Toyota Jidosha Kabushiki Kaisha

Taichi Kawanai

Yusuke Hayashi

Nobuhide Kamata

Daichi Hotta

Keisuke Hokai

Eiji Sakaguchi

Yasuhiro Takagi

Kazuhiko Kamikado

Hideyuki Matsui

Masahiro Harada

Hideo Fukamachi

Sadayuki Abe

Kentaro Ichikawa

Yoshinori Watanabe

Tomoyuki Kuriyama

Taisuke Sugaiwa

Yasuhiro Kobatake

Takahiro Yokota

Atsushi Sone

Yuki Okamoto

Hayato Ito

Shintaro Shiba

Kosuke Futagami

Atsushi Kodama

Yosuke Hirate

Sho Amagai

A moving body control system executes a localization process that estimates a position of a moving body based on sensor-detected information and feature object map information indicating a position of a feature object. The moving body control system executes driving assist control based on the estimated position of the moving body. A first range includes the estimated position of the moving body and becomes larger as reliability of the localization process becomes lower. A first future range is at least a part of an expected passing range of the first range. When an obstacle is present in the first range or the first future range, the moving body control system makes the moving body decelerate or stop. When no obstacle is present in the first range or the first future range, the moving body control system continues the driving assist control.

Moving body control system and moving body control method

A vehicle control apparatus for performing autonomous driving of a host vehicle. The vehicle control apparatus includes an operating section information acquisition unit configured to acquire operating section information that is information of an operating section in which vehicle stability control by brake control has been operated in a vehicle in autonomous driving in the past; an operation plan generation unit configured to generate an operation plan of autonomous driving of the host vehicle based on a preset target route and map information; and a vehicle controller configured to perform autonomous driving along the operation plan, wherein the operation plan generation unit generates the operation plan so that the host vehicle does not stop in the operating section.

Vehicle control apparatus

A control apparatus according to the present disclosure is configured to execute the following first to five processes. The first process is a localization of a moving body. The second process is revising an estimated position obtained by the localization such that a displacement amount with respect to a previous position is within a predetermined range. The third process is regarding a revised estimated position obtained as a position of the moving body in a current process, and performing a control of the moving body based on the revised estimated position. The fourth process is detecting a poor accuracy of the localization based on a difference between the estimated position and the revised estimated position. The fifth process is performing an emergency control corresponding to a magnitude of the difference when the poor accuracy of the localization is detected.

Control apparatus, control method, and non-transitory computer readable recording medium for controlling a moving body based on an estimated position

According to the method of the present disclosure, first, a plurality of data sets is generated from a travel log data group. Each of the plurality of data sets includes one or a plurality of travel log data. Next, map data for evaluation is generated from each of the plurality of data sets. Then, abnormal map data included in a plurality of map data for evaluation generated from the plurality of data sets is specified by comparing the plurality of map data for evaluation with each other. Then, abnormal travel log data is specified by comparing a data set used to generate the abnormal map data with a data set used to generate map data for evaluation other than the abnormal map data. And finally, final map data is generated using a data set that does not include the abnormal travel log data.

Method and apparatus for generating map data, and non-transitory computer-readable storage medium

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 method for inspecting a road surface condition includes the steps of obtaining detailed information on a road surface condition set for each inspection point based on a traveling record of a vehicle, and information on an own position of the vehicle, generating an inspection execution plan of the vehicle in the inspection point when the inspection point is included in a predetermined range in an advancing direction of the vehicle with the own position as a reference, performing evaluation of a road surface condition in the inspection point based on a traveling condition of the vehicle that is obtained during the inspection execution plan, and updating the detailed information on a road surface condition set for the inspection point based on latest information on the road surface condition the evaluation of which is performed.

Method for inspecting road surface condition, road surface condition inspection device, and road surface condition inspection system

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 control system according to the present disclosure comprises one or more memories and one or more processors. The one or more memories are configured to store observation data detected by one or more sensors installed in a moving body and an estimated position of the moving body. The one or more processors are configured to execute the following first to third processes. The first process is calculating the estimated position at a current time based on at least the estimated position calculated in a previous process and the observation data up to the current time. The second process is recalculating the estimated position at a past predetermined time. The third process is evaluating accuracy of the estimated position at the current time based on a difference between the estimated position at the past predetermined time stored in the memory and the recalculated estimated position.

Control system, control 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.

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Susono, Japan

Taichi Kawanai