Mode Choice Heterogeneity Among Zero-Vehicle Households: A Latent Class Cluster Approach

TL;DR

This study uncovers distinct mobility patterns among zero-vehicle households using latent class analysis, revealing three segments with different transportation behaviors and needs, which can inform targeted transportation policies.

Contribution

It applies a novel latent class clustering method to identify diverse travel behaviors within zero-vehicle households, addressing the assumption of homogeneity in prior research.

Findings

Identified three distinct ZVH segments with unique mobility patterns.

Each segment relies on different transportation modes and trip purposes.

Results support tailored transportation planning for diverse ZVH groups.

Abstract

In transportation planning, Zero-Vehicle Households (ZVHs) are often treated as a uniform group with limited mobility options and assumed to rely heavily on walking or public transit. However, such assumptions overlook the diverse travel strategies ZVHs employ in response to varying trip needs and sociodemographic factors. This study addresses this gap by applying a weighted Latent Class Cluster Analysis (LCCA) to data from the 2022 National Household Travel Survey (NHTS) to uncover distinct mobility patterns within the ZVH population. Using travel mode and trip purpose as indicators and demographic, economic, and built environment variables as covariates, we identified three latent classes :Shared mobility errand workers (36.3%), who primarily use transit and ridehailing for commuting and essential activities; car based shoppers (29.9%), who depend on informal vehicle access for longer discretionary trips and active travel Shoppers (33.8%), who rely on walking or cycling for short, local shopping oriented travel. These behavioral findings enable policymakers to develop differentiated planning solutions to the specific needs of each segment among the ZVHs population across varied geographic and demographic settings.