Clarion Co

Hitachi, Ltd.

Nissan Motor Company Limited

Hitachi Astemo Ltd.

Hitachi Automotive Systems, Ltd.

Aisin Aw Co., Ltd.

Kota Irie

Shoji Muramatsu

Masahiro Kiyohara

Masayuki Takemura

Yasuhisa Hayakawa

Tatsuhiko Monji

Osamu Fukata

Takeshi Shima

Katsuyuki Nakamura

Akira Utagawa

Yuji Otsuka

Yasuhiro Akiyama

Mirai Higuchi

Yoshitaka Uchida

Kimiyoshi Machii

Kenji Kato

Masao Sakata

Ryo Yumiba

Naoki Kourogi

Hayato Tsuchihashi

Hiroshi Sasaki

Takehito Ogata

Masaki Nakamura

Shinya Tagawa

Taisetsu Tanimichi

Isao Furusawa

Subrata Kumar Kundu

Yoshitaka Takahashi

Tetsuaki Nakamikawa

Tomoaki Ishikawa

Daisuke Fukuda

Osamu Aisaka

Naveen Kumar Bangalore Ramaiah

Hidetoshi Arima

Takakiyo Yasukawa

Zihan Yu

Tstsuaki Nakamikawa

Xunfei Zhou

Lars Watts

Lars Stephen Watts

Yukti Matta

Shunsuke Kondou

Kazuhiko Ito

A vehicle orientation estimation system includes a region setting unit. The region setting unit can set a first region and a second region that is on a same horizontal line as the first region, in a measurement region corresponding to a road surface acquired by a distance measurement device mounted on a vehicle. The vehicle orientation estimation system can include a distance calculation unit that calculates a distance to the road surface of each of the first region and the second region from the vehicle. The vehicle orientation estimation system can also include an inclination angle calculation unit that obtains an inclination angle of the vehicle based on the distance to the road surface of each of the first region and the second region and a positional relationship of the first region and the second region.

Vehicle orientation estimation system and vehicle orientation estimation method

In some examples, a first electronic control unit (ECU) receives zone sensor data of a plurality of zones associated with a vehicle. For instance, a respective second ECU and a respective set of zone sensors is associated with each respective zone of the plurality of zones. Based on an indicated driving mode of the vehicle, the first ECU may perform recognition on the zone sensor data from a first zone of the plurality of zones to determine first recognition information. The first ECU receives second recognition information from the respective second ECUs of the respective zones. For instance, the respective second ECUs are configured to perform recognition processing on respective zone sensor data from the set of zone sensors of the respective zones. Based on the first recognition information and the second recognition information, the first ECU sends at least one control signal to at least one vehicle actuator.

Distributed processing of vehicle sensor data

A system for dynamic image compression in autonomous vehicles with multiple cameras. The cameras of a vehicle may be prioritized based on various features, and different image compression techniques may be assigned to different cameras in the vehicle, based on the priorities of the cameras, to reduce overall processing load of the vehicle.

Dynamic image compression for multiple cameras of autonomous vehicles

Example implementations as described herein are directed to the use and detection of asymmetrical markers in conjunction with an autonomous mode for a human operated vehicle system. In example implementations, the vehicle system adjusts at least one of a position, orientation and speed based on the detection of asymmetrical markers, which can be utilized for vehicle navigation as well as autonomous valet parking.

Road marker detection method

When a vehicle starts, a surrounding state is securely provided to a driver. When a vehicle operation detector detects that there is a possibility that a parked vehicle starts, a vehicle surrounding state recognizer recognizes a state of surrounding of the vehicle based on images imaged by a plurality of cameras imaging a plurality of different areas of the surrounding of the vehicle. A parking style determiner determines a parking style executed in parking at a position where the vehicle now parks based on a recognition result of the vehicle surrounding state recognizer. A monitoring area setter sets a monitoring area where a driver is required to pay attention when the vehicle is started based on a determination result of the parking style determiner. A vehicle surrounding state provider provides a driver with information provision in the monitoring area.

Vehicle start support device

A technique for improving the visibility of images from an imaging device even in conditions such that waterdrops adhering on a surface of a lens is very small is provided. An imaging deviceincludes a camerahaving a lens, in which a lens side hydrophilic layeris applied on a surface of the lens, and being configured to be provided to a vehicle, and a waterdrop guiding partwhich guides waterdrops that adhere on the vehicle to the lens

Imaging device and waterdrop guiding member

An outside recognition system configured to include a camera installed on a vehicle, to analyze an image from the camera, and to recognize surroundings of the vehicle based on an analysis result of the image from the camera comprises a dirtiness detection unit which determines, as at least one reference line, at least one line on a part of at least one object that does not change in the image from the camera even if the vehicle travels, determines an observation line that corresponds to each of the at least one reference line with the image from the camera, calculates an amount by which the observation line is displaced from each of the at least one reference line, and detects whether dirt adheres to the camera based on the amount of displacement.

Outside recognition system, vehicle and camera dirtiness detection method

An in-vehicle device includes: an image acquisition unit that obtains a captured image from a camera that captures, via a camera lens, an image of a surrounding environment around a vehicle; an accumulation detection unit that individually detects a plurality of types of accumulation settled at the camera lens based upon the captured image; an image recognition unit that recognizes an object image, expressing a specific object present in the surrounding environment, in the captured image; a detection results integrating unit that calculates integrated detection results by integrating a plurality of sets of detection results based upon various sets of detection results pertaining to detection of the plurality of types of accumulation provided by the accumulation detection unit; and an operation control unit that controls operation executed by the image recognition unit based upon the integrated detection results.

In-vehicle device

A water droplet detection device has an image capturing unit and a water droplet detection unit. The image capturing unit has a photographic optical system that an area captures an image of a predetermined area. The water droplet detection unit sets an arbitrary attention point in the captured image, a plurality of first reference points inside an imaginary circle of a predetermined radius having the attention point as a center the imaginary circle, and a plurality of second reference points corresponding to the first reference points outside the imaginary circle. The water droplet detection unit detects edge information between the first reference points and second reference points, and assesses a circularity strength of the edge information to detect a water droplet attached to the photographic optical system. The water droplet detection device can be used with an image conversion unit to form a three-dimensional object detection device.

Water droplet detection device, and three-dimensional object detection device using water droplet detection device

An on-board device, that outputs a control signal to a cleaning control unit that controls accumulation removing units used to remove accumulations settled on a photographic lens in an on-board camera by adopting a plurality of methods, includes: an accumulation detection unit that detects an accumulation settled on the photographic lens from a photographic image output from the on-board camera when a vehicle speed input thereto is equal to or higher than a predetermined vehicle speed; a selection unit that selects an accumulation removing unit adopting a first method among the accumulation removing units adopting the plurality of methods; and a removal decision unit that makes a decision, based upon the photographic image, as to whether or not the accumulation has been removed from the photographic lens through a removal operation performed by the accumulation removing unit adopting the first method, which has been selected by the selection unit, wherein: if the removal decision unit decides that the accumulation has not been removed from the photographic lens, the selection unit selects an accumulation removing unit adopting a second method, different from the accumulation removing unit adopting the first method, based upon a number of times that the removal operation has been performed by engaging the accumulation removing unit adopting the first method.

On-board device controlling accumulation removing units

An approaching-object detection system detects an approaching object based on images captured by an imaging device. The approaching-object detection system comprises an extraction unit, a distortion correction unit, an object detection unit, and an approaching-object classification unit. The extraction unit extracts a partial image of one far side and a partial image of the other far side from each of the images. The distortion correction unit corrects distortion of the partial images. The object detection unit detects an object from the corrected partial images through pattern matching with reference to preinstalled image information on the object. The approaching-object classification unit classifies the detection result of the object detection unit as an approaching object or not.

Approaching-object detection system and vehicle

It is possible to consider an image as a composite wave that is the result of layering waves having differing periods and amplitudes. An image captured via a lens having a water droplet attached thereto has a higher occurrence of changes such as image blur than an image that does not have a water droplet attached thereto, which means that this type of change in an image results in changes in the composite wave thereof as well. Provided is a lens dirtiness detection device that suitably determines whether a lens is dirty without being affected by a background image by: focusing on the occurrence of large changes in the composite wave of an image that accompany an increase in the dirtiness of a camera lens; extracting each of the image frequency components that constitute the composite wave; and analyzing changes in the magnitude relation between the frequency components.

Outside recognition apparatus and lens dirtiness detection method

Provided is a vehicle surroundings recognition apparatus capable of enhancing a calculation accuracy of a relative position and a relative speed with respect to an object such as a pedestrian even in a case where the object cannot be detected accurately in some of the images obtained by performing image-capturing around a vehicle, for example. In a case where a first state in which a first detection unit and a second detection unit detect first position information and second position information about an object and a second state in which only a second detection unit detects second position information about the object occur in a time sequence, first position information interpolation information for interpolating the first position information about the object in the second state is calculated on the basis of the first position information and the second position information in the first state and the second position information in the second state, and a relative distance and a relative speed to the object are measured on the basis of the first position information and the first position information interpolation information.

Vehicle-surroundings recognition device

A camera device includes image capturing device, a lens cleaning device, an adhesion state assessment unit and a controller. The image capturing device is installed on a vehicle and has a lens for forming an image of the vehicle surroundings. The lens cleaning device cleans the lens by spraying a cleaning fluid on the lens in accordance with a predetermined lens cleaning step, in which at least a supply time for supplying cleaning fluid to the lens surface is predetermined. The adhesion state assessment unit is programmed to assess an adhesion state of contamination from a distribution of pixels corresponding to foreign matter adhered to the lens based on a captured image. The controller is programmed to extend the time until a time to start supplying the cleaning fluid in the lens cleaning step as the number of pixels corresponding to foreign matter adhered to the lens increases.

Camera device, three-dimensional object detection device, and lens cleaning method

A surrounding environment recognition device includes: an image acquisition unit that obtains a photographic image from a camera for capturing, via a camera lens, an image of a surrounding environment around a mobile object; an image recognition unit that recognizes an object image of an object present in the surrounding environment based upon the photographic image obtained by the image acquisition unit; an accumulation detection unit that detects accumulation settled on the camera lens based upon the photographic image obtained by the image acquisition unit; a suspension decision-making unit that makes a decision, based upon detection results provided by the accumulation detection unit, whether or not to suspend operation of the image recognition unit; a tracking unit that detects a characteristic quantity in a tracking target image from a specific area in an image captured by the image acquisition unit for a reference frame, determines through calculation an estimated area where the characteristic quantity should be detected in an image captured by the image acquisition unit for a later frame relative to the reference frame and makes a decision as to whether or not the characteristic quantity for the tracking target image is also present in the estimated area; and a resumption decision-making unit that makes a decision, based upon at least decision-making results provided by the tracking unit and indicating whether or not the characteristic quantity for the tracking target image is present, as to whether or not to resume the operation of the image recognition unit currently in a suspended state.

Surrounding environment recognition device

Growing community of inventors

Saitama, Japan

Kota Irie