Optimizing network locations of weigh-in-motion stations: A multi-objective approach for enhancing infrastructure management
In the realm of transportation infrastructure, Weigh-in-Motion (WIM) stations are crucial for monitoring impact of overweight trucks and maintaining infrastructure assets such as roadway pavements and bridges. However, current approaches to WIM location problem (WIMLP) on a network of highways and b...
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Elsevier
2025-01-01
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| Series: | Transportation Research Interdisciplinary Perspectives |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590198224002884 |
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| author | Chan Yang Tu Lan Patrick Lou Hani Nassif Kaan Ozbay Chaekuk Na |
| author_facet | Chan Yang Tu Lan Patrick Lou Hani Nassif Kaan Ozbay Chaekuk Na |
| author_sort | Chan Yang |
| collection | DOAJ |
| description | In the realm of transportation infrastructure, Weigh-in-Motion (WIM) stations are crucial for monitoring impact of overweight trucks and maintaining infrastructure assets such as roadway pavements and bridges. However, current approaches to WIM location problem (WIMLP) on a network of highways and bridges are often region-specific and resource-intensive and lack a multi-objective framework. This study addresses these gaps by proposing a versatile and cost-effective network-based site selection strategy, adaptable to various transportation agency needs. Utilizing an extensive literature review, the framework centers around a comprehensive site-selection framework based on the diverse purposes of WIM data collection. The proposed framework integrates truck traffic composition, infrastructure condition, enforcement needs, and geographical considerations. This approach strategically identifies the optimal sites for WIM installation, maximizing data utility while minimizing resource expenditure.The proposed framework for WIMLP is showcased in New York City, addressing the city’s challenge of managing truck load impacts on its extensive bridge network. Based on the City’s allocation of resources for only ten sites, the research team strategically identified their respective optimal WIM locations across the city’s roadway network and highway bridges. This selection facilitates the assessment of truck load effects, especially from overweight vehicles, on bridge conditions. This approach not only aids in long-term infrastructure monitoring aligned with NYCDOT’s goals but also supports future overweight enforcement efforts. Additionally, the study introduces an analytical framework to enhance the utilization of WIM data in analyzing truck load impacts. |
| format | Article |
| id | doaj-art-3ebf9bfc9efb41ed881c766bb2aba9f5 |
| institution | Kabale University |
| issn | 2590-1982 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Transportation Research Interdisciplinary Perspectives |
| spelling | doaj-art-3ebf9bfc9efb41ed881c766bb2aba9f52025-02-09T05:01:13ZengElsevierTransportation Research Interdisciplinary Perspectives2590-19822025-01-0129101302Optimizing network locations of weigh-in-motion stations: A multi-objective approach for enhancing infrastructure managementChan Yang0Tu Lan1Patrick Lou2Hani Nassif3Kaan Ozbay4Chaekuk Na5HNTB Corporation, Empire State Building, 57th Floor, 350 5th Ave, New York, NY 10118, United StatesDepartment of Civil and Urban Engineering, Tandon School of Engineering, New York University, 6 MetroTech Center, 4th Floor, Brooklyn, NY, 11201, United States; Corresponding author.Rutgers Infrastructure Monitoring and Evaluation (RIME) Group, Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, 500 Bartholomew Road, Piscataway, NJ 08854, United StatesRutgers Infrastructure Monitoring and Evaluation (RIME) Group, Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, 500 Bartholomew Road, Piscataway, NJ 08854, United StatesDepartment of Civil and Urban Engineering, Tandon School of Engineering, New York University, 6 MetroTech Center, 4th Floor, Brooklyn, NY, 11201, United StatesRutgers Infrastructure Monitoring and Evaluation (RIME) Group, Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, 500 Bartholomew Road, Piscataway, NJ 08854, United StatesIn the realm of transportation infrastructure, Weigh-in-Motion (WIM) stations are crucial for monitoring impact of overweight trucks and maintaining infrastructure assets such as roadway pavements and bridges. However, current approaches to WIM location problem (WIMLP) on a network of highways and bridges are often region-specific and resource-intensive and lack a multi-objective framework. This study addresses these gaps by proposing a versatile and cost-effective network-based site selection strategy, adaptable to various transportation agency needs. Utilizing an extensive literature review, the framework centers around a comprehensive site-selection framework based on the diverse purposes of WIM data collection. The proposed framework integrates truck traffic composition, infrastructure condition, enforcement needs, and geographical considerations. This approach strategically identifies the optimal sites for WIM installation, maximizing data utility while minimizing resource expenditure.The proposed framework for WIMLP is showcased in New York City, addressing the city’s challenge of managing truck load impacts on its extensive bridge network. Based on the City’s allocation of resources for only ten sites, the research team strategically identified their respective optimal WIM locations across the city’s roadway network and highway bridges. This selection facilitates the assessment of truck load effects, especially from overweight vehicles, on bridge conditions. This approach not only aids in long-term infrastructure monitoring aligned with NYCDOT’s goals but also supports future overweight enforcement efforts. Additionally, the study introduces an analytical framework to enhance the utilization of WIM data in analyzing truck load impacts.http://www.sciencedirect.com/science/article/pii/S2590198224002884Overweight Truck ImpactWeigh-in-motion (WIM)Multi-objective OptimizationAsset Management |
| spellingShingle | Chan Yang Tu Lan Patrick Lou Hani Nassif Kaan Ozbay Chaekuk Na Optimizing network locations of weigh-in-motion stations: A multi-objective approach for enhancing infrastructure management Transportation Research Interdisciplinary Perspectives Overweight Truck Impact Weigh-in-motion (WIM) Multi-objective Optimization Asset Management |
| title | Optimizing network locations of weigh-in-motion stations: A multi-objective approach for enhancing infrastructure management |
| title_full | Optimizing network locations of weigh-in-motion stations: A multi-objective approach for enhancing infrastructure management |
| title_fullStr | Optimizing network locations of weigh-in-motion stations: A multi-objective approach for enhancing infrastructure management |
| title_full_unstemmed | Optimizing network locations of weigh-in-motion stations: A multi-objective approach for enhancing infrastructure management |
| title_short | Optimizing network locations of weigh-in-motion stations: A multi-objective approach for enhancing infrastructure management |
| title_sort | optimizing network locations of weigh in motion stations a multi objective approach for enhancing infrastructure management |
| topic | Overweight Truck Impact Weigh-in-motion (WIM) Multi-objective Optimization Asset Management |
| url | http://www.sciencedirect.com/science/article/pii/S2590198224002884 |
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