Optimizing network locations of weigh-in-motion stations: A multi-objective approach for enhancing infrastructure management

• Propose a versatile, cost-effective WIM site selection strategy adaptable to agency needs. • The framework integrates multiple factors to identify optimal sites for WIM installation. • Maximize the data collection efficiency/resource allocation while minimizing expenditure. • Showcase the framework in NYC to manage overweight truck impacts on infrastructures. • Enhance WIM data utilization for long-term monitoring and enforcement efforts. 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.