Nissan Motor Company Limited

Renault S.a.s.

Haruo Matsuo

Daiki Yamanoi

Akira Suzuki

Hiroshi Satoh

Takahiko Oki

Toshihiko Nishimura

Hidekazu Nishiuchi

Toshiyuki Andou

Kuniaki Noda

Takashi Ikegami

Tomoko Kurotobi

Masanobu Nagase

An information processing method and an information processing device assign attribute information to each ranging point based on an image obtained by capturing an image of surroundings of a vehicle using an imaging unit, or based on point cloud data related to ranging points around the vehicle generated by a sensor, calculate a distance from the imaging unit to the ranging point and a direction of the ranging point as viewed from the imaging unit based on the point cloud data, calculate a pixel value for each ranging point based on the distance to the ranging point and the attribute information, and generate a two-dimensional image in which pixel corresponding to the direction of the ranging point has the pixel value.

Information processing method, and information processing device

An object recognition method uses a sensor configured to acquire a position of an object existing in a surrounding environment as point clouds including a plurality of detection points in a top view. The method includes: grouping point clouds according to a proximity; determining, when performing polygon approximation on the grouped point clouds, whether at least part of the detection points constituting the grouped point clouds are located in a blind zone of an approximate polygon acquired by the polygon approximation with respect to the sensor; recognizing the grouped point clouds as point clouds corresponding to plural objects when it is determined that the detection points are located in the blind zone with respect to the sensor; and recognizing the grouped point clouds as point clouds corresponding to a single object of the approximate polygon when it is determined that the detection points are not located in the blind zone.

Object recognition method and object recognition device

A traffic signal recognition method and a traffic signal recognition device estimate whether or not a vehicle can be decelerated at a predetermined deceleration acceleration and can stop before a stop line based on a position of the stop line corresponding to a traffic signal located in a traveling direction of the vehicle, select the traffic signal corresponding to the stop line as a target traffic signal in a case where it is estimated that the vehicle cannot stop before the stop line, set detection area corresponding to the target traffic signal on an image obtained by capturing the traveling direction of the vehicle, and determine a display state of the target traffic signal by executing image processing on the detection area.

Traffic signal recognition method and traffic signal recognition device

A traffic signal recognition method and a traffic signal recognition device acquire a result sequence consisting of a plurality of determination results in time-series order obtained by determining a display state of a traffic signal based on a plurality of images of a traveling direction of a vehicle, set a first threshold as a number threshold if a first distance from a position of the vehicle to a position of a stop line corresponding to the traffic signal is equal to or greater than a distance threshold, set a second threshold smaller than the first threshold as the number threshold if the first distance is less than the distance threshold, and output a latest determination result if a number of determination results identical to the latest determination result is greater than the number threshold, among the determination results.

A traffic signal recognition method and a traffic signal recognition device acquire a result sequence consisting of a plurality of determination results in time-series order obtained by determining a display state of a traffic signal based on a plurality of images of a traveling direction of a vehicle, set a first threshold as a number threshold if a specific determination result which is a latest determination result among the determination results is a determination result of a permission display that allows a passage of the stop line corresponding to the traffic signal, set a second threshold smaller than the first threshold as the number threshold if the specific determination result is other than a determination result of the permission display, and output the specific determination result if a number of determination results identical to the specific determination result is greater than the number threshold.

A traffic light recognition device includes: a camera that captures an image around a vehicle; a map information acquisition unit configured to acquire map information around the vehicle; a self-position detector configured to detect the position of a self-position on a map; a traffic light position estimator configured to estimate the position on an image of a traffic light on the basis of the self-position and the map information; a vehicle behavior estimator configured to estimate a vehicle behavior; a traffic light detection area calculator configured to set a detection area of the traffic light onto the image based on the estimated position on the image of the traffic light and an amount of displacement of the position on the image of the traffic light due to a behavior of the vehicle; and a traffic light recognition unit configured to detect a traffic light from the detection area.

Traffic light recognition device and traffic light recognition method

A traffic light recognition device includes: an imaging attitude setting unit configured to set an imaging direction of the camera on the basis of a position on the image of the traffic light and of a moving direction in the future on the image of the traffic light; a camera attitude controller configured to change the imaging direction of the camera to an imaging direction set by an imaging direction setting unit; and a traffic light recognition unit configured to recognize the traffic light from an image captured in the imaging direction by the camera. The traffic light recognition device is capable of accurately detecting the lighting state of a traffic light without being affected by the attitude of a camera.

A traffic signal detection device includes a narrow-angle camera, a wide-angle camera having an angle of view wider than the narrow-angle camera, and a traffic signal detector configured to detect a traffic signal from at least any of a narrow-angle image captured by the narrow-angle camera and a wide-angle image captured by the wide-angle camera. The traffic signal detector selects, as a detection result, any of a traffic signal detected from the narrow-angle image and a traffic signal detected from the wide-angle image, on the basis of a deceleration start region in which a vehicle should start deceleration, the deceleration start region calculated from a position of a traffic signal with respect to the vehicle and a speed of the vehicle in order to stop the vehicle at a stop position with respect to the traffic signal.

Traffic signal detection device and traffic signal detection method

A lamp detection device detects an edge portion from a camera image, the edge portion having a luminance difference equal to or above a predetermined value, and generates a smoothed image by diminishing the luminance difference of the edge portion. Then, the lamp detection device extracts synchronized pixels from the smoothed image, the synchronized pixels having luminances varying synchronously with an alternating current cycle of power supplied to a lamp, and detects the lamp from the synchronized pixels.

Lamp detection device and lamp detection method

A traffic light detection device uses an image pickup unit mounted on a vehicle to extract, from an image taken of surroundings of the vehicle, synchronized pixels, whose brightness changes in synchronization with an alternating current period of electric power supplied to a traffic light, and detects the traffic light from the synchronized pixels. The traffic light detection device is provided with: a positional variation calculation unit that calculates positional variation amounts of continuously extracted positions of the synchronized pixels; and a signal lamp determination unit that determines, as a signal lamp candidate, the synchronized pixels whose positional variation amount is equal to or smaller than a threshold value.

Traffic light detection device and traffic light detection method

A traffic light detection device includes: an image capture unit capturing an image of surroundings; a traffic light location estimation unit estimating a location of a traffic light around the vehicle and setting a traffic light search area in which the traffic light is estimated to be present; a traffic light detection unit detecting the traffic light by searching the traffic light search area on the image; and an obstruction estimation unit. When the obstruction estimation unit estimates that a continuous obstruction state where a view of the traffic light is continuously obstructed occurs in the traffic light search area, the traffic light location estimation unit selects the traffic light search area based on the continuous obstruction state.

A traffic signal recognition apparatus acquires image data by imaging the surroundings of a vehicle, detects a self-position of the vehicle, and detects, in the image, a traffic signal around the vehicle. The traffic signal recognition apparatus identifies two or more of the traffic signal predicted to be captured in the image, based on information on the self-position and map information containing positional information on the traffic signals, and assigns a priority level to each of the two or more traffic signals thus identified, based on a possibility of the traffic signal being blocked out of sight. When the two or more traffic signals are identified, the traffic signal detected in the image is a traffic signal with a highest priority level among the two or more traffic signals.

Traffic signal recognition apparatus and traffic signal recognition method

A target detection apparatus acquires an image by imaging the surroundings of a vehicle, detects a self-position of the vehicle based on an amount of movement of the vehicle from an initial position thereof, and estimates a relative position of a target, located around the vehicle, with respect to the vehicle based on the self-position and information on a position of the target on a map. The target detection apparatus sets a detection area for the target within the image based on the relative position of the target with respect to the vehicle, and detects the target from the detection area. The target detection apparatus estimates error contained in the self-position based on the amount of movement of the vehicle from the initial position, and adjusts the size of the detection area for the target according to the error.

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Kanagawa, Japan

Haruo Matsuo