System Monitoring of Auto Traffic: Queue Detection and Congestion Impact Assessment

Pesti, Geza; Storey, Beverly; Brydia, Robert

doi:10.5038/CUTR-NICR-RR-2022-1-3

i

System Monitoring of Auto Traffic: Queue Detection and Congestion Impact Assessment

2022-04-21
By Pesti, Geza ; Storey, Beverly ; Brydia, Robert

File Language:

English

Details

Creators:

Pesti, Geza ; Storey, Beverly ; Brydia, Robert
Corporate Creators:

Texas A&M Transportation Institute ; University of South Florida. Center for Urban Transportation Research
Corporate Contributors:

University of South Florida. National Institute for Congestion Reduction ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:
Publication/ Report Number:

69 69A3551947136 A355
DOI:

https://doi.org/10.5038/CUTR-NICR-RR-2022-1-3
Resource Type:

Tech Report
Geographical Coverage:

Texas;United States
Corporate Publisher:

University of South Florida. National Institute for Congestion Reduction
Description:

The main objectives of this study were to identify available data sets and explore methodologies for improving the detection of bottlenecks, related congestion, and queue formation, as well as formulate methodologies to determine the extent and rate of spread queues, identify their impact area, and look at potential mitigation strategies. Methodologies are provided that evaluate (a) impacts of single construction projects, (b) combined daily impacts of construction projects and incidents on selected segments of the corridor, and (c) a process to find the most appropriate schedule that minimizes the negative impact of construction, utility work or special events that require partial or full closure of a roadway. Finally, this study describes an approach to queue detection using a combination of data available from two different sources (traffic sensors and third-party data providers) and finding the best combination of the two data sources for queue detection
Format:

PDF
Funding:

69A3551947136 A3551947136 69A3551947136, 79070-00-SUB B and 79070-00 SUB C
Download URL:

https://rosap.ntl.bts.gov/view/dot/63565/dot_63565_DS1.pdf
File Type:

[PDF - 3.62 MB]
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha-512:cd0f85bec38ab41ee38b1b130a368ac33060cab90b70ff6cdc3e9f799d5f46ff1e27e40b5f4a320c6163022f762d63f12d29d53a41490421a23f6cea201b3f43

File Language:

English

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