Toyota Jidosha Kabushiki Kaisha

Olympus Optical Company, Ltd.

Koji Taguchi

Makoto Morita

Tomoyuki Kuriyama

Shin Sakurada

Keiji Yamashita

Koichi Ikemoto

Tatsuo Nagasaki

Nobuhide Kamata

Shinichi Imade

Masaki Wasekura

Yasunao Yoshizaki

Tetsumaru Kubota

Syuichi Takayama

Akio Nakada

Takashi Suzuki

Hiromitsu Urano

Kentaro Ichikawa

Masaaki Hayashi

Masaki Matsunaga

Hiroyoshi Fujimori

Hitoshi Karasawa

Shinji Hatta

Maiko Hirano

Tadao Hagino

Akihiro Taguchi

Eishi Ikuta

Toshiki Terayama

Hiroyuki Kusunoki

Kazunori Shionoya

Shuichi Yokokawa

Masato Endo

Yasuhiro Ueda

Akira Shiga

Masaaki Yamaoka

Yukari Okamura

Naomi Sekino

Haruki Oguri

Hirokazu Kato

Akihisa Yokoyama

Tatsuya Kubota

Masateru Amano

Tomoyuki Doi

Yutaka Aoki

Naoki Matsushita

Makoto Aso

Issei Matsunaga

Seiichi Wakamatsu

Yutaka Ohshima

Yoji Mizoguchi

Norihiro Takahashi

Toyoo Nishiyama

Daisaku Negoro

Masashi Obuchi

Hiroyuki Ishida

Narihito Yamazato

Koji Nakai

Saeko Miyaoka

Ryouichi Konou

Yoshitaka Adachi

A remote assistance management system is in communication with autonomous traveling vehicles for letting an operator provide remote assistance in response to an assistance request from a vehicle. The system predicts an occurrence of an assistance request in future based on operation states of the vehicles, and categorize a cause of an assistance request predicted to occur into a first category cause that lasts for a long time and a second category cause that lasts only for a short time. The system receives an assistance request from the vehicles. In response to acquiring a first assistance request of which the cause is the first category cause from a first vehicle, the system transmits a first command signal for the first vehicle that is decided by an operator to the first vehicle, and applies the first command signal to another vehicle from which the first assistance request is predicted to occur.

Remote assistance management for reducing the load of operators by remote assistance prediction and categorization

According to the remote assistance method of the present disclosure, first, a positional relationship between the vehicle having an autonomous traveling function and an object present around the vehicle at a future time beyond a current time is displayed spatially on a display device, the positional relationship being predicted based on a path plan for autonomous traveling created by the vehicle and information on the object. Next, assistance content input from a remote operator is transmitted to the vehicle. Then, remote assistance corresponding to the assistance content is executed in the vehicle in response to confirmation that the positional relationship between the vehicle and the object displayed on the display device when the assistance content is input is realized after the vehicle receives the assistance content.

Remote assistance method, remote assistance system, and non-transitory computer-readable storage medium

An autonomous running vehicle transmits a camera image around the vehicle photographed by a camera to a remote monitoring center. An obstacle is detected on the basis of information obtained from autonomous sensors including the camera. When an obstacle is detected, the autonomous running vehicle is automatically stopped. The remote monitoring center determines, when the autonomous running vehicle automatically stops, whether or not the run of the autonomous running vehicle is permitted to restart on the basis of the received camera video. When it is determined that the autonomous running vehicle can be restarted, a departure signal is transmitted to the autonomous running vehicle. When the departure signal is received from the remote monitoring center, the autonomous running vehicle restarts running.

Remote monitoring system and an autonomous running vehicle and remote monitoring method

An autonomous driving vehicle provides a driverless transportation service for a user. An alarming phenomenon is a natural phenomenon that potentially causes a disaster. The autonomous driving vehicle recognizes, based on driving environment information, the alarming phenomenon at a current location of the autonomous driving vehicle or on a planned travel route from the current location to a destination. When recognizing the alarming phenomenon, the autonomous driving vehicle determines whether to continue or halt vehicle travel control in accordance with a current travel plan. When determining to halt the vehicle travel control in accordance with the current travel plan, the autonomous driving vehicle sets an emergency plan depending on a type of the alarming phenomenon and controls the autonomous driving vehicle in accordance with the emergency plan.

Autonomous driving vehicle that avoids natural disasters

The transportation vehicle determines whether the calculated distance is equal to or less than the predetermined distance (step S). If the determination result of step Sis positive, the transportation vehicle searches for the closest stoppable location to the current location (step S). The transportation vehicle also performs the pause task at the closest stoppable location. The transportation vehicle performs visualization processing of the surrounding circumstances of the drop-off location, and displays the processed image on touch-screen. The user specifies the detailed drop-off location while looking at the touch-screen (step S).

Automatic drive vehicle

The vehicle dispatching system accepts a dispatch request from a user, selects an autonomous vehicle matching with the dispatch request from among a plurality of autonomous vehicles, and dispatches a selected autonomous vehicle to the user. The plurality of autonomous vehicles include a plurality of battery-mounted vehicles having an in-vehicle battery capable of being charged externally as an energy source. Each of the plurality of battery-mounted vehicles performs charging at a charging station when a charging level of the in-vehicle battery decreases. The vehicle dispatching system comprises a management server including a processor for executing programs stored in memory, the management server programmed to act as a charging planning unit that changes an upper limit charging level of the in-vehicle battery when charging at the charging station according to a time slot.

Vehicle dispatching system and vehicle dispatching method

A vehicle control device includes a failure detection unit configured to detect a failure of a vehicle, and a vehicle controller configured to control the vehicle. The vehicle controller changes the control of the vehicle depending on a failure level when the failure detection unit detects a failure of an on-vehicle component other than the vehicle control device.

Vehicle control device and passenger transportation system

A seat determining apparatus includes a travel route determining unit configured to determine a travel route of a vehicle such that the travel route runs by way of a scheduled boarding point and scheduled alighting point of each of a plurality of users scheduled to ride the vehicle, the scheduled boarding point being a point at which the user is scheduled to get on the vehicle, the scheduled alighting point being a point at which the user is scheduled to get off the vehicle; a boarding and alighting order determining unit configured to determine alighting order, in which the users get off the vehicle, based on the travel route and the scheduled alighting point of each of the users; and a seat determining unit configured to determine a seat according to the alighting order for each of the users when each of the users rides the vehicle.

Seat determining apparatus, seat determining method, and computer program for determining seat

Growing community of inventors

Isehara, Japan

Koji Taguchi