Abstract: 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.

Abstract: A lane detecting apparatus is provided which obtains at least one type of parameters associated with lane lines on the road and selects one of the lane lines as a reference line using one of the parameters which is most useful in determining the configuration of a lane on a road. The lane detecting apparatus also calculates a lane boundary line using the reference lane line.

Abstract: A boundary line recognition apparatus recognizes a boundary line that demarcates a driving lane in which an own vehicle is driving and includes a candidate detecting unit, a dowel bar determining unit, and a boundary line recognizing unit. The candidate detecting unit detects line types of boundary line candidates that are candidates for the boundary line and a quantity of boundary line candidates of the same line type, based on detection data of the boundary line candidates acquired from a detecting unit that detects the boundary line candidates. The dowel bar determining unit determines whether or not the boundary line candidates are formed by dowel bars embedded in a road, based on the line type and quantity detected by the candidate detecting unit. The boundary line recognizing unit eliminates the boundary line candidates that are determined to be formed by the dowel bars and recognizes the boundary line.

Abstract: In a pitch angle estimation apparatus, an image acquirer sequentially acquires images in a forward or rearward direction of a vehicle. Each image is referred to as a frame. A movement amount calculator extracts a feature point from each of the images acquired by the image acquirer and calculates an amount of movement of the feature point in a vertical direction of the image. A pitch angle calculator calculates a pitch angle of the vehicle based on the amount of movement of the feature point. An output unit outputs the pitch angle calculated by the pitch angle calculator. A low frequency component calculator calculates a low frequency component of the pitch angle calculated by the pitch angle calculator. An output determiner determines whether to output the pitch angle based on the magnitude of the low frequency component calculated by the low frequency component calculator.

Abstract: A lane detecting apparatus is provided which obtains at least one type of parameters associated with lane lines on the road and selects one of the lane lines as a reference line using one of the parameters which is most useful in determining the configuration of a lane on a road. The lane detecting apparatus also calculates a lane boundary line using the reference lane line.

Abstract: 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.

Abstract: The demarcation line recognition device determines the line type and line color of the extracted candidate line, and the presence or absence of an influence of backlight, and determines whether the extracted candidate line constitutes a part of a multiple line. The demarcation line recognition device selects a candidate line corresponding to a demarcation line from extracted candidate lines, using the line type and line color determined, and the determination result of the multiple line determination, and according to the rules of the driving region. When a candidate line determined to be under the influence of backlight constitutes a part of a multiple line, the demarcation line recognition device compares the color information of the candidate lines constituting that multiple line with each other and re-determines the line color of the candidate line determined to be under the influence of backlight.

Abstract: In a pitch angle estimation apparatus, an image acquirer sequentially acquires images in a forward or rearward direction of a vehicle. Each image is referred to as a frame. A movement amount calculator extracts a feature point from each of the images acquired by the image acquirer and calculates an amount of movement of the feature point in a vertical direction of the image. A pitch angle calculator calculates a pitch angle of the vehicle based on the amount of movement of the feature point. An output unit outputs the pitch angle calculated by the pitch angle calculator. A low frequency component calculator calculates a low frequency component of the pitch angle calculated by the pitch angle calculator. An output determiner determines whether to output the pitch angle based on the magnitude of the low frequency component calculated by the low frequency component calculator.

Abstract: In a boundary line recognition apparatus, a boundary line candidate extracting part extracts boundary line candidates from image data obtained by an on-vehicle camera based on known image processing such as pattern matching and Hough transform. One or more kinds of boundary line feature calculating parts calculate one or more likelihoods of each boundary line candidate. The likelihood indicates a degree of probability to be the boundary line. A boundary line feature combining means multiplies the likelihoods of each boundary line candidate and outputs a combined likelihood. A boundary line candidate selecting part selects the boundary line candidate having a maximum likelihood as the boundary line. The boundary line feature calculating part further calculates the likelihood of the boundary line candidate using a dispersion of brightness and an internal edge amount, and changes the likelihood based on an additional likelihood obtained by a driving lane surface feature extracting part.

Abstract: In a boundary line recognition apparatus, a boundary line candidate extracting part extracts boundary line candidates from image data obtained by an on-vehicle camera based on known image processing such as pattern matching and Hough transform. One or more kinds of boundary line feature calculating parts calculate one or more likelihoods of each boundary line candidate. The likelihood indicates a degree of probability to be the boundary line. A boundary line feature combining means multiplies the likelihoods of each boundary line candidate and outputs a combined likelihood. A boundary line candidate selecting part selects the boundary line candidate having a maximum likelihood as the boundary line. The boundary line feature calculating part further calculates the likelihood of the boundary line candidate using a dispersion of brightness and an internal edge amount, and changes the likelihood based on an additional likelihood obtained by a driving lane surface feature extracting part.

Abstract: In an exposure control apparatus for a vehicle-installed camera which captures images of an external scene ahead of the vehicle as respective arrays of picture elements, highest-brightness and lowest-brightness picture elements of each image are excluded from processing for measuring the brightness of a region in the scene ahead of the vehicle, thereby enabling stable measurement of brightness with reduced effects of incident light from oncoming vehicle headlights, dark patches on the road surface, etc.

Abstract: An image processing device determines, cuts and extracts a processing area from an image data monitored by a camera mounted onto a driver's vehicle based on a distance between a front target object and a driver's vehicle, a horizontal position of the driver's vehicle, and a strength of a radar wave transmitted from a radar device and then reflected by objects in front of the driver's vehicle. The radar device is mounted to the driver's vehicle and transmits the radar wave to the front area of the driver's vehicle. The image processing device extracts vertical edges and horizontal edges from the image data in the processing area, and subtracts the horizontal edge values from the vertical edge values, and finally detects whether or not the front target object is a three-dimensional object based on the calculated result of the subtraction of the edges.

Abstract: In a boundary line recognition apparatus, a boundary line candidate extracting part extracts boundary line candidates from image data obtained by an on-vehicle camera based on known image processing such as pattern matching and Hough transform. One or more kinds of boundary line feature calculating parts calculate one or more likelihoods of each boundary line candidate. The likelihood indicates a degree of probability to be the boundary line. A boundary line feature combining means multiplies the likelihoods of each boundary line candidate and outputs a combined likelihood. A boundary line candidate selecting part selects the boundary line candidate having a maximum likelihood as the boundary line. The boundary line feature calculating part further calculates the likelihood of the boundary line candidate using a dispersion of brightness and an internal edge amount, and changes the likelihood based on an additional likelihood obtained by a driving lane surface feature extracting part.

Abstract: A road surface reflection detecting apparatus includes a road recognition unit for recognizing a road in a picture taken by a camera of a road existing in front of a vehicle. A road surface reflection detection unit extracts a picture from the road recognized by the road recognition unit and determines the degree of reflection of light from the surface of the road based on the picture extracted from the road. The picture includes the reflection of light beam radiated from vehicle headlights. If the reflection is determined to be high, the direction or intensity of the light beam from the vehicle headlights is regulated.

Abstract: An image processing device determines, cuts and extracts a processing area from an image data monitored by a camera mounted onto a driver's vehicle based on a distance between a front target object and a driver's vehicle, a horizontal position of the driver's vehicle, and a strength of a radar wave transmitted from a radar device and then reflected by objects in front of the driver's vehicle. The radar device is mounted to the driver's vehicle and transmits the radar wave to the front area of the driver's vehicle. The image processing device extracts vertical edges and horizontal edges from the image data in the processing area, and subtracts the horizontal edge values from the vertical edge values, and finally detects whether or not the front target object is a three-dimensional object based on the calculated result of the subtraction of the edges.

Abstract: In an exposure control apparatus for a vehicle-installed camera which captures images of an external scene ahead of the vehicle as respective arrays of picture elements, highest-brightness and lowest-brightness picture elements of each image are excluded from processing for measuring the brightness of a region in the scene ahead of the vehicle, thereby enabling stable measurement of brightness with reduced effects of incident light from oncoming vehicle headlights, dark patches on the road surface, etc.

Abstract: An apparatus for detecting a direction of a target is provided. The apparatus transmits and receives radio waves through a plurality of transmission/reception channels causing a phase difference in signals to be received through the transmission/reception channels and calculates the direction based on the phase difference. The apparatus comprises a direction calculating device, range determining device, and direction correcting device. The direction calculating device calculates the direction of the target based on the phase difference in the received signals on the assumption that the phase difference is within a range of ?? to +? [rad]. The range determining device determines that the target exists in any of azimuthal angle ranges each corresponding to ranges defined by (2m?1) ? to (2m+1) ? [rad] (m is an integer). The direction correcting device corrects the direction according to a range-determined result.

Abstract: An apparatus for detecting a direction of a target is provided. The apparatus transmits and receives radio waves through a plurality of transmission/reception channels causing a phase difference in signals to be received through the transmission/reception channels and calculates the direction based on the phase difference. The apparatus comprises a direction calculating device, range determining device, and direction correcting device. The direction calculating device calculates the direction of the target based on the phase difference in the received signals on the assumption that the phase difference is within a range of ?? to +? [rad]. The range determining device determines that the target exists in any of azimuthal angle ranges each corresponding to ranges defined by (2m?1)? to (2m+1)? [rad] (m is an integer). The direction correcting device corrects the direction according to a range-determined result.

Abstract: A road surface reflection detecting apparatus includes a road recognition unit for recognizing a road in a picture taken by a camera of a road existing in front of a vehicle. A road surface reflection detection unit extracts a picture from the road recognized by the road recognition unit and determines the degree of reflection of light from the surface of the road based on the picture extracted from the road. The picture includes the reflection of light beam radiated from vehicle headlights. If the reflection is determined to be high, the direction or intensity of the light beam from the vehicle headlights is regulated.