Honda Motor Co., Ltd.

Yosuke Sakamoto

Kazuma Ohara

Misa Komuro

Masamitsu Tsuchiya

Yuki Kizumi

Daisuke Kondo

Yuki Nakada

Hiroyuki Koibuchi

Yoshifumi Banno

Umiaki Matsubara

Yuji Yasui

Kentaro Yamada

Yuki Motegi

Kenji Komori

Shinsuke Odai

Yosuke Koike

Kenshi Torikai

A mobile object control device includes a recognizer that recognizes a surroundings situation of a mobile object, and a controller that controls an acceleration and deceleration of the mobile object based on the surroundings situation recognized by recognize, and the controller sets a risk area at a first reference position based on an end of an obstacle present around the mobile object in a traveling direction of the mobile object when a predicted trajectory in which another mobile object is estimated to move and a future trajectory of the mobile object interfere with each other, and the length of a target area corresponding to the predicted trajectory in a predicted trajectory direction is equal to or larger than a predetermined length with respect to the target area difficult for the recognizer to recognize due to the obstacle, and controls at least the speed of the mobile object based on the set risk area.

Mobile object control device, mobile object control method, and storage medium

A vehicle seatbelt device of an embodiment includes a recognizer that recognizes circumstances around a vehicle, a steering operator that is able to adjust steering of the vehicle, a vibrator that causes a portion of the steering operator to vibrate, a seatbelt that restrains a portion of the body of an occupant of the vehicle, a tension adjustment mechanism that is able to adjust the tension of the seatbelt, and a controller that controls the vibrator and the tension adjustment mechanism on the basis of the circumstances recognized by the recognizer.

Vehicle seatbelt device

A the method for controlling a vehicle: recognizing at least a position of a traffic participant around a vehicle and a road environment around the traffic participant, setting a risk region for the traffic participant based on at least the recognized position of the traffic participant, correcting the set risk region based on a width of a sidewalk where the traffic participant is present or a width of a roadway around the traffic participant which is the recognized road environment, and controlling a speed and steering of the vehicle based on the corrected risk region.

Method for controlling vehicle, vehicle control device, and storage medium

A vehicle control device includes a peripheral recognition unit configured to recognize a peripheral status of a vehicle including a position of a traffic participant present in a periphery of the vehicle on the basis of an output of an in-vehicle device, an estimation unit configured to estimate a peripheral attention ability of the traffic participant on the basis of an output of the in-vehicle device, and a risk area setting unit configured to set a risk area of the traffic participant on the basis of a result of the estimation performed by the estimation unit.

Vehicle control device, vehicle control method, and storage medium that performs risk calculation for traffic participant

A vehicle control device includes a recognizer configured to recognize a surrounding environment of a vehicle, a setter configured to set a first risk area in a surrounding area of the vehicle on the basis of a recognition result of the recognizer, and a controller configured to control at least one of a speed and steering of the vehicle. The setter sets the first risk area so that the first risk area includes an area between the moving object and a first end of a crosswalk where the moving object is scheduled to arrive in the crosswalk when the moving object is entering the crosswalk which is provided in front of the vehicle and where the vehicle is scheduled to pass on the basis of the recognition result of the recognizer. The controller prevents the vehicle from entering the first risk area when a first predetermined condition is satisfied.

Vehicle control device, vehicle control method, and storage medium

A method for controlling a vehicle including specifying an object, an attribute of the object, and the strength and direction of wind influencing the object based on an image captured by an imager imaging the surroundings of a vehicle, setting a risk region for the object based on the attribute of the object and the strength and the direction of the wind that are specified, and controlling a speed and steering of the vehicle based on the risk region set by the setter.

A prediction device including: a recognizer recognizing a road structure and another vehicle in the vicinity of a subject vehicle; and a predictor predicting a running locus of the other vehicle recognized by the recognizer in the future on the basis of the road structure recognized by the recognizer in a predetermined situation, wherein, in the predetermined situation, in a case in which at least a part of the road structure used for predicting the running locus of the other vehicle in the future is not recognizable for the recognizer, the predictor predicts the running locus of the other vehicle in the future on the basis of a running locus of the other vehicle in the past acquired on the basis of a result of recognition in the past that is acquired by the recognizer.

Prediction device, prediction method, and storage medium

The present invention provides a vehicle control apparatus capable of traveling a vehicle by automated driving, comprising a state detection unit configured to detect a state of an occupant in the vehicle, and a control unit configured to set a traveling mode of automated driving in accordance with a change in the state of the occupant detected by the state detection unit.

Vehicle control apparatus

A prediction apparatus, comprising an acquisition unit configured to acquire peripheral information of an own vehicle, a determination unit configured to determine, based on the peripheral information, whether a behavior prediction target on a road visually recognizes a predetermined object, and a prediction unit configured to, if it is determined by the determination unit that the behavior prediction target visually recognizes the predetermined object, predict that the behavior prediction target moves across the road in a crossing direction.

Prediction apparatus, vehicle, prediction method, and non-transitory computer-readable storage medium

There is provided a vehicle control apparatus that controls automated driving of a vehicle. The apparatus includes an extraction unit configured to extract an object existing around the vehicle from a scene image representing a peripheral status of the vehicle, and a control unit configured to calculate a moving locus of the object and a moving locus of the vehicle for a predetermined time from time when the scene image is acquired, and generate a moving locus by correcting the moving locus of the object based on the moving locus of the vehicle.

Vehicle control apparatus, vehicle, vehicle control method, and storage medium

A processing apparatus comprises a first determination unit configured to determine, based on peripheral information of a self-vehicle, whether another vehicle that is stopped exists on one side of a road in a width direction; a second determination unit configured to determine, based on the peripheral information, whether a walker exists on the other side of the road in the width direction; and a setting unit configured to, if the other vehicle exists on the one side of the road in the width direction, and the walker exists on the other side of the road in the width direction, set, for the other vehicle, a second warning region wider than a first warning region in a case in which the other vehicle exists, and the walker does not exist.

Processing apparatus, vehicle, processing method, and storage medium

An information processing device, a learning processing method, a learning device and an object recognition device capable of improving learning processing accuracy are provided. An information processing device causes a computer to generate a distortion-corrected equivalent image on the basis of a first captured image including a subject having predetermined distortion generated due to optical operations during imaging, to generate first teacher data in which relevant information about the target object has been added for the equivalent image in which an image region for the target object has been designated, to convert the equivalent image included in the first teacher data into a distorted image having predetermined distortion to generate second teacher data and to generate a learning model which outputs a result obtained by identifying the target object included in the second captured image when the second captured image having predetermined distortion generated therein is input, on the basis of the second teacher data.

Information processing device, learning processing method, learning device, and object recognition device

If road information indicates that a first curve zone at a near side and a second curve zone at a far side that curve in different directions are continuously located in a road, a steering assist unit of a steering assist device or a steering assist circuit finishes decreasing process of decreasing the steering assist amount when the subject vehicle passes through the first curve zone earlier than a case when the subject vehicle passes through the second curve zone.

Steering assist device and circuit

A vehicle drive control device includes a drive lane detector, a drive assist unit, and a curve road steering assist unit. The drive lane detector detects a drive lane of a subject vehicle. The drive assist unit performs drive assist control to assist the subject vehicle in lane keep driving in the drive lane. The curve road steering assist unit performs steering assist for assisting the subject vehicle in turning along a curve of a curve road if the drive lane is the curve road and if the drive assist control performed by the drive assist unit is discontinued during driving on the curve road.

Vehicle drive control device

Provided is an image processing device in which a region targeted for edge extraction of a taken image is divided into a plurality of partial regions() to() for which threshold values for edge extraction different from each other are set, respectively. An edge extraction unit, which extracts edges from the region targeted for edge extraction, performs processing of extracting the edges in the partial regions() to() by using the threshold values set so as to correspond to the each of the partial regions() to().

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Wako, Japan

Yosuke Sakamoto