Accessibility, Connectivity, and Captivity: Impacts on Transit Choice

Edward Beimborn, Michael J. Greenwald, Xia Jin

Transportation Research Record Journal of the Transportation Research Board · 2003 · 181 citations · 3 references

Concepts

TL;DR

Travelers are divided into choice users, who select transit or car when one is superior, and captive users, who have only one option, yet little is known about how captivity affects mode‑split models. This study investigates how transit accessibility and connectivity influence users’ captivity status and subsequent mode choice. Using 1994 Portland Household Activity and Travel Diary data linked to land‑use, fuel‑economy, and energy databases, trips were classified into transit‑captive, automobile‑captive, and choice users, and traditional mode‑split models were compared with segmented models. Traditional models underestimate variation among captive users and overestimate transit attractiveness for choice users; incorporating accessibility and connectivity improves forecasts, and for choice transit users, walk access matters more than travel‑time differences.

Abstract

Travelers can be classified into two groups: choice users and captive users. Choice users select transit or automobile service when they view one option as superior, whereas captive users have only one travel option. Surprisingly, little is known about captivity effects on mode split models. This research examines the way transit service factors such as accessibility and connectivity relate to mode captivity and mode choice. Data for this investigation come from the Portland, Oregon, 1994 Household Activity and Travel Diary Survey, the Regional Land Information System for the Portland area, the U.S. Environmental Protection Agency fuel economy database, and the U.S. Department of Energy. Individual trip data were segmented into transit captive, automobile captive, and choice users based on information about private vehicle availability, transit connectivity, and distance from a transit stop. Traditional transit mode split models are compared with models that segment users into choice and captive groups. It was found that traditional models underestimate the variation in mode choice for captive users, while overestimating the attractiveness of transit for choice users. These results indicate that better transit forecasts can result if accessibility and connectivity are used to help identify captive users. Additionally, among choice transit users, differences in travel times between automobile and transit modes do little to influence mode selection, while walk access to transit has more effect than previously thought.

References

3