Investigating autonomous vehicle impacts on individual activity-travel behavior
Katherine A. Dannemiller,
Aupal Mondal,
Katherine E. Asmussen and
Chandra R. Bhat
Transportation Research Part A: Policy and Practice, 2021, vol. 148, issue C, 402-422
Abstract:
This paper develops an analytic system to investigate the effects of AV availability on multiple dimensions of activity-travel behavior at once, based on a direct survey-based modeling approach. In particular, the model uses individual socio-demographics, built environment variables, as well as psycho-social variables (in the form of latent psychological constructs) as determinant variables to explain likely AV impacts on five dimensions of short-term activity-travel choices: (1) Additional local area trips (that is, those that would not characterized as long distance trips; a long distance trip was defined in the survey as a trip more than 75 miles one-way), (2) Trip distance to shop or eat-out activities in the local area, (3) Trip distance to leisure activities in the local area, (4) Additional long distance road trips beyond the local area, and (5) Commute travel time. The model system includes a confirmatory factor analysis step, a multivariate linear regression model for the latent constructs, and a multivariate ordered-response model for the five main outcomes just listed. Data from a 2019 Austin area survey of new mobility service adoption and use forms the basis for our empirical analysis. Our results, when aggregated across all respondents, does suggest that AVs may not after all have a substantial impact on overall trip-making levels, although local area trips are likely to become longer (for all purposes, including the commute). The highest impact of AVs will, it appears, be on the number of long distance trips (with such trips increasing). Our in-depth examination of the variations in AV activity-travel responses across population segments and geographies underscores the importance of modeling multiple activity-travel dimensions all at once. In addition, our results highlight the value of using psycho-social latent constructs in studies related to the adoption/use of current and emerging mobility services, both in terms of improved prediction fit as well as proactive strategies to design equitable, safe, and community-driven AV systems. There is likely to be considerable heterogeneity in how different population groups view and respond to AVs, and it is imperative that AV campaigns and AV design consider such heterogeneity so as to not “leave anyone behind”.
Keywords: Equity; Autonomous vehicles (AVs); Activity-travel; Long distance travel; Safety; Design; Policy (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S096585642100104X
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:transa:v:148:y:2021:i:c:p:402-422
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.tra.2021.04.006
Access Statistics for this article
Transportation Research Part A: Policy and Practice is currently edited by John (J.M.) Rose
More articles in Transportation Research Part A: Policy and Practice from Elsevier
Bibliographic data for series maintained by Catherine Liu ().