Evaluating the Accuracy of Probe-Based Truck Volumes using Continuous and Short-Duration Traffic Counts

Author:

Zrobek Cassidy1ORCID,Grande Giuseppe1ORCID,Regehr Jonathan1ORCID,Mehran Babak1ORCID

Affiliation:

1. Department of Civil Engineering, University of Manitoba, Winnipeg, Manitoba, Canada

Abstract

The widespread nature of cell phones and connected vehicle navigation systems has led to the development of commercially available probe-based traffic data products. This study assesses the accuracy of annual average daily total traffic, truck traffic, medium-duty truck traffic, and heavy-duty truck traffic volumes obtained using probe-based traffic activity indices from a North American company called StreetLight Data (StL). The probe-based estimates were compared with 2019, 2020, and 2021 volumes at eleven continuous count sites and 2019 volumes at twenty-nine short-duration count (SDC) sites in the Winnipeg Metropolitan Region. The results showed reasonable agreement between the ground truth and probe-based total traffic estimates with mean absolute percent errors (MAPEs) ranging from 8.8% to 22.1% across the study years. The medium-duty truck estimates had larger errors than total traffic with MAPEs of 29.9% to 37.5%. Despite having higher volumes than medium-duty trucks, heavy-duty trucks had the smallest probe data sample and largest errors with MAPEs of 56.6% to 96.4%. Benefiting from its larger sample size, the StL medium-duty truck index was found to be a better predictor of heavy-duty truck traffic than the heavy-duty truck index. Further, the total truck volumes estimated using only the medium-duty index were more accurate than those taken as the sum of the medium and heavy-duty truck volumes obtained using their respective indices. Finally, the percent differences for the 2019 annual average daily total traffic and truck traffic estimates at the SDC sites were comparable when only the medium-duty index was used for truck volume estimation.

Publisher

SAGE Publications

Reference21 articles.

1. Zrobek C. Options for Enhancing Network-Wide Annual Average Daily Truck Volume Estimates. Master’s thesis. University of Manitoba, Winnipeg, Canada, 2023.

2. Methodology to Estimate the Distance Traveled by Trucks on Rural Highway Systems

3. Exploring Vehicle Probe Data as a Resource to Enhance Network-Wide Traffic Volume Estimates

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