Abstract: Provided is an object detection device capable of improving efficiency while ensuring detection accuracy. An object detection device 1 includes a point cloud acquisition unit 201 that acquires point cloud data of an object according to a scanning result of a LiDAR 101, an object detection unit 204 that detects an object based on the point cloud data, and a reliability determination unit 205 that determines a reliability in a detection result of the object detection unit 204. The point cloud acquisition unit 201 controls the scanning range and the irradiation density of the LiDAR 101 on the basis of the reliability.

Abstract: An apparatus for recognizing a division line on a road from an image captured by a camera includes: a processing area setting unit to set a processing area to the image; a statistics calculation unit to calculate statistics of the image in the processing area; a threshold value setting unit to set a plurality of threshold values on the basis of the statistics; a division line feature point extraction unit to classify a plurality of pixels contained in the image on the basis of the white line threshold value and the road surface threshold value and extracts feature points of the division line on the basis of classification results of the plurality of pixels; and a division line decision unit configured to decide the division line on the basis of the feature points extracted by the division line feature point extraction unit.

Abstract: A section line recognition device is realized which can determine a line type of a section line in a road surface with high accuracy. In step 301, a feature amount is extracted from an image captured by each camera. This step corresponds to a process of a feature point extraction unit. In the next step 302, the extracted feature amount is transformed into bird's-eye view coordinates which is common coordinates. This step corresponds to a process of a coordinates transformation unit. Next, in step 303, a camera to be selected is determined. This step is a process of a camera determination unit. Next, in step 304, the state transition at the appearance position of the feature point on the bird's-eye view coordinates is determined using feature point coordinates of the camera selected in step 303. This step is a process of a state transition determination unit. Finally, in step 305, the line type is determined. This step is a process of a line type determination unit.

Abstract: Provided is a travel road recognition device that can accurately recognize a travel road end of a travel road on which an own vehicle travels. A travel road recognition device of the present invention is a travel road recognition device that recognizes the travel road end of the travel road on which an own vehicle 301 travels, and includes: a laser radar 101 that emits a laser bean from the own vehicle 301 toward the travel road; a road surface determination unit 203 that obtains a cross slope of the travel road based on coordinate values of a point cloud obtained by the laser radar 101; and a road end determination unit 204 that obtains a change point at which a slope angle changes in the cross slope of the travel road obtained by the road surface determination unit 203, and obtains coordinate values of at least one travel road end of both sides in a cross direction of the travel road based on the coordinate values of the change point.

Abstract: The present invention addresses the problem of enabling an accurate determination of line type using a plurality of cameras.

Abstract: An apparatus for recognizing a division line on a road from an image captured by a camera includes: a processing area setting unit to set a processing area to the image; a statistics calculation unit to calculate statistics of the image in the processing area; a threshold value setting unit to set a plurality of threshold values on the basis of the statistics; a division line feature point extraction unit to classify a plurality of pixels contained in the image on the basis of the white line threshold value and the road surface threshold value and extracts feature points of the division line on the basis of classification results of the plurality of pixels; and a division line decision unit configured to decide the division line on the basis of the feature points extracted by the division line feature point extraction unit.

Abstract: The present invention addresses the problem of enabling an accurate determination of line type using a plurality of cameras.

Abstract: A section line recognition device is realized which can determine a line type of a section line in a road surface with high accuracy. In step 301, a feature amount is extracted from an image captured by each camera. This step corresponds to a process of a feature point extraction unit. In the next step 302, the extracted feature amount is transformed into bird's-eye view coordinates which is common coordinates. This step corresponds to a process of a coordinates transformation unit. Next, in step 303, a camera to be selected is determined. This step is a process of a camera determination unit. Next, in step 304, the state transition at the appearance position of the feature point on the bird's-eye view coordinates is determined using feature point coordinates of the camera selected in step 303. This step is a process of a state transition determination unit. Finally, in step 305, the line type is determined. This step is a process of a line type determination unit.

Abstract: The obstacle detection device comprises: a first camera installed on a moving vehicle used for photographing a frontward or rearward view of the vehicle; a second camera installed on the vehicle used for photographing a sideward view of the vehicle; a parking space detection unit for detecting a parking space on the basis of an image obtained by photographing by the first camera; a memory unit for storing a real-space area of the parking space; a motion acquisition unit for acquiring information about behaviors of the vehicle; an obstacle calculation unit for calculating information about an obstacle present in the vicinity of the parking space on the basis of multiple images obtained by photographing by the second camera at different points in time; and a processing area setting unit for controlling, the calculation by the obstacle calculation unit.

Abstract: The obstacle detection device comprises: a first camera installed on a moving vehicle used for photographing a frontward or rearward view of the vehicle; a second camera installed on the vehicle used for photographing a sideward view of the vehicle; a parking space detection unit for detecting a parking space on the basis of an image obtained by photographing by the first camera; a memory unit for storing a real-space area of the parking space; a motion acquisition unit for acquiring information about behaviors of the vehicle; an obstacle calculation unit for calculating information about an obstacle present in the vicinity of the parking space on the basis of multiple images obtained by photographing by the second camera at different points in time; and a processing area setting unit for controlling, the calculation by the obstacle calculation unit.

Abstract: It is an object of the present invention to provide a maintenance service method capable of reducing the number of machine parts to be replaced while suppressing the number of times of failures of an apparatus even when an accurate failure probability distribution cannot be estimated concerning single machine parts. Solving means of the present invention is characterized by setting, according to at least one of a failure probability distribution and a performance deterioration probability distribution set for each of machine part types, the number of machine parts to be replaced, setting machine part replacement priority from at least one of the probability distribution and an operation situation or a machine part state, and listing, according to the machine part replacement priority, machine parts equivalent to the number of machine parts to be replaced.

Abstract: An in-vehicle running-environment recognition apparatus including an input unit for inputting an image signal from in-vehicle imaging devices for photographing external environment of a vehicle, an image processing unit for detecting a first image area by processing the image signal, the first image area having a factor which prevents recognition of the external environment, an image determination unit for determining a second image area based on at least any one of size of the first image area, position thereof, and set-up positions of the in-vehicle imaging devices having the first image area, an environment recognition processing being performed in the second image area, the first image area being detected by the image processing unit, and an environment recognition unit for recognizing the external environment of the vehicle based on the second image area.

Abstract: A method for geographic interpolation of traffic data in a vehicle navigation system in which the navigation system includes a map database divided into geographic meshes. Each mesh includes a plurality of road links of different types. That data also includes a first set of meshes containing traffic flow data while a mutually exclusive second set of meshes contains no such traffic flow data. A border between the first and second set of meshes is first identified and thereafter a blend zone of blend meshes is created by selecting at least one mesh adjacent the border so that the blend mesh is interposed between the first and second set of meshes. Thereafter, the traffic data for each type of road link in the blend mesh is adjusted to a value intermediate the first and second set of adjacent meshes for each type of road link and the blend mesh data is then stored.

Abstract: An in-vehicle running-environment recognition apparatus including an input unit for inputting an image signal from in-vehicle imaging devices for photographing external environment of a vehicle, an image processing unit for detecting a first image area by processing the image signal, the first image area having a factor which prevents recognition of the external environment, an image determination unit for determining a second image area based on at least any one of size of the first image area, position thereof, and set-up positions of the in-vehicle imaging devices having the first image area, an environment recognition processing being performed in the second image area, the first image area being detected by the image processing unit, and an environment recognition unit for recognizing the external environment of the vehicle based on the second image area.

Abstract: In a text document processing apparatus, there is provided standard knowledge network data composed of networked phrases having strong mutual relation to each other, the phrases being selected from a knowledge field including contents of a text document to be examined. In addition, there is provided a document knowledge preparing function that prepares knowledge network data of the document to be examined, the knowledge network data being composed of networked phrases having strong mutual relation to each other, the phrases being selected from the text document. Further, a processing unit that checks a specified word constituting the knowledge network data of the document to be examined and a standard knowledge network data, and in a case when information of phrases which are networked to the specified word are different from each other, outputs difference information including information of the specified word.

Abstract: An in-vehicle running-environment recognition apparatus including an input unit for inputting an image signal from in-vehicle imaging devices for photographing external environment of a vehicle, an image processing unit for detecting a first image area by processing the image signal, the first image area having a factor which prevents recognition of the external environment, an image determination unit for determining a second image area based on at least any one of size of the first image area, position thereof, and set-up positions of the in-vehicle imaging devices having the first image area, an environment recognition processing being performed in the second image area, the first image area being detected by the image processing unit, and an environment recognition unit for recognizing the external environment of the vehicle based on the second image area.

Abstract: A traffic information providing system externally acquires traffic information including information relating to the travel time of a link, calculates a travel time for a non-provision link to which no travel time is provided through estimate/complement operation. The estimate/complement operation is carried out with use of travel times, emergencies, travel times of links in the vicinity of the non-provision link, and so on, obtained in the near past. The system stores and statistically processes the externally-acquired traffic information, and also estimates a travel time in the near future. When there is an abnormality in the acquired traffic information, the system deletes the abnormality, regards the information as a non-provision link, calculates a probability distribution of travel times of links, calculates a probability distribution of travel times of the entire route made up of a plurality of links, and also calculates a probability for a specific travel time range.

Abstract: A navi-server which is provided with information from a traffic information providing center, and presents and provides information made on the information to a terminal is characterized by being equipped with a first storage means storing the information provided from the traffic information providing center; a traffic jam statistical making means which makes traffic jam statistical information including traffic jam information in a predetermined point and a predetermined zone as well as a reliability of the traffic jam information, based on information stored in the first storage means; and a second storage means storing information made by the traffic jam statistical making means, wherein the navi-server presents and provides the information stored in the second storage means to the terminal, based on a request of the terminal and at a predetermined timing.

Abstract: In conventional systems using an onboard camera disposed rearward of a vehicle for recognizing an object surrounding the vehicle, the object is recognized by the camera disposed rearward of the vehicle. In the image recognized by the camera, a road surface marking taken by the camera appears at a lower end of a screen of the image, which makes it difficult to predict a specific position in the screen from which the road surface marking appears. Further, an angle of depression of the camera is large, and it is a short period of time to acquire the object. Therefore, it is difficult to improve a recognition rate and to reduce false recognition. Results of recognition (type, position, angle, recognition time) made by a camera disposed forward of the vehicle, are used to predict a specific timing and a specific position of a field of view of a camera disposed rearward of the vehicle, at which the object appears.

Abstract: A traffic information providing system externally acquires traffic information including information relating to the travel time of a link, calculates a travel time for a non-provision link to which no travel time is provided through estimate/complement operation. The estimate/complement operation is carried out with use of travel times, emergencies, travel times of links in the vicinity of the non-provision link, and so on, obtained in the near past. The system stores and statistically processes the externally-acquired traffic information, and also estimates a travel time in the near future. When there is an abnormality in the acquired traffic information, the system deletes the abnormality, regards the information as a non-provision link, calculates a probability distribution of travel times of links, calculates a probability distribution of travel times of the entire route made up of a plurality of links, and also calculates a probability for a specific travel time range.