Toyota Motor North America, Inc.

Toyota Connected North America, Inc.

Toyota Jidosha Kabushiki Kaisha

Ciena Corporation

Motioncorrect Inc.

Toyota Conected North America, Inc.

Yang Ding

Sergei I Gage

Simon P Roberts

Christopher J Macpherson

Daniel Warren Reaser

Derek A Thompson

Keaton Khonsari

Jessica May

Michael R Kushnerik

Cory M Frank

Naohiro J Matsumura

Matthew J Everett

Priyanth Mehta

Andrew Kam

Nathan Lam

Bou-Phon Chang

An example operation includes recording, from a vehicle sensor, data indicative of a plurality of movements of a first occupant in an interior of a vehicle; determining, from the recording, a first maximum range of extension among the plurality of movements, and a first amount of time between a first movement and a second movement of the plurality of movements; and assigning the first occupant to one of a plurality of age groups, based upon the determining.

In-cabin occupant age determination

An example operation includes one or more of determining a movement of an occupant in a vehicle, determining an atypical health condition based on the movement and a position of the occupant in the vehicle, determining if the occupant is breathing, based on an analysis performed by the vehicle, verifying the atypical health condition by the vehicle, based on received data from a device proximate the occupant, and sending a notification to an entity, based on the verification.

Occupant condition detection and response

An example operation includes one or more of receiving a call on a device associated with an occupant of a vehicle, determining a noise level proximate the occupant, and directing the call to a speaker proximate the occupant, based on the noise level.

Dynamic audio control

An example operation includes one or more of receiving a scan of a cabin of a vehicle, wherein the scan includes a spatial region inside the vehicle and outside the vehicle proximate at least one vehicle door, determining at least one occupant characteristic based on the scan, including a classification detection and a presence detection of at least one seat inside the vehicle, determining a cabin status based on the at least one occupant characteristic and communicating the cabin status to a mobile device.

In-cabin detection framework

An example operation includes detecting, by a vehicle, a location of a first potential passenger proximate to a road; determining, by the vehicle, a first road safety level of a pick-up for the first potential passenger; denying, by the vehicle, the pick-up for the first potential passenger when the determined first road safety level is below a threshold; determining, by the vehicle, a second road safety level of a pick-up for a second potential passenger; and picking up, by the vehicle, the second potential passenger, when the second road safety level is above the threshold.

Vehicle action determination based on occupant characteristics

An example operation includes one or more of determining one or more objects in a transport that may become airborne and altering a portion of the transport to minimize the one or more objects from becoming airborne during a collision.

Minimizing airborne objects in a collision

Provided is a process that includes one or more of receiving data from sensors on a vehicle, where the data is associated with an internal environment of the vehicle and characteristics of an occupant of the vehicle and modifying functionality of the vehicle based on the received data. Modifying functionality includes updating a graphical user interface (GUI) of the vehicle and a GUI of a device associated with the occupant.

Dynamic GUI based on enhanced functionality

Display screen or portion thereof with graphical user interface

An example operation includes one or more of detecting a movement of an object in a vehicle when the vehicle is in motion, and determining that the object is an inanimate object, based on a vertical and horizontal distance of the detected movement.

In-cabin occupant detection

An example operation includes one or more of determining a level of risk of a collision of a transport, wherein the level of risk is related to an occupant of the transport and an environment of the transport, accumulating an amount of data based on the level of risk, preparing the accumulated data for sending to one or more recipients when the level of risk exceeds a risk threshold, and sending the prepared data to the one or more recipients when the collision occurs.

Message construction based on potential for collision

An example operation includes one or more of detecting a living element in a transport, determining a dangerous condition exists in response to an internal temperature of the transport is outside of a threshold and a negative characteristic is associated with the living element, and positioning the transport to a location to reduce the dangerous condition.

Protecting living objects in transports

Systems, methods, and other embodiments described herein relate to sensing ingress of water in a vehicle. In one embodiment, a method includes acquiring, from a radar of a vehicle, radar data about a passenger cabin of the vehicle. The method includes determining a current state of the passenger cabin according to the radar data. The method includes, responsive to identifying that the current state indicates an ingress of water into the passenger cabin, generating a response to the ingress of the water.

Sensing the ingress of water into a vehicle

Systems and methods are provided for enhancing techniques for provisioning optical channels to allow optical networks to operate in an optimal fashion. A method, according to one implementation, includes receiving measured optical performance parameters of a plurality of optical channels transmitted over an optical spectrum between two network elements in an optical line system; determining a performance profile of the optical spectrum based on the measured optical performance parameters; translating the performance profile into configuration information for the two network elements; and causing provisioning of the two network elements based on the configuration information. The measured optical performance parameters are for one or more unassigned optical channels on the optical spectrum, with the measured optical performance parameters being made on one or more optical modems.

Autonomous, zero touch provisioning of optical channels in optical line systems

System, methods, and other embodiments described herein relate to adapting vehicle access by detecting a person carrying an object. In one embodiment, a method includes detecting a person near a vehicle for gaining access. The method also includes scanning the person for an object using a radar of the vehicle, wherein information from the radar indicates densities of the person and the object. Upon detecting the object using the densities, the method also includes adapting the access to a compartment of the vehicle.

Systems and methods for detecting carried objects to adapt vehicle access

An example operation includes one or more of determining a characteristic of an occupant in a transport and a current driving environment of the transport, wherein the characteristic includes a position of the occupant, determining that the current driving environment will lead to a collision of the transport, and based on a predicted result of the collision, sending a predicted state of the occupant based on the position, to an emergency service node.

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Montreal, Canada

Yang Ding