Hitachi, Ltd.

Takehisa Nishida

Mariko Okude

Kazuo Muto

Masayoshi Ishikawa

Atsushi Katou

Hiroyuki Ushiba

Zixian Zhang

The purpose of the present invention is to provide a technology for updating a recognition model so that even if there were errors in recognition of an unknown scene or the like, the scene can be recognized quickly. The present invention is provided with a data analysis unitthat, on the basis of data from an outside recognition unitprovided to a vehicle, acquires from among previously stored recognition models a model approximate to a recognition model recognized by the outside recognition unit, and that reproduces the acquired model in the form of computer graphics images. The data analysis unitis provided with: a difference extraction unitthat compares the reproduced computer graphics images and data from the outside recognition unitand extracts a difference therebetween; an object recognition unitthat recognizes an object relating to the difference extracted by the difference extraction unit; and a scene reconfiguration unitthat creates computer graphics images having the object recognized by the recognition unitreflected therein.

Recognition model distribution system and updating method of recognition model

A system for guiding a driver to an ideal driving pattern in order to eliminate dependency on the driver's driving pattern in a fault diagnosis of an automobile part based on automobile running data, even if the driver's driving pattern is far from the ideal driving pattern. The system comprises a fault diagnosis support device equipped with: a diagnosis model selector for outputting a diagnosis model in which, for a feature value used for an examination of an automobile part, an available range available for making a diagnosis and a reference point are stipulated; a driver model generator generating, as a representative point of the feature value that corresponds to a driver's driving pattern; and a recommendation model generator generating, if the representative point is outside the available range, a recommendation model in which a boundary of the available range is set as a recommendation point.

Fault diagnosis support device

Provided is an automatic operation assistance system comprising: a telematics center () that gives notification to a connected car () in accordance with a request that originated from the connected car (), the notification pertaining to the traveling environment of the connected car () from which the request originated and a sensor evaluation value matching an external field sensor (); and the connected car () that changes, on the basis of the sensor evaluation value notified from the telematics center (), a process for reflecting recognition data of each external field sensor () of the connected car on an automatic operation control of the connected car.

Automatic operation assistance system and automatic operation assistance method

A failure detection device that detects a failure in a plurality of external sensors onboard a vehicle, the failure detection device comprises: an overlapping region storage unit that stores an overlapping region of detection areas of the external sensors; an environment performance storage unit that stores an environment-dependent performance of sensing of the external sensors; an environment information acquisition unit that acquires environment information about the vehicle; a recognition result comparison unit that compares recognition results of an object in the overlapping region from the external sensors; a failure likelihood computation unit that computes a failure likelihood of each external sensor based on a comparison result of the recognition results, the environment information, and the environment-dependent performance; and a failure determination unit that determines a failure in each external sensor based on the failure likelihood of each of the external sensors.

Failure detection device for an external sensor and a failure detection method for an external sensor

A vehicle operation data collection apparatus includes a vehicle operation history DB which accumulates vehicle operation data acquired from a vehicle; and a processor programmed to evaluate excess or deficiency of vehicle operation data accumulated in the vehicle operation history DB for each of abnormality types, on the basis of accuracy information of classification obtained when classifying the abnormality types occurring in the vehicle by machine learning, using vehicle operation data accumulated in the vehicle operation history DB, extract a vehicle suitable for acquiring data of an abnormality type evaluated as data deficiency from a vehicle maintenance history DB as a collection target vehicle, and distribute a collection command instructing collection of operation data to the extracted collection target vehicle.

Vehicle operation data collection apparatus, vehicle operation data collection system, and vehicle operation data collection method

A device diagnostic apparatus according to the present invention includes: a diagnosis model selecting unit that selects a diagnosis model for diagnosing a moving device in accordance with a driving environment of the device; and a diagnosis unit that inputs operation data of the device to the selected diagnosis model, receives an output of a diagnosis result for the device from the diagnosis model, and diagnoses the device.

Device diagnostic apparatus, device diagnostic system and device diagnostic methods

A reporting device that is connected to at least one vehicle, which is controlled based on a result of recognition by an outside recognizer, via a network provides the vehicle with information on a possibility of a failure in outside recognition on the basis of a condition under which a failure in outside recognition has occurred previously. Preliminarily, if a failure such as non-detection or erroneous detection occurs due to an outside recognizer of a connected car, the abnormality is stored while being linked with an external traveling environment such as the position of the vehicle or a weather.

Reporting device

An abnormality detection device includes a space recognition success determination unit which determines whether an outside space recognition device is successful in space recognition from information which contains space recognition information and environment information, an environment dependence recognition failure classifying unit which determines and classifies whether a failure of the space recognition corresponds to any one of a failure type previously stored in an environment dependence recognition failure type storage unit with respect to the space recognition information determined as failing in the space recognition, and an abnormality detection unit which uses the space recognition information determined as not corresponding to any failure type by the environment dependence recognition failure classifying unit to detect an abnormality of the outside space recognition device in the space recognition information determined as failing in the space recognition.

Abnormality detection device and abnormality detection method

An object of the present invention is to grasp information regarding the state of a vehicle (for example, an automobile) that cannot be obtained from an OBD, and to monitor the state of the vehicle. An aspect of the present invention includes: a state estimation unit that estimates the state quantities of a monitoring-target vehicle based on sensor data obtained from sensors mounted on a mobile information terminal in the monitoring-target vehicle using a state estimation device that has learned the relationship between sensor data obtained from sensors mounted on a mobile information terminal in an arbitrary vehicle and state quantities of the arbitrary vehicle in advance; a state evaluation unit that executes evaluation regarding a state of the monitoring-target vehicle on the basis of the estimated state quantities of the monitoring-target vehicle; and an evaluation result output unit that outputs a result of the evaluation.

Vehicle state monitoring apparatus, vehicle state monitoring system, and vehicle state monitoring method

An auto driving control system includes: a situation determining unit which recognizes a situation around the vehicle and determines whether automatic traveling is possible; a drive control unit which performs traveling control when the automatic traveling is possible; a state determining unit which determines whether an occupant is able to drive; and an estimation drive control unit configured such that when the automatic traveling is difficult and it is difficult for the occupant to take over the driving, and when it is determined that execution of a function of the automatic traveling is difficult due to a first sensor, the estimation drive control unit executes the function by using information of a second sensor, and performs traveling control of the vehicle, wherein the automatic traveling is continued based on a control instruction of the estimation drive control unit until the occupant becomes able to take over the driving.

Auto driving control system

To provide an anomality candidate information analysis apparatus capable of early confirming that an unexpected anomality occurs in a monitoring object such as a vehicle. There is provided an anomality candidate information analysis apparatus for analyzing anomality candidate information of a vehicle that is a monitoring object. The anomality candidate information analysis apparatus includes a storage unit and an analysis unit. The storage unit stores monitoring object information regarding the vehicle, environment information regarding an environment around the vehicle, operator information regarding an operator of the vehicle, and anomality candidate information detected in the vehicle in association with each other. The analysis unit extracts the anomality candidate information associated with the monitoring object information, the environment information, and the operator information, and analyzes a dependence degree of the anomality candidate information to the environment information and the operator information.

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Tokyo, Japan

Takehisa Nishida