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1. US20180284770 - Machine-learning based autonomous vehicle management system

Office United States of America
Application Number 15475228
Application Date 31.03.2017
Publication Number 20180284770
Publication Date 04.10.2018
Grant Number 10248121
Grant Date 02.04.2019
Publication Kind B2
IPC
G05D 1/00
GPHYSICS
05CONTROLLING; REGULATING
DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
1Control of position, course, altitude, or attitude of land, water, air, or space vehicles, e.g. automatic pilot
G01C 21/26
GPHYSICS
01MEASURING; TESTING
CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
21Navigation; Navigational instruments not provided for in groups G01C1/-G01C19/104
26specially adapted for navigation in a road network
G01C 21/34
GPHYSICS
01MEASURING; TESTING
CMEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
21Navigation; Navigational instruments not provided for in groups G01C1/-G01C19/104
26specially adapted for navigation in a road network
34Route searching; Route guidance
G06N 99/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
99Subject matter not provided for in other groups of this subclass
G05D 1/02
GPHYSICS
05CONTROLLING; REGULATING
DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
1Control of position, course, altitude, or attitude of land, water, air, or space vehicles, e.g. automatic pilot
02Control of position or course in two dimensions
CPC
G05D 1/0088
GPHYSICS
05CONTROLLING; REGULATING
DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
1Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
0088characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
G05D 1/0221
GPHYSICS
05CONTROLLING; REGULATING
DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
1Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
02Control of position or course in two dimensions
021specially adapted to land vehicles
0212with means for defining a desired trajectory
0221involving a learning process
G05D 1/0231
GPHYSICS
05CONTROLLING; REGULATING
DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
1Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
02Control of position or course in two dimensions
021specially adapted to land vehicles
0231using optical position detecting means
G05D 1/0257
GPHYSICS
05CONTROLLING; REGULATING
DSYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
1Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
02Control of position or course in two dimensions
021specially adapted to land vehicles
0257using a radar
G06N 99/005
Applicants Uber Technologies, Inc.
Inventors Dirk John VandenBerg, III
Agents Dority & Manning, P.C.
Title
(EN) Machine-learning based autonomous vehicle management system
Abstract
(EN)

Systems and methods for managing autonomous vehicles to address traffic anomalies are provided. In one example embodiment, a method includes detecting, by one or more computing devices, an existence of a traffic anomaly within a geographic area. The method includes determining, by the one or more computing devices, at least one autonomous vehicle to address the traffic anomaly within the geographic area. The method includes providing, by the one or more computing devices, a communication to the at least one autonomous vehicle instructing the autonomous vehicle to enter into a traffic reduction operation mode to address the traffic anomaly. The traffic reduction operation mode is based at least in part on a profile associated with the traffic reduction operation mode. The profile associated with the traffic reduction operation mode is stored onboard the autonomous vehicle. The autonomous vehicle is configured to operate in the traffic reduction operation mode.