Wyoming Low-Volume Roads Traffic Volume Estimation

Apronti, Dick T.; Herpner, Jaime J.; Ksaibati, Khaled; University of Wyoming. Dept. of Civil and Architectural Engineering

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Wyoming Low-Volume Roads Traffic Volume Estimation

2015-10-01
By Apronti, Dick T. ; Herpner, Jaime J. ; Ksaibati, Khaled

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English

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Details:

Creators:

Apronti, Dick T. ; Herpner, Jaime J. ; Ksaibati, Khaled

Apronti, Dick T. ; Herpner, Jaime J. ; Ksaibati, Khaled Less -
Corporate Creators:

University of Wyoming. Dept. of Civil and Architectural Engineering
Corporate Contributors:

Wyoming. Dept. of Transportation ; United States. Federal Highway Administration

Wyoming. Dept. of Transportation ; United States. Federal Highway Administration Less -
Subject/TRT Terms:

[+]

Accuracy Calibration Counties Estimating Low Volume Roads Recommendations Regression Analysis Regression Methods Traffic Volume Traffic Volume Estimation Travel Demand Travel Demand Model Validation
Publication/ Report Number:

WY 16/04F;FHWA-WY-16/04F
Resource Type:

Tech Report
Geographical Coverage:

United States ; Wyoming

United States ; Wyoming Less -
TRIS Online Accession Number:

01599322
Edition:

Final Report
Corporate Publisher:

Wyoming. Dept. of Transportation
Abstract:

Low-volume roads are excluded from regular traffic counts except on a need to know basis. But needs for traffic volume data on low-volume roads in road infrastructure management, safety, and air quality analysis have necessitated regular traffic volume estimates. This study developed traffic volume estimation models for low-volume roads in Wyoming. A review of existing estimation models was carried out. Two main model types were identified - regression models and Travel Demand Models (TDMs). The study developed the two model types and recommended the best model for implementation. Two regression models were developed, a linear and a logistic regression model. Each of the regression models was developed using data from 13 randomly selected counties and nine counties were used in model validation. The linear regression model had an R2 of 64 percent and was verified to be a good predictor of traffic volumes across Wyoming. The logistic regression model validation indicated a prediction accuracy ranging from 78 to 89 percent. The TDM was developed using standard factors and trip rates in the NCHRP Report 365. The TDM was implemented for four south eastern counties in Wyoming. The model was then validated and calibrated by comparing actual traffic volumes to those generated by the model. The calibrated model had a Percentage Root Mean Square Error and an R 2 values of 50 and 74 percent respectively. The report compared the three models with respect to cost-effectiveness, ease of use, and accuracy and recommended the TDM for implementation. The regression models were recommended for applications requiring quick traffic volume estimations and for which lower levels of accuracy are acceptable.
Format:

PDF
Funding:

RS06213
Collection(s):

US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:eef66359f1c84c06abfe68d3585e33c708eccf90a9fee5160c44c8932f3f6a66
Download URL:

https://rosap.ntl.bts.gov/view/dot/34366/dot_34366_DS1.pdf
File Type:

Data Management Plan

pdf

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