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1. US20180276991 - Hybrid distributed prediction of traffic signal state changes

Office
United States of America
Application Number 15993417
Application Date 30.05.2018
Publication Number 20180276991
Publication Date 27.09.2018
Grant Number 10140862
Grant Date 27.11.2018
Publication Kind B2
IPC
G08G 1/0967
GPHYSICS
08SIGNALLING
GTRAFFIC CONTROL SYSTEMS
1Traffic control systems for road vehicles
09Arrangements for giving variable traffic instructions
0962having an indicator mounted inside the vehicle, e.g. giving voice messages
0967Systems involving transmission of highway information, e.g. weather, speed limits
B60R 1/00
BPERFORMING OPERATIONS; TRANSPORTING
60VEHICLES IN GENERAL
RVEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
1Optical viewing arrangements
G06K 9/00
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
G08G 1/01
GPHYSICS
08SIGNALLING
GTRAFFIC CONTROL SYSTEMS
1Traffic control systems for road vehicles
01Detecting movement of traffic to be counted or controlled
G08G 1/0962
GPHYSICS
08SIGNALLING
GTRAFFIC CONTROL SYSTEMS
1Traffic control systems for road vehicles
09Arrangements for giving variable traffic instructions
0962having an indicator mounted inside the vehicle, e.g. giving voice messages
CPC
B60R 1/00
BPERFORMING OPERATIONS; TRANSPORTING
60VEHICLES IN GENERAL
RVEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
1Optical viewing arrangements
G06K 9/00825
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
00624Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
00791Recognising scenes perceived from the perspective of a land vehicle, e.g. recognising lanes, obstacles or traffic signs on road scenes
00825Recognition of vehicle or traffic lights
G08G 1/0116
GPHYSICS
08SIGNALLING
GTRAFFIC CONTROL SYSTEMS
1Traffic control systems for road vehicles
01Detecting movement of traffic to be counted or controlled
0104Measuring and analyzing of parameters relative to traffic conditions
0108based on the source of data
0116from roadside infrastructure, e.g. beacons
G08G 1/0129
GPHYSICS
08SIGNALLING
GTRAFFIC CONTROL SYSTEMS
1Traffic control systems for road vehicles
01Detecting movement of traffic to be counted or controlled
0104Measuring and analyzing of parameters relative to traffic conditions
0125Traffic data processing
0129for creating historical data or processing based on historical data
G08G 1/0141
GPHYSICS
08SIGNALLING
GTRAFFIC CONTROL SYSTEMS
1Traffic control systems for road vehicles
01Detecting movement of traffic to be counted or controlled
0104Measuring and analyzing of parameters relative to traffic conditions
0137for specific applications
0141for traffic information dissemination
G08G 1/09623
GPHYSICS
08SIGNALLING
GTRAFFIC CONTROL SYSTEMS
1Traffic control systems for road vehicles
09Arrangements for giving variable traffic instructions
0962having an indicator mounted inside the vehicle, e.g. giving voice messages
09623Systems involving the acquisition of information from passive traffic signs by means mounted on the vehicle
Applicants TRAFFIC TECHNOLOGY SERVICES, INC.
Inventors Kiel Roger Ova
Thomas Bauer
Jingtao Ma
Kyle Zachary Hatcher
Agents FisherBroyles LLP
Micah D. Stolowitz
Title
(EN) Hybrid distributed prediction of traffic signal state changes
Abstract
(EN)

Computer-implemented predictions of upcoming traffic control signal states or state changes can be used to improve driver convenience, safety, and fuel economy. Such information can be used advantageously by a human operator, or by an autonomous or semi-autonomous vehicle control system. Predictions can be computed with suitable machines installed in a vehicle, in cooperation with a remote back-end server system. The prediction computations in the vehicle may be supported by data communicated to the vehicle computing machinery over various wireless communications, including telecom systems, DSRC, etc.

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