Abstract: In a driving-state data storage apparatus, a collector collects, from each of vehicles on a target travelling road, a value of data indicative of a driving state of the corresponding vehicle to correspondingly obtain driving-state data values for the target road. A data allocator divides, based on similarity among the driving-state data values, the target traveling road into a plurality of traveling segments, and extracts, from the driving-state data values, data values for each of the divided travelling segments. The data values extracted for each of the travelling segments are similar to each other. The data allocator allocates a distribution of the extracted data values for each of the divided travelling segments to the corresponding one of the divided travelling segments as a feature distribution. A storage unit stores the feature distribution allocated for each of the travelling segments.

Abstract: A drive support apparatus includes a data collection part that collects driving behavior data of drivers, a classification part that performs clustering of the driving behavior data to form small clusters, an integration part that integrates, in accordance with contents of predetermined drive supports, the small clusters to thereby form support clusters each showing tendency of driving behavior of the drivers for each kind of the drive supports, an object data acquisition part that acquires, as object data, the driving behavior data regarding a support object driver to be supported, an estimation part that estimates, as a belonging cluster, one of the support clusters to which the support object driver belongs for each kind of the drive supports by comparing the object data with the support cluster information accumulated by the integration part.

Abstract: A drive assist apparatus includes a data collection part that collects driving behavior data representing driving maneuvers and vehicle behaviors caused by the driving maneuvers for each drivers, a classification part that classifies the driving behavior data into a plurality of clusters each showing a tendency of driving behavior of the drivers by clustering the driving behavior data, a storage part that stores cluster information representing a driving behavior characteristic of each of the clusters, a subject data acquisition part that acquires, as subject data, the driving behavior data for a subject driver to be assisted, an estimation part that estimates, as a corresponding cluster, one of the clusters to which the subject driver is assumed to belong by comparing the subject data with the cluster information stored in the storage part, and an assist providing part that provides a drive assist depending on the estimated corresponding cluster.

Abstract: In a system, a behavior description generator extracts a feature portion from at least one of segmented behavior-data sequences corresponding to at least one target driving situation included in sequential driving situations, and generates behavior-description information indicative of a description of a driver's behavior associated with the at least one target driving situation. An event description generator sequentially detects traffic events in at least one environmental data sequence indicative of time-series driving environments of a vehicle. The event description generator generates event-description information including a description indicative of each of the detected traffic events. A context description generator extracts, from the sequentially detected traffic events, one target traffic event that is detected immediately adjacent to the feature portion.

Abstract: In an object identification device, each score calculator extracts a feature quantity from the image, and calculates a score using the extracted feature quantity and a model of the specified object. The score represents a reliability that the specified object is displayed in the image. A score-vector generator generates a score vector having the scores as elements thereof. A cluster determiner determines, based on previously determined clusters in which the score vector is classifiable, one of the clusters to which the score vector belongs as a target cluster. An object identifier identifies whether the specified object is displayed in the image based on one of the identification conditions. The one of the identification conditions is previously determined for the target cluster determined by the cluster determiner.

Abstract: A drive video recording device is provided. The drive video recording device creates a summarized moving image in which the inputted video is culled such that a playback speed of the video of the time period during which the amount of information is smaller is faster than a playback speed of the video of the time period during which the amount of information is larger, and stores the summarized moving image in a storage section.

Abstract: A drive data collection system includes an in-vehicle system and an information center. The in-vehicle system includes a data collector that repeatedly collects measurement values indicative of various indexes regarding a state of a subject vehicle, a model memory that memorizes model information regarding discretization rules that are shared by each of participating vehicles in the system, and a data discretizer that discretizes drive data, which includes time-series measurement values collected by the data collector, into multiple data parts according to the model information. The information center includes a data accumulator that accumulates the discretized drive data in a server. The in-vehicle system sends the discretized drive data to the information center through a communicator. Therefore, the drive data collection system efficiently collects the drive data in a versatilely-utilizable manner for the analysis of general driving practices/behaviors.

Abstract: In a system, a behavior description generator extracts a feature portion from at least one of segmented behavior-data sequences corresponding to at least one target driving situation included in sequential driving situations, and generates behavior-description information indicative of a description of a driver's behavior associated with the at least one target driving situation. An event description generator sequentially detects traffic events in at least one environmental data sequence indicative of time-series driving environments of a vehicle. The event description generator generates event-description information including a description indicative of each of the detected traffic events. A context description generator extracts, from the sequentially detected traffic events, one target traffic event that is detected immediately adjacent to the feature portion.

Abstract: In an object identification device, each score calculator extracts a feature quantity from the image, and calculates a score using the extracted feature quantity and a model of the specified object. The score represents a reliability that the specified object is displayed in the image. A score-vector generator generates a score vector having the scores as elements thereof. A cluster determiner determines, based on previously determined clusters in which the score vector is classifiable, one of the clusters to which the score vector belongs as a target cluster. An object identifier identifies whether the specified object is displayed in the image based on one of the identification conditions. The one of the identification conditions is previously determined for the target cluster determined by the cluster determiner.

Abstract: A drive video recording device is provided. The drive video recording device creates a summarized moving image in which the inputted video is culled such that a playback speed of the video of the time period during which the amount of information is smaller is faster than a playback speed of the video of the time period during which the amount of information is larger, and stores the summarized moving image in a storage section.