Toyota Research Institute, Inc.

Toyota Jidosha Kabushiki Kaisha

Tokyo Institute of Technology

Junya Ueno

Hiromitsu Urano

Kentaro Ichikawa

Hideyuki Matsui

Hiroshi Sakamoto

Ryosuke Fukatani

Keiji Saneyoshi

Yusuke Kanzawa

Kazuki Tamura

Mark Edward Tjersland

Hiroaki Iwata

A method for controlling a comfort component of a vehicle includes setting a comfort component, while a passenger is occupying the vehicle, to an active state to adjust a temperature within the vehicle to a passenger desired temperature based on receiving an input from the passenger. The method further includes maintaining, after the passenger exited the vehicle, the comfort component in an active state based on a likelihood of the passenger returning to the vehicle satisfying an active state condition. The method still further includes capturing, after the passenger exited the vehicle, an image of a person approaching the vehicle via one or more sensors of the vehicle. The method also includes adjusting the comfort component from the active state to a default state based on an identity of the person being different from an identity of the passenger, the identity of the person being determined based on the image.

Controlling comfort components of a vehicle based on an occupancy state

A method for adjusting a seat in a vehicle includes adjusting the seat from an initial position to a passenger adjusted position based on receiving an input from a passenger. The method further includes determining the passenger exited the vehicle after adjusting the seat and predicting a likelihood of the passenger returning to the vehicle based on determining the passenger exited the vehicle. The method also includes adjusting the seat to the initial position based on the likelihood of the passenger returning is less than a passenger returning threshold. The method still further includes identifying a person approaching the vehicle after the passenger exited the vehicle based on information captured by one or more sensors of the vehicle. The method also includes adjusting the seat to a position associated with the previous passenger based on identifying the person approaching the vehicle as the previous passenger.

Autonomous seat adjustment in a vehicle

System, methods, and other embodiments described herein relate to improving the training of a driver during an automated driving system mode. In one embodiment, a method includes generating, in association with a maneuver by the driver that is a takeover of a vehicle, an automated motion plan associated with the maneuver. The method also includes determining if the automated motion plan is valid based, at least in part, on a condition that one or more parameters of a reliability model satisfy a threshold. The one or more parameters may be associated with the vehicle and a driving environment. The method also includes notifying the driver that the maneuver was unnecessary using a notification signal if the one or more parameters satisfy the threshold.

Systems and methods for training a driver about automated driving operation using a reliability model

A method for controlling a comfort component of a vehicle is presented. The method includes determining that the vehicle has arrived at a destination. The method also includes determining that the comfort component is activated. The method further includes deactivating the comfort component in response to determining that the comfort component is activated and the vehicle has arrived at the destination.

A method for vehicle management performed by a vehicle control system includes monitoring a respective location associated with each vehicle of a plurality of vehicles based on location information transmitted from each of the plurality of vehicles. The method also includes receiving, from a user equipment (UE) associated with a customer, customer location information identifying a location of the customer. The method further includes receiving, from each vehicle of the plurality of vehicles, a set of current compartment climate values based on a triggering event at the vehicle. The method still further includes selecting one vehicle of the plurality of vehicles as a preferred vehicle based on a set of climate preferences associated with the customer. The method also includes transmitting, to the preferred vehicle, a message dispatching the preferred vehicle to the location of the customer, such that the preferred vehicle navigates to the location of the customer.

Remotely controlling comfort components in an autonomous vehicle

A method for vehicle selection performed by a user equipment (UE) associated with a customer includes transmitting, from the UE to a vehicle control system, customer location information identifying a location of the customer. The method also includes receiving, from the vehicle control system based on transmitting the customer location information, vehicle location information and a set of compartment climate values associated with each vehicle of a set of vehicles within a range of the location of the customer. The method further includes outputting the current compartment climate value and a location associated with the vehicle location information of each vehicle of the set of vehicles for display at the UE. The method still further includes transmitting, to the vehicle control system, a message indicating a selection of one vehicle of the set of vehicles based on receiving a customer input at the UE, the one vehicle being selected based on one or both of the current compartment climate value of the one vehicle and the location associated with the vehicle location information of the one vehicle.

A method for controlling a driving condition component of a vehicle includes disabling automatic operation of the driving condition component based on enabling an autonomous operating mode of the vehicle. The method also includes determining, while the vehicle is operating in the autonomous mode, a current condition satisfies an unsafe driving condition for a manual operating mode of the vehicle. The method further includes enabling the driving condition component to mitigate based on predicting a human occupant will enable the manual operating mode during a time period associated with the current condition, the driving condition component being enabled prior to the human occupant switching from the autonomous operating mode to the manual operating mode.

Controlling driving condition components of an autonomous vehicle based on a current driving mode and current conditions

System, methods, and other embodiments described herein relate to a training system to train a driver about occurrences of anomalous driving events of automated vehicle systems. In one embodiment, a method includes determining, upon receiving a selection of a vehicle behavior from one or more anomalous driving events and a detected state change signal, whether the vehicle behavior affects one or more entities. The method includes assessing a state of the one or more entities to simulate the vehicle behavior according to a safety standard. The method includes triggering simulation of the vehicle behavior if the state satisfies a threshold. The method includes simulating the vehicle behavior by at least controlling the vehicle to simulate the vehicle behavior during automated driving of the vehicle.

Systems and methods for driver training during operation of automated vehicle systems

System, methods, and other embodiments described herein relate to improving automated driving by testing for inputs during driving. In one embodiment, a method includes testing an input from a driver in a manual driving mode of a vehicle. The method also includes adapting a fixed time interval on a condition that a test result of the input satisfies criteria used to validate driver inputs. The method also includes monitoring, via an input system of the vehicle, for driver feedback according to the fixed time interval in an automated driving mode.

Systems and methods for testing of driver inputs to improve automated driving

In step S, a color image CIMG is acquired. In step S, a distance image DIMG is acquired. In step S, the color image CIMG is projected onto the distance image DIMG. An alignment of the color image CIMG and the distance image DIMG is performed prior to the projection of the color image CIMG. In step S, it is determined whether or not a basic condition is satisfied. In S, it is determined whether or not a special condition is satisfied. If a judgement result of the steps Sor Sis positive, then in step Sa first data point and a second data point on the distance image DIMG are associated. If bot of the judgement results of steps Sand Sare negative, data points are not associated in step S

Object recognition device

A method for controlling an operating mode of a vehicle is presented. The method includes determining a current range of the vehicle while the vehicle is operating in a first operating mode. The method also includes determining a distance to a destination. The method further includes controlling the vehicle to operate in a second operating mode instead of the first operating mode when the range is less than the distance to the destination.

Adjusting an operating mode of a vehicle based on an expected resource level

An object recognition apparatus include a storage device and a processor. The storage device stores peripheral information and tolerance information. The tolerance information is information in which the degree of tolerance for the undetected object is represented for each class of the object. The peripheral information is acquired by a sensor device provided in the vehicle. The processor performs object recognition process for recognizing an object around the vehicle. In the object recognition process, the processor identifies the object and its class to be detected based on the peripheral information, and calculates the likelihood that is a parameter representing the probability of detection of the object. Further, the processor calculates a likelihood threshold corresponding to the object based on the tolerance information, and determines whether to output the identification result of the object based on the comparative between the likelihood and the likelihood threshold.

Object recognition apparatus

System, methods, and other embodiments described herein relate to improving driver warnings for automated driving by a vehicle. In one embodiment, a method includes monitoring a vehicle control system for driver feedback during the automated driving. The method also includes adapting a points value at a defined rate according to whether the driver feedback is present. The method also includes, responsive to determining that the points value satisfies a threshold before the driver feedback is present, generating a warning to a driver.

Systems and methods for improving driver warnings during automated driving

In one embodiment, a system for correcting parallax error is provided. An image is received from a camera and a plurality of points is received from a LiDAR sensor. The points are placed on the image based on coordinates associated with each point. The image is divided into a plurality of cells by placing a grid over the image. For each cell, a minimum distance between the points in the cell and the camera is determined. For each cell, a margin is calculated based on the determined minimum distance. For each cell, points that have a distance from the camera that is greater than the minimum distance plus the margin are removed or deleted. The image and/or the remaining points are then used to provide one or more vehicle functions.

Systems and methods for correcting parallax

System, methods, and other embodiments described herein relate to improving the training of a driver during automated driving system mode. In one embodiment, a method includes generating, in association with a vehicle takeover and a maneuver by the driver, an automated motion plan associated with the maneuver. The method also includes determining if a difference parameter satisfies a threshold, wherein the difference parameter indicates a disparity between the maneuver by the driver in relation to the automated motion plan associated with the maneuver. The method also includes notifying, if the difference parameter does not satisfy the threshold, the driver that the vehicle takeover and the maneuver by the driver were unnecessary.

Growing community of inventors

Ann Arbor, MI, United States of America

Junya Ueno