Fusing Loop and GPS Probe Measurements to Estimate Freeway Density

In an age of ever-increasing penetration of Global Positioning System-enabled mobile devices, the potential of real-time "probe" location information for estimating the state of transportation networks is receiving increasing attention. Much work has been done on using probe data to estima...

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Veröffentlicht in:IEEE transactions on intelligent transportation systems Jg. 17; H. 12; S. 3577 - 3590
Hauptverfasser: Wright, Matthew, Horowitz, Roberto
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.12.2016
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Density measurement
Detectors
Estimation
Filtering algorithms
Global Positioning System (GPS)
Global positioning systems
GPS
hidden Markov model
Highways
Mathematical model
Monte Carlo simulation
particle filters
Probes
Real time
road transportation
Roads
state estimation
Traffic control
Traffic information
Traffic volume
Travel time
Vehicles
Los Angeles California
United States > US
ISSN:1524-9050, 1558-0016
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Zusammenfassung:In an age of ever-increasing penetration of Global Positioning System-enabled mobile devices, the potential of real-time "probe" location information for estimating the state of transportation networks is receiving increasing attention. Much work has been done on using probe data to estimate the current speed of vehicle traffic (or, equivalently, trip travel time). While travel times are useful to individual drivers, the state variable for a large class of traffic models and control algorithms is vehicle density. Our goal is to use probe data to supplement traditional fixed-location loop detector data for density estimation. To this end, we derive a method based on Rao-Blackwellized particle filters, a sequential Monte Carlo scheme. We present a simulation where we obtain a 30% reduction in density mean absolute percentage error from fusing loop and probe data versus using loop data alone. We also present results using real data from a 19-mi freeway section in Los Angeles, CA, where we obtain a 31% reduction. In addition, our method's estimate when using only the real-world probe data and no loop data outperformed the estimate produced when only loop data were used (i.e., an 18% reduction). These results demonstrate that probe data can be used for traffic density estimation.
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ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2016.2565438