Traffic Surveillance Data Processing in Urban Freeway Corridors Using Kalman Filter Techniques

Houpt, Paul K.; Athans, Michael; Orlhac, Daniel G.; Mitchell, William J.; Massachusetts Institute of Technology

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Traffic Surveillance Data Processing in Urban Freeway Corridors Using Kalman Filter Techniques

1978-11-01
By Houpt, Paul K. ; Athans, Michael ; Orlhac, Daniel G. ; ...

[PDF-3.13 MB]

English

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Creators:

Houpt, Paul K. ; Athans, Michael ; Orlhac, Daniel G. ; Mitchell, William J.

Houpt, Paul K. ; Athans, Michael ; Orlhac, Daniel G. ; Mitchell, William J. Less -
Corporate Creators:

Massachusetts Institute of Technology
Corporate Contributors:

John A. Volpe National Transportation Systems Center (U.S.) ; United States. Dept. of Transportation. Research and Special Programs Administration

John A. Volpe National Transportation Systems Center (U.S.) ; United States. Dept. of Transportation. Research and Special Programs Administration Less -
Subject/TRT Terms:

[+]

Algorithms Estimates Freeways Highway Traffic Highway Traffic Control Human Information Processing Methodology Partial Differential Equations Performance Real Time Control Simulation Stochastic Processes Surveillance Traffic Control Traffic Engineering Traffic Flow Traffic Surveillance Urban Areas
Publication/ Report Number:

DOT-TSC-RSPA-78-18
Resource Type:

Tech Report
Geographical Coverage:

United States
Corporate Publisher:

United States. Dept. of Transportation. Research and Special Programs Administration
NTL Classification:

NTL-PLANNING AND POLICY-PLANNING AND POLICY;NTL-PLANNING AND POLICY-Travel Demand;NTL-PLANNING AND POLICY-Management Systems;NTL-PLANNING AND POLICY-Access Management;
Abstract:

Real-time surveillance of traffic conditions on urban freeway corridors using spatially discrete presence detectors is addressed. Using a finite-dimensional (macroscopic) fluid-analog model for freeway vehicular traffic flow, an extended Kalman filter is proposed as a data-processing algorithm to obtain minimum variance estimates of spatial mean speed and density. It is shown that certain model parameters associated with available roadway capacity can be estimated on-line with a variation of the extended Kalman filter, and furthermore, that the time signatures associated with these estimates provide quantitative information concerning the presence of anomalous (i.e., incident) traffic events. Performance of the surveillance algorithm is evaluated using a detailed, multi-lane microscopic vehicle simulation which retains a stochastic mix of driver-vehicle types and passing. Complexity problems associated with the computer implementation of the extended Kalman filter are addressed, and techniques for decentralized realization are proposed.
Format:

PDF
Collection(s):

Volpe Center
Main Document Checksum:

[+]

urn:sha256:50d83d45fe7b09c228e5fafb8a23a68a34c632a9265e06c0dea09ecc0e26e37a
Download URL:

https://rosap.ntl.bts.gov/view/dot/11304/dot_11304_DS1.pdf
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Traffic Surveillance Data Processing in Urban Freeway Corridors Using Kalman Filter Techniques

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