Comparative Assessment of Geospatial and Statistical Methods to Estimate Local Road Annual Average Daily Traffic-Reference-Cited by-同舟云学术

Comparative Assessment of Geospatial and Statistical Methods to Estimate Local Road Annual Average Daily Traffic

Published:2021-07 Issue:7 Volume:147 Page:04021035
ISSN:2473-2907
Container-title:Journal of Transportation Engineering, Part A: Systems
language:en
Short-container-title:J. Transp. Eng., Part A: Systems

Author:

Mathew Sonu¹,Pulugurtha Srinivas S.²^ORCID

Affiliation:

1. Postdoctoral Researcher, Infrastructure, Design, Environment, and Sustainability Center, Univ. of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223-0001.

2. Professor, Dept. of Civil and Environmental Engineering, Univ. of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223-0001; Director, Infrastructure, Design, Environment, and Sustainability Center, Univ. of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28223-0001 (corresponding author). ORCID: .

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/JTEPBS.0000542

Reference45 articles.

1. Estimating traffic volume on Wyoming low volume roads using linear and logistic regression methods;Apronti D.;J. Traff. Transp. Eng.,2016

2. Comparison of Linear and Nonlinear Kriging Methods for Characterization and Interpolation of Soil Data

3. Multivariate interpolation to incorporate thematic surface data using inverse distance weighting (IDW)

4. Geographically Weighted Regression

5. AADT prediction using support vector regression with data-dependent parameters;Castro N.;Expert Syst. Appl.,2009

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