Abstract: A vehicle location recognition apparatus includes a link determination unit which accurately determines a link traveled by a vehicle from among a plurality of links meeting at a narrow-angle branch point, on the basis of vehicle location information and road information, travel history information representing a route traveled by the vehicle at the branch point. The vehicle location recognition apparatus includes a history information generation unit for generating travel history information for the determined link. The travel history information is stored in a learning database. On the basis of the travel history information, a learning unit generates learned priority information representing the priorities of the respective links meeting at a branch point and used in the determination by the link determination unit.

Abstract: Systems, methods, and programs capture an image of a periphery of a vehicle. The systems, methods, and programs, store predetermined patterns representing conditions of road markings formed on a road surface, detect a road marking on the basis of the captured image, and compare the detected road marking to the predetermined patterns. If the detected road marking matches one of the predetermined patterns, the systems, methods, and programs execute a predetermined action associated with the matching predetermined pattern.

Abstract: A feature extraction method includes: the step of grouping a cluster of features, in which an internal of the respective features is less than or equal to a predetermined grouping interval, to form a feature group, for a plurality of features of which feature information including at least information of a position and a feature type is included in a predetermined feature information storage unit; the step of excluding the feature, not suitable for use in an image recognition process of the feature with respect to image information, from the cluster of the features within the feature group; and the step of extracting a part or all of one or more of the features within the feature group remaining as a result of the exclusion step as a target feature suitable for the use in the image recognition process.

Abstract: A wrong-way-travel warning device comprising a vehicle speed detecting part configured to detect a vehicle speed of a vehicle, a part configured to detect a position of the vehicle, an angle detecting part configured to detect an angle of a vehicular longitudinal direction of the vehicle relative to a lane marking if the vehicle speed of the vehicle becomes less than or equal to a predetermined value, and a warning part configured to issue a warning to an occupant if the position of the vehicle is on a main lane of a highway and if the angle becomes about 90 degrees, is provided.

Abstract: A lane determining device includes: a feature information obtaining unit for obtaining feature information F of a target feature existing in each lane in the traveling direction of a vehicle 30, based on vehicle position information; an image recognizing unit for conducting image recognition processing of a feature type of the target feature in a vehicle lane, with respect to image information; and a lane accuracy determining unit for determining a vehicle lane accuracy for the respective lanes based on a type of a recognized feature fa shown in an image recognition result, feature types Ft1 to Ft4 of the target feature of the respective lanes shown in the feature information F, in accordance with a level of probability for each of the feature types Ft1 to Ft4 of the target feature of the respective lanes is recognized as the type of the recognized feature fa.

Abstract: Feature information collecting apparatuses, methods, and programs acquire vehicle position information that represents the current position of a vehicle, acquire image information for a vicinity of the vehicle, and carry out image recognition processing on recognition target objects that are included in the image information. The apparatuses, methods, and programs store recognition information in a memory that represents a result of the image recognition of the recognition target objects in association with information for the recognition position of the recognition target objects, the recognition position determined based on the vehicle position information.

Abstract: Apparatuses, methods, and programs acquire vehicle position information that represents a current position of a vehicle, acquire image information of a vicinity of the vehicle, and carry out image recognition processing of a target feature that is included in the image information to determine a position of the target feature. The apparatuses, methods, and programs store recognition position information that is based on the acquired vehicle position information and that represents the determined recognition position of the target feature. The apparatuses, methods, and programs determine an estimated position of the target feature based on a set of a plurality of stored recognition position information for the target feature, the plurality of stored recognition position information for the target feature being stored due to the target feature being subject to image recognition processing a plurality of times.

Abstract: Apparatuses, methods and programs store a plurality of target types, each target type having recognition attribute information indicating the likelihood that the target type will be recognized based on a type of road or a type of area. The apparatuses, methods and programs acquire vehicle position information indicating a current position of a vehicle, acquire image information in the vicinity of the vehicle, and acquire road attribute information about a road on which the vehicle is traveling, the road attribute information acquired based on the vehicle position information. The apparatuses, methods and programs determine a target type defining a target for image recognition within the image information, the target type being determined based on the acquired road attribute information and the stored recognition attribute information, and perform image recognition of a target feature included in the image information, the target feature being of the determined target type.

Abstract: Vehicle-position-recognition apparatuses, methods, and programs acquire current position information indicating a current position of a vehicle and acquire road information indicating at least one road based on a connection relationship between plural links. The apparatuses, methods, and programs determine a link where the vehicle travels based on the current position information and the road information and generate travel-history information indicating a route that the vehicle travels at a point where a link is branched based on the determined link. The apparatuses, methods, and programs acquire an image of an area surrounding the vehicle, recognize a recognition target in the acquired image, and store the generated travel-history information in the memory in association with information indicating the recognition of the recognition target.

Abstract: Vehicle behavior learning apparatuses, methods, and programs store pieces of feature information including position information and attribute information of a plurality of target features. The apparatuses, methods, and programs obtain vehicle position information that shows a current position of a vehicle, obtaining image information of surroundings of the vehicle, and obtain one of the stored pieces of feature information corresponding to the surroundings of the vehicle based on the vehicle position information. The apparatuses, methods, and programs perform an image recognition for recognizing a target feature contained in the image information that corresponds to the obtained piece of feature information, detect a behavior of the vehicle that is performed within a predetermined range from a position of the recognized target feature, and store, based on the vehicle position information, the detected behavior in correspondence with information of a position in which the detected behavior was detected.

Abstract: A map data update system includes a first storage portion that stores road network data that describes a road in terms of a connection relationship between a node and a link; an update portion that receives update data and updates the road network data based on the update data; a data obtaining portion that obtains additional data by a means that differs from a means that receives the update data; a second storage portion that stores the additional data including association information that indicates association between the additional data and the link; and a correcting portion that, when update processing of the road network data is executed by the update portion, the association information in the additional data that is associated with the link that is changed by the update processing.

Abstract: A wrong-way-travel warning device comprising a vehicle speed detecting part configured to detect a vehicle speed of a vehicle, a part configured to detect a position of the vehicle, an angle detecting part configured to detect an angle of a vehicular longitudinal direction of the vehicle relative to a lane marking if the vehicle speed of the vehicle becomes less than or equal to a predetermined value, and a warning part configured to issue a warning to an occupant if the position of the vehicle is on a main lane of a highway and if the angle becomes about 90 degrees, is provided.

Abstract: Provided is a driving support device and method that specifies the reliability of information used in a driving support device. The driving support device includes a storage medium that stores one or more programs and accuracy information that specifies the reliability of information of various elements used by one of the programs to provide driving support. The driving support device also includes an execution target program specification unit that specifies what program from the one or more programs is to be executed as the execution target program. An element selection unit selects an element that corresponds to the specified execution target program from the various elements. The device also includes a reliability specification unit that specifies the reliability of information used in the target execution program based on the accuracy information of the selected element.

Abstract: A feature extraction method includes: the step of grouping a cluster of features, in which an internal of the respective features is less than or equal to a predetermined grouping interval, to form a feature group, for a plurality of features of which feature information including at least information of a position and a feature type is included in a predetermined feature information storage unit; the step of excluding the feature, not suitable for use in an image recognition process of the feature with respect to image information, from the cluster of the features within the feature group; and the step of extracting a part or all of one or more of the features within the feature group remaining as a result of the exclusion step as a target feature suitable for the use in the image recognition process.

Abstract: Provided is a reliability evaluation method and apparatus to evaluate the reliability of map information. The apparatus includes an evaluation object value acquisition unit that acquires an evaluation object value from map information stored in a storage medium. A measurement value acquisition unit acquires measurement values for the evaluation object value using a sensor installed in a vehicle. After acquiring the measurement values, a reliability evaluation unit that selects a reliability evaluation method to evaluate the reliability of the evaluation object value based on a current measured value and the dispersion of the measured values.

Abstract: In a case where it is determined that a road surface marking exists within a specified range from a vehicle 2 (YES at S2), the road surface marking is recognized based on an image that has been acquired by a rear camera 3 (S3), an on-road distance from the vehicle 2 to a control object that is associated with the recognized road surface marking is computed (S5 to S7), and in a case where it has been determined that the on-road distance to the control object has become a specified distance (YES at S8), driving guidance and the vehicle control are performed in accordance with the type of the associated control object (S11).

Abstract: A lane determining device includes: a feature information obtaining unit for obtaining feature information F of a target feature existing in each lane in the traveling direction of a vehicle 30, based on vehicle position information; an image recognizing unit for conducting image recognition processing of a feature type of the target feature in a vehicle lane, with respect to image information; and a lane accuracy determining unit for determining a vehicle lane accuracy for the respective lanes based on a type of a recognized feature fa shown in an image recognition result, feature types Ft1 to Ft4 of the target feature of the respective lanes shown in the feature information F, in accordance with a level of probability for each of the feature types Ft1 to Ft4 of the target feature of the respective lanes is recognized as the type of the recognized feature fa.

Abstract: Systems, methods, and programs capture an image of a periphery of a vehicle. The systems, methods, and programs, store predetermined patterns representing conditions of road markings formed on a road surface, detect a road marking on the basis of the captured image, and compare the detected road marking to the predetermined patterns. If the detected road marking matches one of the predetermined patterns, the systems, methods, and programs execute a predetermined action associated with the matching predetermined pattern.

Abstract: Vehicle behavior learning apparatuses, methods, and programs acquire image information of an area around a vehicle and perform image recognition of a particular feature included in the image information. The apparatuses, methods, and programs detect a behavior of the vehicle and acquire relation information indicating the relationship between the detected behavior of the and the recognized particular feature before the recognition of the behavior. The apparatuses, methods, and programs store detected behavior information including behavior property information indicating a property of the detected behavior of the vehicle and the acquired relation information associated with the behavior in a memory and produce learned behavior information indicating a result of learning of the behavior related to the particular feature on the basis of the stored detected behavior information.

Abstract: Vehicle-position-recognition apparatuses, methods, and programs acquire current position information indicating a current position of a vehicle and acquire road information indicating at least one road based on a connection relationship between plural links. The apparatuses, methods, and programs determine a link where the vehicle travels based on the current position information and the road information and generate travel-history information indicating a route that the vehicle travels at a point where a link is branched based on the determined link. The apparatuses, methods, and programs acquire an image of an area surrounding the vehicle, recognize a recognition target in the acquired image, and store the generated travel-history information in the memory in association with information indicating the recognition of the recognition target.