Technologies for Truck Classification and Methodologies for Estimating Truck Vehicle Miles Traveled

Author:

Benekohal Rahim F.1,Girianna Montty1

Affiliation:

1. Newmark Civil Engineering Laboratory, Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 North Mathews Avenue, Urbana, IL 61801

Abstract

Results are presented of a national survey of all state departments of transportation (DOTs), including Puerto Rico, about technologies used for truck classification and methodologies used for estimating truck vehicle miles traveled (VMT). More than two-thirds of state DOTs returned the survey. Procedures were found to classify trucks, to adjust truck data from short-term counts, and to calculate truck VMT. To classify trucks, most state DOTs followed FHWA’s 13 categories. The products from two manufacturers, Peek Traffic and Diamond Traffic Products, with a variety of sensors, dominated the classification devices used by state DOTs. The sensor used most for short-term classification counts was the pneumatic tube. Duration and number of truck-classification counts (machine or manual) varied by state DOT. With machine classifiers, state DOTs collected short-term and continuous truck data for a variety of state highway coverage. Truck data were collected by using machine classifiers unless certain conditions, such as congested highways, demanded manual collection. To adjust truck data from short-term classification counts, most state DOTs developed their adjustment factors from continuous volume counts (not truck counts) and used them to adjust truck volumes. Some state DOTs used different adjustment factors for trucks and cars. For all state DOTs, the general practice of truck VMT estimation was based on traffic counts. When truck data were available, state DOTs directly calculated truck VMT by multiplying truck average daily traffic and the length of a roadway section; when the data were not available, truck VMT was indirectly calculated as a fraction (percentage) of total VMT. For the state highway systems, state DOTs generally relied on the first (direct) method, since the resources were normally available and the standards for conducting traffic counts were also available. However, some states lacked the necessary resources to adequately sample average daily traffic on the local road systems. As a result, many state DOTs used the indirect method to calculate truck VMT.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Reference2 articles.

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. GPS data-based mobility mode inference model using long-term recurrent convolutional networks;Transportation Research Part C: Emerging Technologies;2022-02

2. Vehicle classification from low-frequency GPS data with recurrent neural networks;Transportation Research Part C: Emerging Technologies;2018-06

3. Integration of Weigh-in-Motion (WIM) and inductive signature data for truck body classification;Transportation Research Part C: Emerging Technologies;2016-07

4. Vehicle classification using GPS data;Transportation Research Part C: Emerging Technologies;2013-12

5. Methodology to Estimate the Distance Traveled by Trucks on Rural Highway Systems;Journal of Transportation Engineering;2013-04

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