Toyota Jidosha Kabushiki Kaisha

Kyocera Corporation

Kabushiki Kaisha Toshiba

Ricoh Company, Ltd.

Konica Minolta, Inc.

Honda Motor Co., Ltd.

Toshiba Electronic Devices & Storage Corporation

Ohlins Racing Ab

Yusuke Hayashi

Taichi Kawanai

Naoto Ohara

Keisuke Hokai

Nobuhide Kamata

Kaoru Kusafuka

Daichi Hotta

Tomoya Sugita

Kazuto Takao

Satoshi Kawaji

Yasuhiro Takagi

Eiji Sakaguchi

Masahiro Harada

Hideyuki Matsui

Hideo Fukamachi

Kazuhiko Kamikado

Kentaro Ichikawa

Tomoaki Inokuchi

Yohei Sato

Tatsunori Sakano

Hiro Gangi

Masahiro Koyama

Sadayuki Abe

Jun Marubayashi

Shin Miura

Akihisa Shimomura

Mitsuyoshi Ohno

Hiromitsu Urano

Shuichi Suzuki

Yusuke Kobayashi

Ryo Igarashi

Kentaro Ikeda

Satoshi Yoshida

Tatsuya Nishiwaki

Mitsuru Nakajima

Bunyo Okumura

Kenichi Yoshimura

Ryohei Gejo

Naoki Kuwabara

Taisuke Sugaiwa

Takuya Nezaki

Yuji Takahashi

Keita Ito

Motoyuki Katsumata

Hikaru Hamano

Yoshitaka Sotoyama

Yoshimi Satoh

Hiroaki Kozai

Tadashi Hirano

Takahiro Kato

Souichi Tanaka

Koji Toida

Yousuke Matsumoto

Tomohiro Nishiura

Mikael Jonsson

Junji Ohashi

Yoichi Miyauchi

Shigeyasu Murase

Shingo Uraki

Keigo Arita

According to one embodiment, a power conversion device includes: a plurality of DC-DC converter circuits configured to generate AC voltages at both ends of a plurality of first inductors by switching on a DC voltage and rectifies the AC voltages to output DC voltages; and a plurality of second inductors respectively magnetically coupled to the plurality of first inductors of the plurality of DC-DC converter circuits, wherein inputs and outputs of the plurality of DC-DC converter circuits are respectively connected in series and the plurality of second inductors are connected in parallel between two nodes.

Power conversion device

An automated driving management system is applied to a vehicle that performs automated driving by using a perception sensor. The automated driving management system acquires first sensor perception information indicating a result of perception by the perception sensor. Reference information indicates a correspondence relationship between a vehicle position and expected sensor perception information that is the first sensor perception information expected when an automated driving condition is satisfied. Based on the reference information, the automated driving management system acquires the expected sensor perception information associated with a determination target position. The automated driving management system determines whether or not the automated driving condition is satisfied at the determination target position by comparing the first sensor perception information acquired at the determination target position with the expected sensor perception information associated with the determination target position.

Automated driving management system and automated driving management method

A travel planner identifies, for a connection point where a travel lane in which a vehicle is traveling connects ahead of the vehicle with another lane different from the travel lane, an entry time range representing a time range during which entry of the vehicle from the travel lane to the connection point is recommended, and creates a travel plan including a transition of travel speed of the vehicle from a current position of the vehicle to the connection point so as to arrive at the connection point within the entry time range.

Travel planner and method for travel planning

The object detection apparatus detects an object target by using the LIDAR and the camera. The object detection apparatus includes a calibration processing unit that is configured to perform calibration of the LIDAR and the camera. The LIDAR includes a light reception element configured to receive reflection light of irradiated laser light and reflection light of ambient light which is light other than the laser light and to detect an intensity of the received reflection light of the ambient light. The calibration processing unit is configured to perform the calibration, based on a result of light reception of the received reflection light of the ambient light and the camera image captured by the camera.

Object detection apparatus

A vehicle dispatch system for dispatching an autonomous vehicle in accordance with a vehicle dispatch request is proposed. The vehicle dispatch system is configured to execute generating a transportation route from a pick-up point to a destination point, generating a plurality of candidate dispatch routes for a dispatch route from a current point of the autonomous vehicle to the pick-up point, calculating a degree of overlap between the transportation route and the dispatch route for each of the plurality of candidate dispatch routes, selecting the dispatch route from the plurality of candidate dispatch routes based on the degree of overlap, and causing the autonomous vehicle to travel along the dispatch route and the transportation route.

Vehicle dispatch system, traveling route generation method, and non-transitory computer readable recording medium

A remote support system is configured to determine whether a vehicle collides with an object to be avoided when the vehicle gets into a remote control request situation, stop to send a remote control request when the remote support system determines that the vehicle does not collide with the object, generate a first speed plan for the vehicle to continue autonomous driving at a predicted collision position and a second speed plan for the vehicle to stop before reaching the predicted collision position when the remote support system determines that the vehicle collides with the object, and determine to send a remote control request based on the degree of deviation between these speed plans.

Remote support system and remote support method

A map management system stores map information used by an automated driving vehicle. The automated driving vehicle detects an obstacle based on the map information, or acquires a margin distance when stopping in front of an obstacle based on the map information. When requiring a remote operator's decision about an action with respect to the obstacle, the automated driving vehicle issues a support request that requests the remote operator to give support. The map management system acquires an operator instruction to the automated driving vehicle issued by the remote operator in response to the support request. The map management system estimates a type of the obstacle based on a state of acquisition of the operator instruction or a content of the operator instruction. Then, the map management system updates the map information according to the type of the obstacle.

Map management system and map management method

A processor of a vehicle determines whether remote assistance from a remote facility is necessary during autonomous driving control. When determination is made that the remote assistance is necessary, the processor generates a target trajectory of the vehicle that includes an expected waiting position. The expected waiting position is a position where the vehicle is expected to wait for reception of an assistance signal from the remote facility. The processor calculates a traveling efficiency level indicating a level of traveling efficiency required in the vehicle, and calculates, based on the traveling efficiency level, a request timing to transmit a request signal for the remote assistance to the remote facility. When the traveling efficiency level is low in calculation of the request timing, the processor outputs a late timing.

Vehicle control system and vehicle control method

A log management apparatus according to the present disclosure comprises a memory storing traveling log data of a vehicle and one or more processors. The one or more processors are configured to execute the following first to five processes. The first process is acquiring a remaining capacity of the memory at a current time. The second process is acquiring a traveling plan of the vehicle. The third process is calculating a predicted data size which is a size of the traveling log data predicted to be stored in the future in the traveling plan. The fourth process is predicting a capacity shortage of the memory in the traveling plan based on the predicted data size and the remaining capacity at the current time. The fifth process is a process of increasing the remaining capacity when the capacity shortage of the memory is predicted.

System and method for log management in a vehicle

A distribution calculation process, a similarity level calculation process, a similarity level evaluation process, and a collision determination process are executed. In the distribution calculation process, a probability density distribution related to a future position of a moving object is calculated for each behavior pattern using position data and speed data of the moving object, error data thereof, and a plurality of behavior models set for each behavior pattern corresponding to a type of the moving object. In the similarity level calculation process, a similarity level between the probability density distribution and a reference probability density distribution is calculated for each behavior pattern. In the similarity level evaluation process, the similarity level is evaluated. The similarity level includes an out-of-range level falling below a similarity allowable range. In the similarity level evaluation process, the behavior pattern having the out-of-range level is excluded from a target of the collision determination process.

Behavior prediction device

A management device manages remote support for a vehicle. The management device executes assigns a remote operator to a target vehicle in response to a support request from the target vehicle. Vehicle information includes a position and a travel plan of the target vehicle. When receiving a plurality of support requests in a same period respectively from a plurality of target vehicles scheduled to pass through a predetermined area, the management device recognizes, based on the vehicle information, an entry direction into the predetermined area and an exit direction from the predetermined area for each target vehicle. Based on a combination of the entry direction and the exit direction, the management device determines whether to assign a same remote operator to the plurality of target vehicles or assign different remote operators to the plurality of target vehicles.

Management device, management method, and non-transitory computer-readable recording medium

A semiconductor device of an embodiment includes: a semiconductor layer having a first face and a second face, the semiconductor layer including a first trench and a second trench on a side of a first face; a first electrode on the side of the first face; a second electrode on the side of the second face; a first gate electrode in the first trench; a first field plate electrode electrically connected to the first electrode in the first trench, a second gate electrode in the second trench; and a second field plate electrode electrically connected to the first electrode in the second trench, a resistance between first electrode and second field plate is different from a resistance between first electrode and the first field plate electrode.

Semiconductor device

At least one processor of a vehicle is configured to execute at least one program to: generate a speed plan for a first travel route from a blind spot elimination position to a position specified by a control standby condition, the speed plan specifying a speed of the vehicle for a position on the first travel route so as to meet a requirement that the vehicle be decelerated at a predetermined allowable deceleration or less for a predetermined time from the blind spot elimination position to satisfy the control standby condition; and instruct, for a second travel route from a current position of the vehicle to the blind spot elimination position, the vehicle to travel along the second travel route by autonomous driving so as to cause the vehicle to reach a speed specified by the speed plan at the blind spot elimination position.

The vehicle position estimation apparatus that estimates the position of the host vehicle includes: a laser light irradiation unit configured to illuminate laser light; a light reception element configured to receive reflection light of the laser light and reflection light of ambient light which is light other than the laser light and be able to detect an intensity of each of the received reflection light; and a host position estimation unit configured to estimate the position of the host vehicle, based on a result of light reception of the reflection light of the laser light received by the light reception element and a result of light reception of the reflection light of the ambient light.

Vehicle position estimation apparatus

According to one embodiment, electronic circuitry includes a semiconductor switching element; and a driving circuit configured to supply a current to a control terminal of the semiconductor switching element and to adjust a magnitude of the current supplied to the control terminal based on a voltage at the control terminal.

Electronic circuitry, electronic system, and driving method

Growing community of inventors

Tokyo, Japan

Yusuke Hayashi