Jason E Schell, 42141 W Market St UNIT 1B, York, PA 17401

2021004, Feb 18, 2021

Aug 14, 2019

16/540676

- Plano TX, US
Jason Schell - Dallas TX, US
Neil Dutta - Addison TX, US

G08G 1/0967
G08G 1/0968
H04W 4/44
G08G 1/01
G01C 21/34

Systems and methods for roadway obstruction detection are disclosed herein. One embodiment receives information pertaining to a potential roadway obstruction; determines that additional information regarding the potential roadway obstruction is needed to identify the potential roadway obstruction; selects one or more vehicles from a plurality of vehicles based, at least in part, on their proximity to the potential roadway obstruction and their sensor capabilities; and determines that the potential roadway obstruction is a specific type of roadway obstruction based, at least in part, on additional information regarding the potential roadway obstruction received from at least one of the selected one or more vehicles.

2021005, Feb 18, 2021

Aug 14, 2019

16/540703

- PLANO TX, US
JASON O. SCHELL - Dallas TX, US

H04W 72/12
H04W 4/40
G08G 1/09

Vehicles, media, and methods are provided for sharing vehicle map data over transmission media selected according to urgency of the map data. One vehicle includes a hardware processor; and a non-transitory machine-readable storage medium encoded with instructions executable by the hardware processor to perform a method comprising: receiving information relating to a road; determining an urgency level of the information; selecting one of a plurality of transmission media according to the determined urgency level; and transmitting the information over the selected transmission medium.

2020027, Sep 3, 2020

Feb 28, 2019

16/288781

- Plano TX, US
Jason Schell - Dallas TX, US
Neil Dutta - Addison TX, US

B60W 40/02
G01W 1/10
G01C 21/36
G05D 1/00
G05D 1/02

Systems and methods for vehicle-based weather detection are disclosed herein. The systems and methods can include selecting one or more vehicles from a plurality of vehicles based on one or more network membership parameters. One or more data acquisition networks can be formed using the one or more selected vehicles. Sensor data can be received from the one or more data acquisition networks. One or more weather conditions can be predicted using the sensor data. One or more environmental elements can be updated based on the predicted weather conditions.

2020018, Jun 11, 2020

Dec 6, 2018

16/212004

- Plano TX, US
Jason Schell - Dallas TX, US

Toyota Motor North America, Inc. - Plano TX

G06T 19/00
G06K 9/00
G06K 9/62

An augmented reality inspection system includes a computing device having a processor and a non-transitory computer readable memory, a camera and display device communicatively coupled to the computing device, and a machine-readable instruction set stored in the non-transitory computer readable memory. The machine-readable instruction set causes the augmented reality inspection system to capture an image of a portion of a vehicle with the camera, compare the image of the portion of the vehicle to an image of an acceptable vehicle configuration, determine whether features within the image of the portion of the vehicle matches at least one acceptable vehicle configuration based on the image of the acceptable vehicle configuration, and in response to determining that the features does not match at least one acceptable vehicle configuration, present on the display device a highlighted portion identifying the features within the image of the portion of the vehicle that does not match.