Gautam Muralidhar

US Patent:

20180372504, Dec 27, 2018

Filed:

Jun 27, 2017

Appl. No.:

15/634197

Inventors:

- San Jose CA, US
Nadav Aharony - Mountain View CA, US
Anthony Tao Liang - Palo Alto CA, US
Gautam Muralidhar - San Jose CA, US

International Classification:

G01C 21/34
G08G 1/01

Abstract:

The systems and methods described herein can be applied to a vehicle equipped with a sensor suite that can observe information about a location, for example, a traffic light duration. The system can record information, e.g., the traffic light colors, duration of color changes, and location of the traffic lights and can upload this information to the cloud. Then, the system can augment or learn about the location, e.g., learning of traffic patterns, and store the augmented data as database-based information, where available. The learned information can help a requesting vehicle to better estimate an estimated time of arrival (ETA) for common routes taken, provide more accurate ETAs based on historical knowledge, and/or calculate or provide alternative route information.

US Patent:

20180141568, May 24, 2018

Filed:

Dec 30, 2016

Appl. No.:

15/395924

Inventors:

- San Jose CA, US
Gautam Muralidhar - San Jose CA, US
Christopher F. Pouliot - San Mateo CA, US
Edward H. Baik - Mountain View CA, US
Jonathan A. Cox - San Jose CA, US

International Classification:

B60W 50/08
B60W 40/09
G05D 1/00
G05D 1/02
B60W 50/00
A61B 5/18
A61B 5/16
A61B 5/024
A61B 5/08
A61B 5/01

Abstract:

Embodiments herein relate to an autonomous vehicle or self-driving vehicle. The level of comfort with autonomous driving offered to the user and the parameters of operation of the autonomous vehicle might increase or decrease a driver's comfort (anxiety) with the vehicle. Sensors in the vehicle can detect a user's driving style, comfort level and may propose an autonomy level to the user and/or parameters of operation.

US Patent:

20180143639, May 24, 2018

Filed:

Dec 30, 2016

Appl. No.:

15/395952

Inventors:

- San Jose CA, US
Gautam Muralidhar - San Jose CA, US
Christopher F. Pouliot - San Mateo CA, US
Edward H. Baik - Mountain View CA, US
Jonathan A. Cox - San Jose CA, US

International Classification:

G05D 1/02
G01C 21/34
G01C 21/36

Abstract:

Embodiments herein can determine an optimal route for an autonomous electric vehicle. The system may score viable routes between the start and end locations of a trip using a numeric or other scale that denotes how viable the route is for autonomy. The score is adjusted using a variety of factors where a learning process leverages both offline and online data. The scored routes are not based simply on the shortest distance between the start and end points but determine the best route based on the driving context for the vehicle and the user.