Denso Corporation

Nippon Soken, Inc.

So-Ken Corporation

Shunsuke Suzuki

Naoki Kawasaki

Tetsuya Takafuji

Syunya Kumano

Shunya Kumano

Tomohiko Tsuruta

Hiroshi Mizuno

Yuu Maeda

Osamu Shimomura

Kazuhisa Ishimaru

Kazuma Hashimoto

Kojiro Tateishi

Takeshi Shikimachi

Hirotake Ishigami

Taiki Kawano

Akihiro Watanabe

Masayuki Imanishi

Yusuke Akamine

Yusuke Ueda

Yusuke Tanaka

Junichi Hasegawa

Kenji Muto

Satoshi Osanai

Masaya Okada

Tatsuru Kuwabara

Kenta Hoki

Mikio Shimizu

Keiko Ogawa

Koujirou Tateishi

Ryota Yamamoto

In a road parameter estimation apparatus, a marker-based estimator extracts, based on markers extracted by a marker extractor, at least one lane line that demarcates a road into plural regions in a width direction of the road, and estimates, based on the extracted at least one lane line, a value of at least one feature parameter of the road as a maker-based estimation result. The at least one feature parameter of the road represents at least one feature of the road. A model-based estimator estimates, based on the at least one model-based demarcation line, a value of the at least one feature parameter of the road parameter as a model-based estimation result. A determiner compares the at least one lane line with the model-based demarcation line to accordingly determine whether to use the marker-based estimation result or the model-based estimation result.

Apparatus for estimating road parameter

A driving support apparatus is provided to improve accuracy of the driving support such as a notification to the driver and the vehicle control. In the apparatus, a common parameter indicating a location of a lane boundary is calculated for the vehicle control, based on an actual boundary line where a location of the lane boundary line existing at both sides of the vehicle is actually measured. A common error is defined as an error between the location of an estimated boundary indicated by the common parameter and a location of the actual boundary line. In the case where the common error is larger than or equal to a common threshold in which an amount of the common error is set in advance, the apparatus determines that the travelling road where the vehicle travels is branched and stops the vehicle control using the common parameter.

Driving support apparatus

A road parameter calculator is provided which is equipped with an edge-point extracting unit, a road parameter calculating unit, a gradient detecting unit, and a modeling unit. The image acquiring unit. The edge-point extracting unit extracts edge points from an image of a frontal view of a vehicle. The parameter calculating unit calculates a road parameter using the edge points through a Kalman filter. The gradient detecting unit detects a change in gradient of the road in front of the vehicle. The modeling unit is responsive to a change in gradient to make a model as extending more straight than when the change in gradient is not detected. This minimizes adverse effects of the change in gradient of the road on the calculation of the road parameter.

Road parameter calculator

An apparatus for identifying a line marking on a road surface. In the apparatus, an extractor extracts a paint candidate that is a candidate for road surface paint used to identify a line marking in an image captured by a camera mounted on a vehicle to capture an image of an area including a road surface ahead of the vehicle. A determiner determines whether or not the paint candidate has at least one predefined flare feature. A line marking identifier identifies a line marking using the paint candidate which meets an identification condition used to identify a line marking. The line marking identifier sets the identification condition to be more stringent for a flare paint candidate that is the paint candidate determined by the determiner to have the at least one predefined flare feature than for the paint candidate determined by the determiner to have no predefined flare feature.

Apparatus for identifying line marking on road surface

The driving support system extracts edge points based on luminance of pixels, in which up edge point is the edge point where the luminance of the inner pixel is smaller than that of the outer pixel, down edge point is the edge point where the luminance of the outer pixel is smaller than the luminance of inner pixel. The system determines, among a plurality of line candidates acquired in accordance with the edge points location, a lane candidate excluding the line candidate that satisfies a predetermined exclusion condition, to be the lane marking, the line candidate determined as the lane marking being located most closely to the vehicle position. The exclusion condition includes a condition where the number of edge points of the up edge line is larger than or equal to a predetermined point threshold, compared to the number of edge points of the down edge line.

Driving support system

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.

Boundary line recognition apparatus and branch road determination apparatus

In a travelling road estimating apparatus, an estimator estimates, based on the coordinates of at least one of edge points included in a selected candidate, a road parameter using a previously prepared filter having an adjustable response level. The road parameter is associated with a condition of the travelling road relative to the vehicle and a shape of the travelling road. A determiner determines whether there is an unstable situation that causes an accuracy of estimating the edge points by an edge extractor to be reduced. A response level adjuster adjusts the response level of the filter in accordance with determination of whether there is an unstable situation that causes an accuracy of estimating the edge points by the edge extractor to be reduced.

Estimating apparatus

A position identifying apparatus includes a position detecting unit; an information acquiring unit; a feature extracting unit; an index value calculating unit; a feature selecting unit; a correlating unit; a weight setting unit; and a correcting unit. The position detecting unit performs a map matching to detect a vehicle position on a map. The information acquiring unit acquires road information from the map. The feature extracting unit extracts features of a ground object. The index value calculating unit calculates an index value representing a likelihood of a stationary object. The feature selecting unit selects feature candidates among the features having the index values larger than or equal to a predetermined likelihood of the stationary object. The correlating unit correlates the feature candidates with the road information. The weight setting unit sets weights of the feature candidates. The correcting unit corrects the position of the vehicle using the weights.

Apparatus for identifying position of own vehicle and method for identifying position of own vehicle

In a location estimation device, a change detection unit detects a point of change in the width of a roadside structure as a width change point. A width correction unit calculates a width deviation between a first relative location of the roadside structure on a map data segment and a second relative location of the roadside structure obtained based on shape information of the roadside structure in the width direction of a vehicle. The width correction unit corrects, as a function of the width deviation and a positional accuracy of the vehicle in the travelling direction, an estimated location of the vehicle in the width direction when it is determined that there is the point of change in the width of the roadside structure in the travelling direction of the vehicle.

Location estimation device

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.

Road surface information acquisition apparatus for entrance/exit lane

An in-vehicle system as a road curvature detection device calculates a curvature of a road in front of a vehicle based on an acquired front scene image. The in-vehicle system receives gradient information from the data map. The gradient information corresponds to a current road section on the road on which the vehicle drives. The in-vehicle system detects a gradient accuracy of the received gradient information. When the current road section has a gradient, i.e. the road is an uphill or downhill road, the in-vehicle system selects an appropriate special detection methods based on the gradient accuracy of the received gradient information, and calculates a road curvature by using the selected special detection method. Each of the special detection methods calculates a road curvature while effectively suppressing influence of a road gradient indicated by the received gradient information.

Road curvature detection device

A traveling path estimation apparatus includes a calculation section that calculates a traveling marking line marking a lane of a road, on which a vehicle runs, based on a front image acquired by a camera mounted in the vehicle, an estimation section that estimates road parameters including a curvature and a curvature change rate of the lane, the estimation section estimating the road parameters at current time based on the traveling marking line calculated by the calculation section and the road parameters previously estimated, a determination section that determines departure of the vehicle from a curve of the lane, and a reset section that, when the determination section determines the departure of the vehicle, resets at least the curvature change rate included in the road parameters previously estimated by the estimation section.

Traveling path estimation apparatus

In an apparatus for recognizing a lane partition line, a pre-branch section setting unit sets a pre-branch section of a road on which an own vehicle is traveling. The pre-branch section extends a section length from a start line that is positioned closer to the own vehicle than a branch location by an offset distance in a traveling direction of the own vehicle. A determination unit determines whether or not a geographical location of the own vehicle is within the pre-branch section. If it is determined that the geographical location of the own vehicle is within the pre-branch section, a recognition unit suppresses recognition of the lane partition line on an diverging road side of the road on which the own vehicle is traveling. The diverging road is another road branching off from the road on which the vehicle is traveling at the branch location.

Apparatus for recognizing lane partition lines

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.

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Aichi-ken, Japan

Shunsuke Suzuki