Other

Toyota Jidosha Kabushiki Kaisha

Dustin Harber

Vinuth Rai

Divya Sai Toopran

Matthew Kresse

Ugur Oezdemir

Kentaro Oguchi

Roger D Melen

Tim Uwe Falkenmayer

Hidenobu Suzuki

Shazaan Bahrainwala

The disclosure includes embodiments for providing secure package delivery for a vehicle. In some embodiments, a method includes receiving, by a Dedicated Short Range Communication radio (a DSRC radio) of a vehicle, a DSRC message. In some embodiments, the method includes unlocking a trunk of the DSRC-equipped vehicle responsive to receiving the DSRC message by the DSRC radio.

Delivery security for a parked vehicle

The disclosure includes a method for determining, based on vehicle sensor data associated with a vehicle, a current vehicle condition associated with the vehicle that is detrimental to operation of the vehicle and receiving a condition message that includes mitigating action plan data describing one or more steps configured to alter the current vehicle condition, the mitigating action plan data including an offer fulfillment location included in a route of a journey for the vehicle.

Wireless incentive system for vehicle users

The disclosure includes a system and method for determining, based on vehicle sensor data associated with the vehicle, a current vehicle condition that is detrimental to operation of the vehicle, transmitting, by a mobile computing device programmed to perform the transmitting, a description of the current vehicle condition to a condition message provider, and receiving a condition message that includes offer data and mitigating plan data describing one or more steps configured to alter the current vehicle condition.

A system or method for providing recommended items for presentation to users and/or consideration by vehicle systems may be executable to: retrieve social network data associated with a user; extract a keyword and/or a key phrase from the social network data; and determine a preference model that includes a frequency analysis associated with the keyword and/or the key phrase and indicating how often the keyword and/or the key phrase are observed in the social network data. The system may further receive a request for content data; search a content database to retrieve one or more content items based on the frequency analysis associated with the preference model; generate one or more recommended items for the user or for a vehicle system from the one or more content items; and provide the one or more recommended items for presentation to the user or for processing by the vehicle system.

System for dynamic content recommendation using social network data

A system and method for regulating media volume is disclosed. The system comprises a prediction engine and a regulation module. The prediction engine collects sensor data and scene category data. The scene category data includes data describing an environment in which the media volume is regulated. The prediction engine predicts a workload for a user based at least in part on the scene category data and the sensor data and generates a predicted workload value for the predicted workload. The regulation module adjusts the media volume based at least in part on the predicted workload value.

Media volume control system

A system and method for estimating street parking availability for a user is disclosed. The system comprises a communication module and a parking probability generator. The communication module receives data describing a set of traces for a group of vehicles associated with a group of users. The parking probability generator assigns the set of traces to one or more street segments based at least in part on street segment data describing the one or more street segments. The parking probability generator generates one or more parking probabilities for the one or more street segments based at least in part on one or more user densities in the one or more street segments.

Street parking availability estimation

A system and method for in-vehicle content recommendation is disclosed. The system comprises an aggregator module, a modeler module and a recommendation module. The aggregator module aggregates content data describing content such as a music, a news program, a podcast, an audio book, a movie, a television program, etc. The aggregator module also aggregates situation data describing an environment in which the content was recommended to a user, and feedback data describing the user's response to the recommendation. The modeler module generates a content preference model. The content preference model represents the user's dynamic content preferences based at least in part on the aggregated data. The recommendation module generates a first content recommendation based at least in part on the content preference model.

Growing community of inventors

San Ramon, CA, United States of America

Dustin Harber