Toyota Jidosha Kabushiki Kaisha

Kabushiki Kaisha Toyota Chuo Kenkyusho

Aisin Seiki Kabushiki Kaisha

Nagoya University

Denso Corporation

Yoshiki Ninomiya

Eiichi Ono

Hiroaki Takada

Yoshihiro Adachi

Junya Kasugai

Isahiko Tanaka

Kiyokazu Sunami

Yoshikatsu Kisanuki

Nobuyuki Shiraki

Takeshi Hayashi

Shigeharu Teshima

Gunji Sugimoto

Takero Hongo

Arata Takahashi

Yousuke Watanabe

Kazunori Furukawa

Michinori Ando

Hiroaki Kataoka

Katsuhiko Iwazaki

Seiji Kawakami

Hisashi Satonaka

Takuhiro Omi

Tomohiko Endo

Toru Sugiyama

Yuichi Kubota

Yuji Muragishi

Hideyuki Iwakiri

Shinichi Kojima

Akira Matsui

Keiichi Shimaoka

Takashi Hiramaki

Jun Adachi

Yoshikazu Hattori

Yoshinao Takemae

Takashi Naito

Yuichi Tanaka

Norio Fujitsuka

Satoru Nakanishi

Yuzo Yamamoto

Hideo Arakawa

Kazuo Miki

Koichi Tange

Takayuki Morikawa

Keiichi Watanabe

Yuki Yoshihara

Yoshikatsu Kimura

Tetsuzou Inoue

Yojiro Koike

Kenya Sato

Kentaro Takaki

Eijiro Takeuchi

A vehicle driving support system includes a detection part detecting an object; an area classification part classifying areas other than a presence area where the object detected by the detection part is present into an empty area and an unknown area, the empty area being such an area that it is determined that no object is present and an unknown area being such an area that whether an object is present is unknown; and a control part guiding a vehicle to the empty area.

Vehicle driving support system

A driving assistance device includes a driving situation acquisition unit that acquires driving situations of vehicles that may collide with each other, a driving characteristics acquisition unit that acquires driving characteristics of drivers of the vehicles, a driving action determination unit that determines driving actions that allow the vehicles to avoid collision with each other in the driving situation acquired by the driving situation acquisition unit and that match the driving characteristics acquired by the driving characteristics acquisition unit, and a driving action instruction unit that instructs the vehicles about the driving actions determined by the driving action determination unit.

Driving assistance device and driving assistance method

A position estimation system estimates a position of a mobile unit including a camera that captures an image of an area around the mobile unit. The system includes an ECU configured to store a plurality of pieces of map information, the plurality of pieces of map information respectively including a plurality of pieces of image information and respectively including a plurality of pieces of first positional information. The image information corresponding to a plurality of images respectively captured at a plurality of points within a predetermined range, the first positional information being acquired based on information other than the image information and respectively corresponding to the points, environmental conditions of the map information when the images were captured are different from each other, acquire an image captured by the camera, and estimate the position of the mobile unit based on the image acquired by the ECU and the map information.

Position estimation system, position estimation method and mobile unit

Detecting with good precision an eye inside corner position and an eye outside corner position as face feature points even when the eye inside corner and/or the eye outside corner portions are obscured by noise. First eyelid profile modeling is performed with a Bezier curve expressed by a fixed control point Pindicating an eye inside corner first position detected in an image, a fixed control point Pindicating an eye outside corner first position, a control point Pcorresponding to an upper eyelid position candidate (first parameter), and a control point Pcorresponding to a lower eyelid position candidate (second parameter). Then in a second eyelid profile model with fixed Pand Pof the first eyelid profile model having the highest fitting evaluation value &#x3bb; to the eyelid profile in the image, the values of a control point Pindicating an eye inside corner position candidate (third parameter) and a control point Pindicating an eye outside corner candidate (fourth parameter) at a maximum of a fitting evaluation value &#x3bb; when changing the values of the control point Pand control point Pare determined as an eye inside corner second position and an eye outside corner second position, respectively.

Face feature point detection device and program

The invention provides a vehicle motion control device capable of realizing optimum avoidance control in the case of an emergency. The vehicle motion control device includes an external environment detection unit for detecting external environment, and a travel state detection unit for detecting a travel state of a driver's vehicle. An obstruction is detected based on the external environment detected by the external environment detection unit, and an environment map indicating obstructions is created. A control device estimates a plurality of possible avoidance actions for avoiding an obstruction based on the environment map and the travel state of the driver's vehicle detected by the travel state detection unit. The control device estimates collision damage according to each avoidance action estimated by the avoidance action estimation unit, and selects an appropriate avoidance action based on the estimated collision damage. The control device controls a vehicle such that the selected avoidance action is carried out.

Vehicle motion control device

A collision behavior control apparatus which comprises a contacting portion disposed in a portion of the front of a vehicle, and which, at the time of collision against a pedestrian or a two-wheeler with a rider riding thereon, controls the behavior of the pedestrian or the two-wheeler rider by pushing the pedestrian or the two-wheeler rider separated from the two-wheeler with the contacting portion, wherein the pedestrian or the two-wheeler rider is pushed by the contacting portion such that the pedestrian or the two-wheeler rider is not bumped up onto the hood, whereby the pedestrian or the two-wheeler rider is moved to the vehicle side.

Collision behavior control apparatus

An object determining apparatus is disclosed which is structured such that right and left disparity images are acquired from different view points, disparity of corresponding points in the right and left images is computed, information relating to the points for which disparity is computed is voted to respective blocks of a disparity map that arranges blocks with one side corresponding to disparity, other side corresponding to image lateral position, and these sides being elongated with increasing disparity. An attribute of three dimensional object is applied to first blocks in which distribution of voted disparity points in disparity direction is small and image vertical direction is large. An attribute of road surface is applied to second blocks in which distribution in disparity direction is large and image vertical direction small, thereby determining an object as a three dimensional object or road surface.

Object determining apparatus

A central location of a face detecting device comprises an image input means for inputting a captured face image, a horizontal edge detecting means for detecting a horizontal edge having a predetermined vertical length based on the face image inputted by the image input means; and a central location of a face detecting means for calculating an average value of a horizontal location data of the horizontal edge detected by the horizontal edge detecting means, and determining the average value as a central location of the face.

Central location of a face detecting device, method and program

A facial parts position detection device which includes an image inputting device for inputting a captured face image, an ends position detecting device for detecting right and left ends position of the face on the basis of the image, a facial parts region setting device for setting facial parts region indicating a region where facial parts exists on the basis of the right and left ends of the face, a horizontal edge detecting device for detecting a horizontal edge on the basis of the image inputted by the image inputting device, a horizontal edge histogram creating device for creating a horizontal edge histogram by projecting the horizontal edge in a horizontal direction, a proposed position setting device for setting a plurality of peaks of the horizontal edge histogram as proposed positions respectively, and an optimum position detecting device for detecting an optimum position of the facial parts region.

Facial parts position detection device, method for detecting facial parts position, and program for detecting facial parts position

A driving assist apparatus for a vehicle that guides the vehicle to a target position is provided. On the basis of the present direction of the vehicle and the direction of the vehicle at the target position, a basic path that changes the vehicle direction so as to coincide with the target direction of the vehicle at the target position is computed. A path from the present position to the target position is computed by adding a straight-line path to the basic path under a predetermined condition.

Driving assist apparatus and method for vehicle

An outer environment of the vehicle is inputted as an image. Image processing is performed to the input image, and many edge segments are extracted. The edge segments which are colinear are clustered in order to perform a matching operation. Matching is performed in a respective set of plural longer edge segments representing plural clusters in correspondence with a set of plural guide signs as standards of guide of the vehicle mapped on the image input surface, and a set of longer edge segments being most matched each other is extracted. From position and headings of the extracted longer edge segments on the image input surface, the position and heading in the outer environment are calculated. The position and heading of the vehicle are detected from these values. The position and heading of the vehicle obtained in the above-mentioned image processing and the position and heading of the vehicle measured by other techniques and are evaluated synthetically. When the guide signs are mapped on the image input surface, the forecast values of position and heading of the vehicle at the image input time are used. In this manner, the detecting accuracy of the position and heading of the vehicle is improved.

Position and heading detecting device for self controlled vehicle

An obstacle data processing system for an unmanned self-controlled vehicle, capable of enabling the vehicle to automatically avert any obstacle which lies in the course of running of the vehicle. The system has obstacle position memory device capable of accumulating position data concerning specific obstacles and, hence, forming data concerning the distribution of the obstacles. The vehicle therefore can conduct appropriate averting operation in accordance with the distribution of a plurality of obstacles.

Obstacle data processing system for unmanned vehicle

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Nagoya, Japan

Yoshiki Ninomiya