Mitsubishi Electric Corporation

Splice Sleeve Japan, Ltd.

Mitsubishi Denki Kabushiki Kaisha

Denki Kagaku Kogyo Kabushiki Kaisha

Mitsubishi Electric Corpotation

Mitsubishi Electric Coproration

Masahiro Abukawa

Shu Murayama

Naoyuki Tsushima

Michinori Yoshida

Takefumi Hasegawa

Takeshi Mitsui

Akira Hirata

Masahiko Tanimoto

Yasuaki Takimoto

Junya Ujiie

Yoshihiro Nakai

Yoshiaki Watanabe

Tsutomu Matsubara

Kenji Sakata

Hisao Nakano

Takehisa Mizuguchi

Shinji Akatsu

Yohei Miki

Nobuyoshi Okumura

Takehiko Hanada

Yoshie Imai

Ken Miyamoto

Kentaro Ishikawa

Yosuke Ishiwatari

Eisuke Yonezawa

Kumiko Ikeda

Tetsuo Otsuka

Tooru Shiraiwa

Tooru Yagi

Heikan Izumi

Yushi Fukuchi

Haruo Nakata

A course prediction device () includes a blind spot calculation unit () and a prediction unit (). The blind spot calculation unit () acquires a sensing result sequentially from a sensor which is arranged in a mobile object and which detects whether an object exists, and calculates, based on sensor information, a blind spot area expressing such an area that an object existing therein cannot be detected by the sensor. The blind spot calculation unit () also detects an object entering the blind spot area based on the sensor information. The prediction unit () predicts a course in the blind spot area of the detected object based on the sensing result.

Course prediction device, computer readable medium, and course prediction method

A driving monitoring device () decides an applicable collision pattern that applies to a collision pattern of a case where a vehicle () collides with a mobile object, based on a velocity vector of the vehicle, a velocity vector of the mobile object, and so on. Subsequently, the driving monitoring device calculates a time until collision, which is a time taken until the vehicle collides with the mobile object, in the applicable collision pattern. Then, the driving monitoring device calculates a danger level of an accident in which the vehicle collides with the mobile object, based on the applicable collision pattern and the time until collision.

Driving monitoring device and computer readable medium

A failure detection apparatus () acquires, as target data, sensor data output in a past reference period by a sensor (), such as a millimeter wave radar or LiDAR (Light Detection And Ranging), mounted on a moving body (). The failure detection apparatus () determines whether detected data indicating a characteristic of a detected object indicated by normal data, which is sensor data output when the sensor () is normal, is included in the acquired detected data in the past reference period. In this way, the failure detection apparatus () determines whether a failure has occurred in the sensor ().

Failure detection device, failure detection method, and failure detection program

A first image-data acquisition unit () acquires a plurality of pieces of image data in which different areas in a facility in which an autonomous driving vehicle conducts autonomous traveling are shown. A priority setting unit () analyzes a status shown in each of the plurality of pieces of image data and sets a priority to each image data. A first image-data display unit () decides a display mode at a time of displaying the plurality of pieces of image data according to the priority set by the priority setting unit ().

Information processing device, information processing method, and computer readable medium

An acquisition unit of a falling object detection apparatus installed and used in a first vehicle acquires a depth image of a second vehicle, on which a load is mounted and which is traveling in front of the first vehicle, and of the area around the second vehicle. A determination unit of the falling object detection apparatus determines whether the load has not made a movement different from that of the second vehicle, using the depth image acquired by the acquisition unit. A detection unit of the falling object detection apparatus detects a fall of the load based on a result of determination by the determination unit.

Falling object detection apparatus, in-vehicle system, vehicle, and computer readable medium

A detected data acquisition unit () acquires detected data outputted during a past reference period by a sensor () mounted on a moving body (). A peripheral data acquisition unit () acquires peripheral data detected by a peripheral body existing on peripheral of the moving body (). A failure determination unit () determines whether or not there is a failure in the sensor () based on whether or not the detected data includes detected data that identifies a detected content of which difference from a peripheral content identified from the peripheral data is within a reference scope.

Failure detection apparatus, failure detection method, and computer readable medium

A crossing detection unit () detects a pedestrian who is about to cross a roadway on which a vehicle () travels. A behavior detection unit () detects a behavior of a nearby vehicle traveling around the vehicle (). A stop determination unit () determines whether or not to stop the vehicle () in view of the detection of the pedestrian who is about to cross the roadway by the crossing detection unit () and the behavior of the nearby vehicle detected by the behavior detection unit (). A vehicle control unit () stops the vehicle () before the pedestrian when the stop determination unit () determines to stop the vehicle.

Driving assistance system

A direction identification unit () identifies a traveling direction in which a surrounding vehicle travels in a partial region of a region indicated by image information () obtained by photographing using a camera (). A feature amount acquisition unit () acquires a reference feature amount () being a feature amount computed from a reference image corresponding to the identified traveling direction. A vehicle determination unit () computes an image feature amount being a feature amount of the image information of the partial region and compares the computed image feature amount with the acquired reference feature amount (), thereby determining whether the surrounding vehicle is present in the partial region.

Vehicle determination apparatus, vehicle determination method, and computer readable medium

A driving support apparatus () converts at least one of a first map () and a second map () so that the first map () and the second map () become three-dimensional maps in a same coordinate system. The first map () is a three-dimensional map indicating three-dimensional positions of objects around a vehicle (). The second map () is a three-dimensional map indicating three-dimensional positions of objects around an external apparatus () that is one of a roadside apparatus () and a different vehicle () from the vehicle (). Then, the driving support apparatus () synthesizes the first map () and the second map () after the conversion, thereby generating a composite map ().

Driving support apparatus, driving support system, driving support method, and computer readable recording medium

A driver assistance system according to the present invention has an other-vehicle information acquisition unit that acquires travel direction information of an other-vehicle; a storage unit in which a spot where the visibility of a driver in a vehicle is reduced and information on a direction, associated with the spot, in which the visibility of the driver of the vehicle is reduced are stored in association with each other; a visibility determination unit that determines whether or not the visibility of a driver in the other-vehicle is reduced on the basis of the travel direction information acquired by the other-vehicle information acquisition unit and the information on the direction in which the visibility is reduced stored in the storage unit; and a warning processing unit that warns a driver of an own-vehicle that the visibility of the driver in the other-vehicle is reduced if the visibility determination unit determines that the visibility of the driver in the other-vehicle is reduced.

Driver assistance system

An image display systemin accordance with the present invention is configured with a navigation deviceand an image display devicewhich are connected to each other via a network. The navigation devicetransmits a drawing setting for specifying a method of drawing a vertex string showing a feature of a component of an image when a network connection with the image display deviceis established, and transmits image data including the vertex string when the image display device draws an image, and the image display device receives the drawing setting from the image transmission device, corrects the drawing setting on the basis of the display ability of the image transmission device and its own display ability, and, when receiving the image data from the image transmission device, draws and display the image by using the above-mentioned drawing setting corrected thereby.

Image display device, image transmission device, and image display system using these devices

A collision risk calculation device includes: a movement information obtaining unit that obtains a speed and a movement direction of an obstacle; and a risk map generator that generates a risk map indicating a range within which the obstacle can exist after one unit of time and degree of risk of collision of an own vehicle with the obstacle within the range, on a basis of the speed and the movement direction of the obstacle obtained by the movement information obtaining unit, wherein the risk map generator changes the range in left and right directions with respect to a traveling direction of the obstacle, on a basis of the speed of the obstacle in the traveling direction.

Collision risk calculation device, collision risk display device, and vehicle body control device

When a CPU core ()and a CPU core ()share the execution of an OS (), a program (A), and a program (B), the CPU core ()withdraws from sharing the execution of the OS (), the program (A), and the program (B), starts a replacement OS which replaces the OS (), and switches an OS on which the program (A)operates from the OS ()to the replacement OS. After the OS on which the program (A)operates is switched to the replacement OS, the CPU core ()terminates the execution of the OS ().

Executing an operating system in a multiprocessor computer system

A home security system includes an in-home system and a vehicle-mounted system, wherein the in-home system includes an in-home sensor that is mounted in a home and is capable of detect a state of the home, and an in-home communication module that is capable of communicating with the vehicle-mounted system to sense an abnormality from information of the in-home sensor, and wherein the vehicle-mounted system includes a vehicle-mounted device that is mounted on a vehicle that is capable of a vehicle outside output, and a vehicle-mounted communication module that is capable of communicating with the in-home system via the in-home communication module, and when the in-home system senses the abnormality, an instruction is received from the in-home system via the in-home communication module and vehicle-mounted communication module to deal with the abnormality using the vehicle-mounted device according to the instruction.

Home security system and vehicle-mounted system used by same

An electronic key system includes a lock-side terminal that is mounted in a locked object and capable of at least locking and unlocking the locked object, and a portable terminal capable of sending and receiving the electronic key to and from the lock-side terminal mounted in the locked object and the other portable terminals, and when receiving a request from the one portable terminal, the lock-side terminal generates the electronic key at random, and sends the randomly generated electronic key to the one portable terminal.

Growing community of inventors

Tokyo, Japan

Masahiro Abukawa