Zoning, Sampling and Trip Distribution Analysis Data-Driven Transport Planning in Madison Metropolitan Area (case study)

Arman Hajiha¹ Hamid Zekavatmand²

1) Researcher, Politecnico di Torino
2) Msc. Civil Engineering Politecnico di Torino

IOI Code : XKFA-AZEGKA
Publication : Second International Conference on applied researches in civil engineering, architecture and urban planning (icarcau.com/2nd)
Abstract :
    Effective transport planning is crucial for managing the complex mobility demands of urban areas, particularly in large metropolitan regions like Madison. As population growth, economic development, and urbanization continue to reshape cities, data-driven approaches have become essential in designing and optimizing transportation systems. This paper focuses on the use of sampling techniques and trip distribution analysis as key components of data-driven transport planning, using the Madison Metropolitan Area as a case study. Sampling provides a representative understanding of travel behavior by collecting data from a subset of the population, offering insights into commuting patterns, travel preferences, and mode choices. Coupled with this, trip distribution analysis—which examines the spatial flow of trips between different zones—helps to uncover critical travel dynamics such as home-based work (HBW), home-based other (HBO), and non-home-based (NHB) trips. These analyses enable transport planners to identify patterns in travel demand and to forecast future mobility needs. In this study, we employ household data from the National Household Travel Survey (NHTS) and demographic insights from the American Community Survey (ACS) to perform a detailed examination of trip distribution across the Madison Metropolitan Area. By integrating population and land-use data with transportation modeling, this case study aims to highlight the importance of data-driven planning in improving the efficiency of transportation networks, reducing congestion, and promoting sustainable mobility solutions. Through this analysis, we seek to offer evidence-based recommendations for future infrastructure investments and transportation policy reforms in the region

Keywords : transport planning sampling survey trip distribution analysis nhb hbo hbw trips analysis