Abstract
This paper presents a novel and practical methodology for freight tonnage estimation by leveraging two complementary datasets: Telemetric Traffic Monitoring Sites (TTMS) data and Weigh-In-Motion (WIM) systems. To estimate freight tonnage statewide and potentially nationwide with limited truck weigh-in-motion stations, we have proposed a multi-objective location-allocation model that associated TTMSs with WIM stations based on similar attributes. Additionally, we have developed a fuzzy k-prototype clustering-based non-dominated sorting genetic algorithm -simulated annealing algorithm (FKC-NSGASA) to solve the multi-objective location-allocation problem, enabling accurate estimation of truck volumes. To address the over-counting problem, we introduced a truck volume elimination method. Finally, we have aggregated annual truck tonnage using the truck volume data and the average tonnage of WIM stations. The proposed methodologies are validated using WIM data from 2012 and 2017 in Florida. The results demonstrate that our approach achieves higher estimation accuracy, showcasing its potential for accurately estimating statewide freight tonnage. Furthermore, the developed estimation framework and algorithm offer an effective and computationally efficient method for statewide freight traffic evaluation.
| Original language | English |
|---|---|
| Article number | 10741214 |
| Pages (from-to) | 19581-19591 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Intelligent Transportation Systems |
| Volume | 25 |
| Issue number | 12 |
| Early online date | 1 Nov 2024 |
| DOIs | |
| Publication status | Published - Dec 2024 |
Funding
This work was supported in part by the Florida Department of Transportation under Grant BDV27-977-15, in part by the Freight Mobility Research Institute, in part by Shanghai Municipal Human Resources and Social Security Bureau under Grant 23PJC072, in part by Humanities and Social Sciences of the Ministry of Education under Grant 23YJCZH128, and in part by the Key Laboratory of Transport Industry of Comprehensive Transportation Theory (Nanjing Modern Multimodal Transportation Laboratory) under Grant MTF2023002. The Associate Editor for this article was W.-H. Lin. Received 8 June 2023; revised 29 October 2023 and 22 April 2024; accepted 15 June 2024. This work was supported in part by the Florida Department of Transportation under Grant BDV27-977-15, in part by the Freight Mobility Research Institute, in part by Shanghai Municipal Human Resources and Social Security Bureau under Grant 23PJC072, in part by Humanities and Social Sciences of the Ministry of Education under Grant 23YJCZH128, and in part by the Key Laboratory of Transport Industry of Comprehensive Transportation Theory (Nanjing Modern Multimodal Transportation Laboratory) under Grant MTF2023002. The Associate Editor for this article was W.-H. Lin. (Corresponding author: Dan Liu.) Dan Liu is with the Department of Management, College of Business and Public Management, Kean University, Union, NJ 07083 USA (e-mail: [email protected]).
Keywords
- multi-objective location allocation method
- telemetered traffic monitoring site
- truck tonnage
- urban freight
- Weigh-in-motion