Automated Congestion Prediction With Smart Phones

Gokhale, Swapna S.; Lownes, Nicholas; New England University Transportation Center; University of Connecticut. Connecticut Transportation Institute; Massachusetts Institute of Technology

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Automated Congestion Prediction With Smart Phones

2015-06-29
By Gokhale, Swapna S. ; Lownes, Nicholas

[PDF-172.81 KB]

English

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Details:

Creators:

Gokhale, Swapna S. ; Lownes, Nicholas

Gokhale, Swapna S. ; Lownes, Nicholas Less -
Corporate Creators:

New England University Transportation Center ; University of Connecticut. Connecticut Transportation Institute ; Massachusetts Institute of Technology

New England University Transportation Center ; University of Connecticut. Connecticut Transportation Institute ; Massachusetts Institute of Technology Less -
Corporate Contributors:

United States. Dept. of Transportation. Research and Innovative Technology Administration
Subject/TRT Terms:

[+]

Cell Phones Data And Information Technology Data Collection Feasibility Analysis Highways I72: Traffic And Transport Planning I73: Traffic Control Mobile Applications Operations And Traffic Management Planning And Forecasting Smartphones Traffic Congestion Traffic Flow Traffic Forecasting
Resource Type:

Brief
Geographical Coverage:

United States ; Connecticut

United States ; Connecticut Less -
TRIS Online Accession Number:

01590494
Edition:

Final Report
Corporate Publisher:

New England University Transportation Center
Abstract:

Accurate collection of traffic data is essential for tactical efficient highway operations and strategic planning. Currently, the collection of such traffic data relies on physical sensors, which gather limited measurements of vehicle speeds and times as observed from fixed locations. These sensors cannot systematically acquire data on the mobility dynamics of individual vehicles and collective interactions among them, preventing the formulation of detailed models of vehicle flow within a transportation network. Finally, deployment and maintenance of physical sensors is expensive and time consuming.
Format:

PDF
Funding:

DTRT12-G-UTC01 ; UCNR24-29

DTRT12-G-UTC01 ; UCNR24-29 Less -
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:0213f5d614994d6f3bba55a387c038e6c52ca3a181981623192f791c95a30db0
Download URL:

https://rosap.ntl.bts.gov/view/dot/39683/dot_39683_DS1.pdf
File Type:

No Additional Files

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Automated Congestion Prediction With Smart Phones

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