, and judges whether each of the extracted edges belongs to the object based on characteristics of the object to be recognized. More practically, the controller can check if each of the extracted edges contains a pixel on a boundary of the processing area. If so, the controller judges to the edge to belong to an object other than the object. The controller can also examine the linearity of each of the extracted edges. If the linearity is larger than a predetermined value, the controller judges the edge to belong to an object other than the object. The controller can also examine the slope of each of the extracted edges. If the slope is larger than a predetermined value, the controller judges the edge to belong to an object other than the object. Thus, the edges judged to belong to an object other than the object are removed. The controller recognizes the outline of the object based on the edges judged to belong to the object.

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Wako, Japan

Tomoyoshi Aoki