Honda Motor Co., Ltd.

Sensetime Group Limited

Tokitomo Ariyoshi

Yuji Yasui

Hideki Matsunaga

Umiaki Matsubara

Mingmei Li

Takahiro Fukushige

Kazuhiro Nakadai

Atsushi Kawamura

Yuji Kaneda

Masamitsu Tsuchiya

Xiaogang Wang

Hiroshi Tsujino

Junjie Yan

Rei Sakai

Yuki Okuma

Tatsuya Okabe

Xingyu Zeng

Yuhi Goto

Yingjie Cai

Shinan Liu

Yusuke Uda

Shuichi Yokemura

A map generation apparatus including a detection device that detects an external situation around a subject vehicle, and an electronic control unit including a microprocessor and a memory. The microprocessor is configured to perform generating a first map for a current lane on which a subject vehicle travels, based on the external situation detected by the detection device, and acquiring a map information on an opposite lane map for an opposite lane generated by another vehicle traveling on the opposite lane opposite to the current lane. The microprocessor is configured to perform the generating further including generating a second map for the current lane corresponding to a point where the map information on the opposite lane map has been acquired, by inverting the opposite lane map.

Map generation apparatus

A map generation apparatus including a microprocessor. The microprocessor is configured to perform recognizing another vehicle traveling on an opposite lane opposite to a current lane on which a subject vehicle travels, acquiring an information of an external situation around the other vehicle in a route matching section when the other vehicle is recognized, the information of the external situation being obtained by the other vehicle traveling on the opposite lane, the route matching section being a section in which a driving route of the subject vehicle and a driving route of the other vehicle match in a driving route including the current lane and the opposite lane, and generating a map for the opposite lane in the route matching section, based on the information of the external situation.

An image processing apparatus applies predetermined image processing to an actual image captured by an image capturing device and recognizes a target within the captured image with use of the image which the predetermined image processing has been applied to. The image processing apparatus applies, to tones of the actual image, the predetermined image processing for reducing a difference from tones of a CG image which shows the same scene and which is presented through computer graphics.

Image processing apparatus, vehicle, control method for information processing apparatus, storage medium, information processing server, and information processing method for recognizing a target within a captured image

A map generation apparatus including an electronic control unit including a microprocessor and a memory connected to the microprocessor. The microprocessor is configured to perform acquiring a map data of a first map for a current lane on which a subject vehicle travels, and generating a second map for an opposite lane opposite to the current lane by inverting the first map, based on the map data acquired.

Provided is a risk estimation device capable of appropriately estimating a risk in a traveling direction of an own vehicle even under the condition that a relationship between a traffic participant and a road condition is inappropriate. The risk estimation device recognizes a traffic participant, a road condition, and a condition of the traffic participant in the traveling direction of the own vehicle based on a surrounding condition data, determines, by using a reference relationship model, whether the relationship between the traffic participant and the road condition is appropriate, estimates, by using a risk model, a traveling risk in a case where the relationship between the traffic participant and the road condition is determined to be appropriate, and estimates the traveling risk according to the condition of the traffic participant in a case where the relationship between the traffic participant and the road condition is determined to be inappropriate.

Risk estimation device and vehicle control device

Provided herein is a vehicle control device that includes a recognition unit that recognizes a surrounding status of a vehicle and a driving control unit that controls a speed and/or a steering of the vehicle. The driving control unit performs switching to a second driving state in which a driver has a higher degree of a monitoring obligation than in a first driving state. The vehicle control device further includes a map updating unit that updates intrinsic map information on the basis of the recognition result and when switching from the first driving state to the second driving state is performed by the driving control unit.

Vehicle control device, map information management system, vehicle control method, and storage medium

A vehicle control device includes: a peripheral situation recognition unit () configured to recognize a peripheral situation of an automatic driving vehicle; a driving control unit (, ()) configured to control one or both of steering and an acceleration or deceleration speed of the vehicle based on the peripheral situation recognized by the peripheral situation recognition unit; and a potential risk estimation unit () configured to estimate presence or absence and classification of a potential risk meeting with an obstacle based on classification of a target recognized by the peripheral situation recognition unit and a positional relation between the vehicle and the target. The driving control unit performs the driving control based on an estimation result of the potential risk estimation unit.

Vehicle control device, vehicle control method, and storage medium

A 3D object detection method includes: obtaining two-dimensional (2D) coordinates of at least one predetermined key point of a target object in an image to be processed; constructing a pseudo 3D detection body of the target object in a 2D space according to the 2D coordinates of the at least one predetermined key point; obtaining depth information of a plurality of vertices of the pseudo 3D detection body; and determining a 3D detection body of the target object in a 3D space according to the depth information of the plurality of vertices of the pseudo 3D detection body.

Three-dimensional object detection method and device, method and device for controlling smart driving, medium and apparatus

A recognition processing device includes a peripheral situation recognition unit configured to recognize a type of object around a vehicle and a positional relationship with the vehicle, an object recognition unit configured to select a word indicating the type of object recognized by the peripheral situation recognition unit and a word indicating a positional relationship between the vehicle and the object, and a text generation unit configured to generate text for describing a peripheral situation recognized by the peripheral situation recognition unit, wherein the text includes the word indicating the type of object selected by the object recognition unit and the word indicating the positional relationship between the vehicle and the object selected by the object recognition unit.

Recognition processing device, vehicle control device, recognition control method, and storage medium

A time-series data prediction device includes an acquisition unit, a prediction model generation unit, and a prediction unit. The acquisition unit acquires a plurality of observation values that continue at predetermined time intervals, as a prediction data, from time-series data of an observation value of a predetermined observation target, and acquires a training data. The prediction model generation unit generates a prediction model to calculate time-series data, which is an observation value predicted based on given time-series data, using the training data. The prediction unit calculates a predicted value of an observation value using the generated prediction model and the prediction data.

Time-series data prediction device of observation value, time-series data prediction method of observation value, and program

A performance predicting apparatus includes an approximate model storage unit configured to store approximate models each of which is associated with one of categories, and which are used to calculate functional performance based on feature values, a feature value extracting unit configured to extract the feature values from shape data representing a shape of an object, a selection unit configured to select one of the approximate models to be used from the approximate models stored in the approximate model storage unit depending on the feature values extracted by the feature value extracting unit, and a performance calculating unit configured to calculate functional performance based on the feature values extracted by the feature value extracting unit using the approximate model selected by the selection unit.

Performance predicting apparatus, performance predicting method, and program

An information transmission device which analyzes a diction of a speaker and provides an utterance in accordance with the diction of the speaker, and which has a microphone detecting a sound signal of the speaker, a feature extraction unit extracting at least one feature value of the diction of the speaker based on the sound signal detected by the microphone, a voice synthesis unit synthesizing a voice signal to be uttered so that the voice signal has the same feature value as the diction of the speaker, based on the feature value extracted by the feature extraction unit, and a voice output unit performing an utterance based on the voice signal synthesized by the voice synthesis unit.

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Wako, Japan

Tokitomo Ariyoshi