Abstract: A map reliability determination apparatus includes a microprocessor and a memory coupled to the microprocessor. The microprocessor is configured to perform: acquiring a traveling trajectory of a predetermined section on which a subject vehicle has traveled; recognizing, based on a map information around the subject vehicle, a pair of left and right lane boundary lines which defines a lane on which the subject vehicle has traveled in the predetermined section; calculating a deviation amount between the traveling trajectory acquired in the acquiring and the pair of left and right lane boundary lines recognized in the recognizing; determining a reliability of the pair of left and right lane boundary lines recognized in the recognizing based on the deviation amount calculated in the calculating; and outputting the reliability information including a determination result of the reliability in the determining.

Abstract: A map generation apparatus including a division line detection part, a feature point detection part and a microprocessor. The microprocessor is configured to perform generating a first map including position information of the division line detected by the division line detection part, generating a second map including position information of the feature points detected by the feature point detection part, and determining whether a position of the division line has changed, the determining including determining that the position of the division line has changed when a degree of difference between two first maps respectively generated at a first time point and a second time point after the first time point is a first predetermined degree or more and a degree of difference between two second maps respectively generated at the first time point and the second time point is a second predetermined degree or more.

Abstract: A map generation apparatus including an external circumstance detection part and a microprocessor. The microprocessor is configured to perform detecting a travel trace of a subject vehicle, associating a front lane before entering an intersection with a rear lane after passing through the intersection, and generating a map of a traveling lane from the front lane to the rear lane. The traveling lane includes a first lane and a second lane adjacent to the first lane or branching from the first lane. The microprocessor is configured to perform the associating including associating a first front lane with a first rear lane based on the travel trace and associating a second front lane adjacent to the first front lane with the second rear lane adjacent to the first rear lane or the first front lane with the second rear lane based on the external circumstance.

Abstract: A map creation device includes a processor, and the processor is configured to execute a program to acquire an image captured by a camera mounted in a vehicle, estimate a first position indicating a position of the vehicle and an error of the first position based on information indicating a traveling state of the vehicle, estimate a second position indicating the position of the vehicle and an error of the second position based on radio waves transmitted from artificial satellites, set position information of the vehicle preferentially using one position with a smaller error of the first position and the second position, and create a map of places in which the vehicle has traveled based on the set position information of the vehicle and the image.

Abstract: A map creation device includes a processor, and the processor is configured to execute a program to acquire an image captured by a camera mounted in a vehicle, estimate a first position indicating a position of the vehicle and an error of the first position based on information indicating a traveling state of the vehicle, estimate a second position indicating the position of the vehicle and an error of the second position based on radio waves transmitted from artificial satellites, set position information of the vehicle preferentially using one position with a smaller error of the first position and the second position, and create a map of places in which the vehicle has traveled based on the set position information of the vehicle and the image.

Abstract: A vehicle position estimation apparatus includes a microprocessor configured to perform recognizing a moving object included in a detection region specified by a detection data acquired by a detection unit mounted on a vehicle, partitioning the detection region specified by the detection data acquired by the detection unit into a first region including the moving object and a second region not including the moving object, extracting a feature point of the detection data from the second region, and executing a predetermined processing based on the feature point corresponding to the second region among the extracted feature points extracted. The microprocessor is configured to execute at least one of a processing of generating a point cloud map using the extracted feature point and a processing of estimating a position of the vehicle based on a change over time in a position of the acquired detection data.

Abstract: A performance predicting apparatus includes an approximate model storage unit configured to store approximate models each of which is associated with one of categories, and which are used to calculate functional performance based on feature values, a feature value extracting unit configured to extract the feature values from shape data representing a shape of an object, a selection unit configured to select one of the approximate models to be used from the approximate models stored in the approximate model storage unit depending on the feature values extracted by the feature value extracting unit, and a performance calculating unit configured to calculate functional performance based on the feature values extracted by the feature value extracting unit using the approximate model selected by the selection unit.

Abstract: A performance predicting apparatus includes an approximate model storage unit configured to store approximate models each of which is associated with one of categories, and which are used to calculate functional performance based on feature values, a feature value extracting unit configured to extract the feature values from shape data representing a shape of an object, a selection unit configured to select one of the approximate models to be used from the approximate models stored in the approximate model storage unit depending on the feature values extracted by the feature value extracting unit, and a performance calculating unit configured to calculate functional performance based on the feature values extracted by the feature value extracting unit using the approximate model selected by the selection unit.