WO2009006059A3 - Predictive models of road reliability for traffic sensor configuration and routing - Google Patents

Predictive models of road reliability for traffic sensor configuration and routing Download PDF

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Publication number
WO2009006059A3
WO2009006059A3 PCT/US2008/067820 US2008067820W WO2009006059A3 WO 2009006059 A3 WO2009006059 A3 WO 2009006059A3 US 2008067820 W US2008067820 W US 2008067820W WO 2009006059 A3 WO2009006059 A3 WO 2009006059A3
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WO
WIPO (PCT)
Prior art keywords
road
sensed
variance
predictive models
traffic
Prior art date
Application number
PCT/US2008/067820
Other languages
French (fr)
Other versions
WO2009006059A2 (en
Inventor
Eric J Horvitz
Sridhar Srinivasan
Original Assignee
Microsoft Corp
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Microsoft Corp filed Critical Microsoft Corp
Publication of WO2009006059A2 publication Critical patent/WO2009006059A2/en
Publication of WO2009006059A3 publication Critical patent/WO2009006059A3/en

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Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions

Abstract

Methods for decision making about sensor location/configuration for traffic sensing and routing are described. Construction of predictive models via machine learning that infer variance of road speeds, in general or for specific contexts (e.g., rush hours for a traffic system) occurs. Predictive models for road reliability are built from libraries of data about sensed variances and road segments. The datasets include information for road segments monitored by fixed sensors/moving probes, road segment properties, geometric relationships among road segments, and proximal resources. Road segments are labeled by the sensed variance seen in traffic speeds over similar contexts. A model is created that can apply estimates of the variance of the traffic speed for a segment, including non-sensed segments via generalization to non-sensed road segments. Methods are described for employing predictive models of variance, along with demand and propagation models, to make decisions about configuration of sensors.
PCT/US2008/067820 2007-06-29 2008-06-22 Predictive models of road reliability for traffic sensor configuration and routing WO2009006059A2 (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US11/771,205 2007-06-29
US11/771,205 US7948400B2 (en) 2007-06-29 2007-06-29 Predictive models of road reliability for traffic sensor configuration and routing

Publications (2)

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WO2009006059A2 WO2009006059A2 (en) 2009-01-08
WO2009006059A3 true WO2009006059A3 (en) 2009-02-19

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PCT/US2008/067820 WO2009006059A2 (en) 2007-06-29 2008-06-22 Predictive models of road reliability for traffic sensor configuration and routing

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US (1) US7948400B2 (en)
WO (1) WO2009006059A2 (en)

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Publication number Publication date
US7948400B2 (en) 2011-05-24
WO2009006059A2 (en) 2009-01-08
US20090002195A1 (en) 2009-01-01

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