Use of Probe Data for Arterial Roadway Travel Time Estimation and Freeway Medium-Term Travel Time Prediction

Rakha, Hesham A.; Chen, Hao; Haghani, Ali; Zhang, Xuechi; Hamedi, Masoud; Virginia Polytechnic Institute and State University; Virginia Tech Transportation Institute; University of Maryland (College Park, Md.). Dept. of Civil and Environmental Engineering

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Use of Probe Data for Arterial Roadway Travel Time Estimation and Freeway Medium-Term Travel Time Prediction

2015-12-01
By Rakha, Hesham A. ; Chen, Hao ; Haghani, Ali ; ...

[PDF-2.32 MB]

English

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Details:

Creators:

Rakha, Hesham A. ; Chen, Hao ; Haghani, Ali ; Zhang, Xuechi ; Hamedi, Masoud

Rakha, Hesham A. ; Chen, Hao ; Haghani, Ali ; Zhang, Xuechi ; Hamedi, Masoud Less -
Corporate Creators:

Virginia Polytechnic Institute and State University ; Virginia Tech Transportation Institute ; University of Maryland (College Park, Md.). Dept. of Civil and Environmental Engineering

Virginia Polytechnic Institute and State University ; Virginia Tech Transportation Institute ; University of Maryland (College Park, Md.). Dept. of Civil and Environmental Engineering Less -
Corporate Contributors:

United States. Dept. of Transportation. Research and Innovative Technology Administration ; Mid-Atlantic Universities Transportation Center

United States. Dept. of Transportation. Research and Innovative Technology Administration ; Mid-Atlantic Universities Transportation Center Less -
Subject/TRT Terms:

[+]

Agent Based Modeling Algorithms Arterial Highways Arterial Travel Time Estimation Data Fusion Data Quality Dynamic Template Matching Estimating Floating Car Data Freeways Freeway Travel Time Prediction Learning (Artificial Intelligence) Mathematical Prediction Particle Filter Pattern Recognition Systems Probe Data Probe Vehicles Traffic Mitigation Travel Time
Publication/ Report Number:

MAUTC-2013-05
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final report, 7/1/2013 - 12/31/2014
Corporate Publisher:

Mid-Atlantic Universities Transportation Center
Abstract:

Urban traffic congestion is a problem that plagues many cities in the United States. One approach to alleviating this congestion is to provide drivers with better travel time information so that they can make better departure time and routing decisions. This research project focuses on two efforts: (1) validating the use of probe data to estimate arterial travel times and (2) validating and developing techniques to predict freeway travel times over a 2 to 4 hour window. With regards to the arterial travel time estimation the objective are two-fold. The first goal is a comprehensive validation of INRIX arterial data. In the validation the variability and reliability of arterial data in different corridors equipped with permanent and portable traffic sensors will be studied under different traffic conditions. The second goal is to develop a methodology for augmenting INRIX data with other data sources in order to improve the data quality. With regards to freeway travel time prediction the objectives are also two-fold. The first objective is to validate the INRIX travel time prediction algorithms along a number of corridors in the state of Virginia. The second objective is to enhance the prediction accuracy using various pattern recognition and machine learning techniques.
Format:

PDF
Alternate URL:

http://www.mautc.psu.edu/docs/MAUTC-2013-05.pdf
Funding:

DRTR12-G-UTC03
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:133b696a0726815cb0772ee2d718a817afe30203e7484a40330b00cf308fe7ef
Download URL:

https://rosap.ntl.bts.gov/view/dot/37106/dot_37106_DS1.pdf
File Type:

MAUTC-2013-05.pdf

pdf

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