Citation

Kaushik K, Wood E, Gonder J. Transp. Res. Rec. 2018; 2672(43): 1-11.

Affiliation

1Department of Civil and Environmental Engineering, University of Maryland, College Park, MD 2Transportation & Hydrogen Systems Center, National Renewable Energy Laboratory, Golden, CO, USA Corresponding Author: Address correspondence to Kartik Kaushik: kartikk@umd.edu

Copyright

(Copyright © 2018, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/0361198118758391

PMID

unavailable

Abstract

The advent of mobile devices with embedded global positioning systems has allowed commercial providers of real-time traffic data to develop highly accurate estimates of network-level vehicle speeds. Traffic speed data have far outpaced the availability and accuracy of real-time traffic volume information. Limited to a relatively small number of permanent and temporary traffic counters in any city, traffic volumes typically only cover a handful of roadways, with inconsistent temporal resolution. This work addressed this data gap by coupling a commercial data set of typical traffic speeds (by roadway and time of week) from TomTom to the U.S. Federal Highway Administration's Highway Performance Monitoring System database of annual average daily traffic (AADT) counts by roadway. This work is technically novel in its solution for establishing a national crosswalk between independent network geometries using spatial conflation and big data techniques. The resulting product is a national data set providing traffic speed and volume estimates under typical conditions for all U.S. roadways with AADT values.

Language: en