Household Vehicle Holdings and Composition: A Multi-Dimensional Analysis of Body and Fuel Type Choices

Household vehicle ownership is the foundation of personal mobility for the vast majority of American families. The number of vehicles a household owns, and the specific types of vehicles in its fleet, determine how household members access employment, healthcare, education, and services, and directly generate the travel demand that shapes roadway utilization, network performance, and infrastructure needs. Accurately representing how households make vehicle fleet decisions is therefore essential for travel demand forecasting, long-range transportation planning, and the design of policies that support reliable and efficient system operations. While a substantial body of research has examined vehicle holdings, several important gaps remain. Most existing studies treat vehicle ownership as a single aggregate outcome, failing to jointly model the count of vehicles owned alongside the specific body-type and fuel-type composition of the household fleet. Even studies that examine fleet composition, often using the multiple discrete continuous extreme value (MDCEV) modeling approach (Bhat and Sen, 2006; Augustin et al., 2015; Chakraborty et al., 2023), identify only whether at least one vehicle of each type is present, rather than modeling the count of vehicles in each category. This is a meaningful limitation as many households own more than one vehicle of the same body type, and the specific count in each category has direct implications for household mobility capabilities and system-level demand generation. Further, existing studies do not allow for a direct effect of total fleet size on preferences for specific vehicle types. This is an important consideration because a household adding a second or third vehicle faces a fundamentally different choice context than one purchasing its first, and the body type preferred as a secondary addition to an existing fleet may differ substantially from a household's primary vehicle choice. Failing to account for these factors limits the accuracy of fleet-level demand forecasts and the ability of planners to anticipate how household vehicle availability translates into system demand. This project addresses these gaps by developing a multivariate ordered-response probit (MORP) framework that jointly models household fleet size alongside the count of vehicles in each of twelve body-type and fuel-type combinations, including six body types (SUV, sedan, pickup truck, compact, minivan, and sports car) and two fuel types (internal combustion engine and electric). A key methodological contribution is the normalization of the likelihood function to ensure that the sum of vehicle counts across all body-type and fuel-type categories equals the total fleet count, eliminating infeasible outcome combinations while enabling direct estimation of the effect of total fleet size on preferences for specific vehicle types. The analysis uses data from the 2024 Transportation Heartbeat of America (THA) survey, a large national sample of households, supplemented with built environment data from the EPA Smart Location Database. The modeling framework also incorporates three latent attitudinal constructs capturing the degree to which individuals prioritize sustainability in transportation decisions, the extent to which safety considerations shape personal travel choices, and the degree to which individuals view vehicles as social signals rather than functional assets. The inclusion of these attitudinal variables reveals the indirect pathways through which household demographics shape vehicle fleet composition, providing specific avenues for policy changes to influences vehicle holdings. The results will enable metropolitan planning organizations and state DOTs to improve vehicle fleet representation in activity-based travel demand models, replacing aggregate ownership assumptions with behaviorally grounded estimates of

Language

• English

Project

• Status: Active
• Funding: $75,000.00
• Contract Numbers:

  69A3552344815

  69A3552348320

• Sponsor Organizations:

  Office of the Assistant Secretary for Research and Technology

  University Transportation Centers Program
  Department of Transportation
  Washington, DC  United States  20590
• Managing Organizations:

  University of Texas at Austin

  Austin, TX  United States  78712
• Performing Organizations:

  University of Texas at Austin

  Austin, TX  United States  78712
• Principal Investigators:

  Bhat, Chandra

• Start Date: 20260601
• Expected Completion Date: 20270531
• Actual Completion Date: 0
• USDOT Program: University Transportation Centers

Subject/Index Terms

• TRT Terms: Attitudes; Automobile ownership; Consumer preferences; Electric vehicles; Households; Internal combustion engines; Probits; Vehicle bodies
• Subject Areas: Energy; Highways; Planning and Forecasting; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 02002871
• Record Type: Research project
• Source Agency: Center for Understanding Future of Travel Behavior and Demand
• Contract Numbers: 69A3552344815, 69A3552348320
• Files: UTC, RIP
• Created Date: Sep 18 2026 10:31AM