Using Mobile Device Samples to Estimate Traffic Volumes

Turner, Shawn; Koeneman, Pete; Texas A&M Transportation Institute

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Using Mobile Device Samples to Estimate Traffic Volumes

2017-12-01
By Turner, Shawn ; Koeneman, Pete

[PDF-2.39 MB]

English

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Creators:

Turner, Shawn ; Koeneman, Pete

Turner, Shawn ; Koeneman, Pete Less -
Corporate Creators:

Texas A&M Transportation Institute
Corporate Contributors:

Minnesota. Dept. of Transportation. Research Services & Library
Subject/TRT Terms:

[+]

Annual Average Daily Traffic Global Positioning System Mobile Communication Systems Mobile Devices Street Lighting Traffic Counts Traffic Estimation Traffic Forecasting Traffic Measurement Traffic Volume
Publication/ Report Number:

MN/RC 2017-49
Resource Type:

Tech Report
Geographical Coverage:

Minnesota;United States
Corporate Publisher:

Minnesota. Dept. of Transportation. Research Services & Library
Abstract:

In this project, TTI worked with StreetLight Data to evaluate a beta version of its traffic volume estimates derived from global positioning system (GPS)-based mobile devices. TTI evaluated the accuracy of average annual daily traffic (AADT) volume

estimates as well as average annual hourly volume (AAHV) estimates from Streetlight Data using actual volume counts from MnDOT traffic monitoring sites. Traffic volume estimation from mobile devices has potential, but analytic enhancements are needed to improve accuracy and granularity of estimated traffic volumes. Some of the AADT volume estimates from StreetLight Data were within acceptable error ranges (10% to 20% absolute percent error), but other estimates were significantly outside this acceptable error range

(greater than 100% absolute percent error). Lower volume roadways had the highest errors, presumably due to lower mobile device sample sizes. The AAHV evaluation results at 12 non-public MnDOT sites reinforce the need for analytic improvements, as these results showed higher error (49% mean absolute percent error) than the results at the 69 public

permanent sites (39% mean absolute percent error).
Format:

PDF
Funding:

(c) 99007 (wo) 5
Collection(s):

US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:1ffeb3346088e47060a8aaf324ebb07c9a32ad76f170c8702ca2cd8ae755b0f7
Download URL:

https://rosap.ntl.bts.gov/view/dot/34555/dot_34555_DS1.pdf
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Using Mobile Device Samples to Estimate Traffic Volumes

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