Other

Toyota Jidosha Kabushiki Kaisha

Rahul Parundekar

Kentaro Oguchi

Preeti Jayagopi Pillai

John Mark Agosta

Daisuke Hiroki

Veera Ganesh Yalla

Veeraganesh Yalla

Roger D Melen

Emrah Akin Sisbot

Shojiro Takeuchi

Takuya Hasegawa

Vinuth Rai

Divya Sai Toopran

Rama Vuyyuru

The disclosure includes implementations for executing one or more computations for a vehicle. Some implementations of a method for a vehicle may include identifying one or more computations as being un-executable by any processor-based computing device of the vehicle. The method may include generating a query including query data describing the one or more computations to be executed for the vehicle. The method may include providing the query to a network. The method may include receiving a response from the network. The response may include solution data describing a result of executing the one or more computations. The response may be provided to the network by a processor-based computing device included in a hierarchy of processor-based computing devices that have greater computational ability than any processor-based computing devices of the vehicle.

Situational understanding of unknown roadway conditions that are ahead for a connected vehicle

The disclosure includes a system and method for provisioning wireless application services in sparsely connected wireless environments. The system includes a processor and a memory storing instructions that, when executed, cause the system to: estimate journey requirements; generate a current connectivity map based on driving-related data; generate a current connectivity map based on driving-related data; estimate services for a current journey; and generate a prioritized list of services and at least one expiration time for one of the services.

Providing wireless services to a connected vehicle

The disclosure includes a system and method for providing recommendation items to users. The system includes a processor and a memory storing instructions that when executed cause the system to: receive identification input data associated with a user; identify the user using the identification input data; receive sensor data; determine a current situation associated with the user from one or more predefined situations described by predefined situation data and associated parameters; receive data describing a set of candidate items; generate a set of efficacy scores for the set of candidate items; eliminate one or more candidate items from the set of candidate items to obtain one or more remaining candidate items; rank the one or more remaining candidate items based on one or more associated efficacy scores; and provide one or more recommendation items to the user from the one or more ranked remaining candidate items.

Content recommendation based on efficacy models

In an example embodiment, a computer-implemented method is disclosed that generates a spectral signature describing one or more dynamic objects and a scene layout of a current road scene; identifies, from among one or more scene clusters included in a familiarity graph associated with a user, a road scene cluster corresponding to the current road scene; determine a position of the spectral signature relative to other spectral signatures comprising the identified road scene cluster; and generates a familiarity index estimating familiarity of the user with the current road scene based on the position of the spectral signature. The method can further include determining an assistance level based on the familiarity index of the user; and providing one or more of an auditory instruction, a visual instruction, and a tactile instruction to the user via one or more output devices of a vehicle at the determined assistance level.

Generating real-time driver familiarity index for fine-grained dynamic road scenes

In an example embodiment, a computer-implemented method is disclosed that receives road scene data and vehicle operation data from one or more sensors associated with a first vehicle on a road segment; receives situation ontology data; automatically generates a semantic road scene description of the road segment using the road scene data, the vehicle operation data, and the situation ontology data; and transmits, via a communication network, the semantic road scene description to one or more other vehicles associated with the road segment. Automatically generating the semantic road scene description of the road segment can include determining lane-level activity information for each lane based on lane information and dynamic road object information and determining a lane-level spatial layout for each lane based on the lane information and the dynamic road object information.

Understanding road scene situation and semantic representation of road scene situation for reliable sharing

The disclosure includes a system and method for optimizing a bus to log sensor data. The system includes a processor and a memory storing instructions that, when executed by the processor, cause the system to: estimate a use case of a journey of a mobile device; retrieve a set of sensor configuration parameters associated with the estimated use case; and configure one or more sensors according to the set of sensor configuration parameters to operate during at least a portion of the journey according to the set of sensor configuration parameters.

Bus optimization to log sensor data

The disclosure includes a method for autocompleting an in-vehicle operation that includes monitoring sensors for sensor data. The method includes determining an occurrence of an initial vehicle operation performed by a user based on the sensor data. The method includes determining a vehicle task from a digitally stored dataset based on the initial vehicle operation. The method includes determining a next vehicle operation to autocomplete based on the vehicle task. The method includes autocompleting the next vehicle operation. The method includes determining whether the vehicle task is complete.

Proactive autocomplete of a user's in-vehicle operations

The disclosure includes a system and method for configuring custom vocabularies for personalized speech recognition. The system includes a processor and a memory storing instructions that when executed cause the system to: detect a provisioning trigger event; determine a state of a journey associated with a user based on the provisioning trigger event; determine one or more interest places based on the state of the journey; populate a place vocabulary associated with the user using the one or more interest places; filter the place vocabulary based on one or more place filtering parameters; and register the filtered place vocabulary for the user.

Configuring dynamic custom vocabulary for personalized speech recognition

The disclosure includes a speech-enabled device and method to share speech dialog capabilities of the speech-enabled device with a dumb device. The speech-enabled device includes a processor and a memory storing instructions that, when executed by the processor, cause the speech-enabled device to: receive speech dialog data of the dumb device that indicates a function of the dumb device; receive speech input; determine the function of the dumb device to be invoked based on the speech input by using the speech dialog data; generate a command effective to invoke the function of the dumb device based on the speech dialog data; and send the command to the dumb device to invoke the function of the dumb device.

Sharing speech dialog capabilities of a vehicle

The disclosure includes a system, method and tangible memory for providing a driver familiarity adapted explanation to a driver of a vehicle. The system includes a sensor set configured to measure sensor data describing a task and the driver. The system also includes an onboard vehicle computer including a tangible memory, a processor, a task tracker and a familiarity application. The task tracker causes the processor to determine a vehicle operation to be proactively performed by the task tracker to autocomplete the task. The familiarity application causes the processor to execute steps including estimating how familiar the driver is with the vehicle operation based on the sensor data describing the driver of the vehicle, retrieving a template explanation associated with the vehicle operation, and adapting the template explanation to generate a driver familiarity adapted explanation describing the autocomplete of the vehicle operation.

Driver familiarity adapted explanations for proactive automated vehicle operations

A system and method for estimating a place affinity for a user is disclosed. The system comprises a gathering module, a communication module and a scoring module. The gathering module receives a place and retrieves rich place data associated with the place. The communication module retrieves user profile data associated with a user and a place affinity model associated with the user. The scoring module estimates an affinity score for the place using the place affinity model based at least in part on the rich place data and the user profile data.

Growing community of inventors

Sunnyvale, CA, United States of America

Rahul Parundekar