Evaluation of Truck Tonnage Estimation Methodologies

Kaisar, Evangelos I.; Liu, Dan; Ardalan, Taraneh; Florida Atlantic University. Freight Mobility Research Institute

Advanced Search

Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

Advanced Search
Custom Query

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Clear All

Query Builder

Query box

Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Evaluation of Truck Tonnage Estimation Methodologies

2019-12-01
By Kaisar, Evangelos I. ; Liu, Dan ; Ardalan, Taraneh

[PDF-4.91 MB]

English

Details You May Also Like

Details:

Creators:

Kaisar, Evangelos I. ; Liu, Dan ; Ardalan, Taraneh

Kaisar, Evangelos I. ; Liu, Dan ; Ardalan, Taraneh Less -
Corporate Creators:

Florida Atlantic University. Freight Mobility Research Institute
Corporate Contributors:

Florida Department of Transportation. Mobility Measures Program (MMP)
Subject/TRT Terms:

[+]

Algorithms Case Studies Cluster Analysis Estimating Evaluation Evaluation And Assessment Freight Tonnage Estimation Freight Traffic K-Nearest Neighbors Clustering Methodology Strategic Telemetered Traffic Monitoring Site (TTMS) Selection Tonnage Traffic Volume Trucks Weigh In Motion
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final report, January 2019-December 2019
Contracting Officer:

Zhong, Monica; Tabatabaee, Frank
Corporate Publisher:

Florida Atlantic University
Abstract:

Truck tonnage is an important mobility measure to evaluate transportation system performance, which can identify how much freight is moved. This study develops a methodology for truck tonnage estimation, which consists of three main parts: (i) Weigh in Motion (WIM) sites clustering, (ii) truck volume estimation based on Telemetric Traffic Monitoring sites (TTMS) data, and (iii) average truck tonnage calculation for WIM site. In this methodology, WIM sites were divided into different groups by applying the K-nearest neighbor algorithm, based on the truck tonnage distributions and average truck volumes. A clustering classification was then fitted to the TTMS, based on truck volumes and distances to the WIM sites. To avoid the double-counting issue, strategic TTMS were selected, considering the locations of the sites, the daily factor (commonly known as the D factor), and the truck factor (commonly known as the T factor). Afterwards, vehicle classes in WIM sites were categorized by a K-mean clustering method based on the vehicle loads for calculating the average truck tonnage. Furthermore, the empty vehicle weight for different vehicle classes was estimated, applying Gaussian distribution of gross tonnage. At last, a weighted mean method was applied to calculate the average truck tonnage. The aforementioned methodology was tested in a case study of truck tonnage estimation in Florida using WIM data in 2012 and 2017, and compared with the method using the 2012 data released by the Freight Analysis Framework (FAF). The proposed model might shed light on the statewide performance evaluation of freight mobility.
Format:

PDF
Funding:

BDV27-977-15
Collection(s):

University Transportation Centers US Transportation Collection
Main Document Checksum:

[+]

urn:sha256:c09ded55f92f7c1db86bf619db37a7fa050a1f2caeaec69f5e2ce701e290a248
Download URL:

https://rosap.ntl.bts.gov/view/dot/49954/dot_49954_DS1.pdf
File Type:

No Additional Files

More +

Evaluation of Truck Tonnage Estimation Methodologies

Details:

Supporting Files

You May Also Like