Assessment of pavement degradation through statistical analysis model A case study of the Department of Transportation (DOT) of Iowa, USA

Abstract

Transportation network, especially highways, is considered a national or international asset, and by proper maintenance system, public and private organizations can prioritize the budgeting of repair and reconstruction. The problem is to have a reliable and practical model creating a solid understanding of the pavement degradation condition by inexpensive measurable parameters for municipalities. This study focuses on the road pavement condition, particularly the statistical evaluation of the processes of degradation involved in various road sections. Quantitative statistical analysis of a sample taken from the Iowa Department of Transportation (DOT) in the United States provides a better understanding of the needs in pavement maintenance processes. In addition, it can identify the critical factors of pavement maintenance. Through a case study, it is shown that organizations can develop a solid based statistical decision-making model using basic and low-priced parameters. The model has two approaches, with and without pavement type (used by creating several dummy variables to include each pavement type as independent variables). This study will positively enhance the pavement degradation prediction through a statistical analysis model and a case study of the Department of Transportation (DOT) of Iowa, USA. These details include explanatory models, bivariate correlation, principal component analysis, hierarchical and non-hierarchical clustering, creating dummy variables, and developing multivariate regression models.

Climate Adaptation Measures for Enhancing Urban Resilience

“…Netobra.com aids the integration and analysis of the 50 climate adaptation measures identified in our study, reflecting prior research emphasizing the importance of comprehensive and multipronged approaches to climate adaptation. For instance, in the realm of physical infrastructure and climate adaptation measures, Netobra.com can provide spatial analysis and visualization of data related to measures such as sea walls, flood barriers, and heat-resistant pavement materials [174]. Similarly, in ecosystem restoration and protection efforts, Netobra.com can assist in mapping reforestation areas, wetland restoration sites, and wildlife corridors.…”

Urban Resilience Index for Critical Infrastructure: A Scenario-Based Approach to Disaster Risk Reduction in Road Networks

“…Regarding the factors influencing asset performance, we might consider (i) Design and Material Selection-initial design specifications, materials choices, and adherence to construction standards play a fundamental role in long-term asset performance [48,49]; (ii) Environmental Conditions-extreme temperatures, moisture levels, freeze-thaw cycles, soil properties, and seismic activity impose constant stresses on asset materials and structures [50]; (iii) Traffic Loading-intensity, frequency, and weight of vehicles generate cumulative wear and tear on pavements, bridges, and support structures; (iv) Maintenance Practices-regular preventative maintenance, rapid repair of emerging issues, and timely resurfacing extend asset lifespan and minimize major disruptions [51,52]; and (v) Technological Advancements-innovative materials (like recycled or self-healing asphalt), structural health monitoring, and asset management software can enhance performance and predict failures [53,54].…”

“…On the other hand, the Proactive Resilience Planning scenario (Scenario 2) demonstrates the lowest loss at −0.108, suggesting that pre-emptive measures can effectively mitigate the impact of floods on the road network. The Early Warning Systems Implementation scenario (Scenario 3) falls in the middle, with a loss of −0.144, highlighting the potential of early warning systems to reduce, but not completely eliminate, performance degradation [52].…”