Evaluating the Impacts of Autonomous Electric Vehicles Adoption on Vehicle Miles Traveled and CO 2 Emissions

Jingyi Xiao (), Konstadinos G. Goulias (), Srinath Ravulaparthy, Shivam Sharda, Ling Jin and C. Anna Spurlock
Additional contact information
Jingyi Xiao: Department of Geography and GeoTrans Lab, University of California, Santa Barbara, CA 93106, USA
Konstadinos G. Goulias: Department of Geography and GeoTrans Lab, University of California, Santa Barbara, CA 93106, USA
Srinath Ravulaparthy: Department of Geography and GeoTrans Lab, University of California, Santa Barbara, CA 93106, USA
Shivam Sharda: National Renewable Energy Laboratory, Golden, CO 80401, USA
Ling Jin: Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
C. Anna Spurlock: Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA

Energies, 2024, vol. 17, issue 23, 1-19

Abstract: Autonomous electric vehicles (AEVs) can potentially revolutionize the transportation landscape, offering a safer, contact-free, easily accessible, and more eco-friendly mode of travel. Prior to the market uptake of AEVs, it is critical to understand the consumer segments that are most likely to adopt these vehicles. Beyond market adoption, it is also important to quantify the impact of AEVs on broader transportation systems and the environment, such as impacts on the annual vehicle miles traveled (VMT) and greenhouse gas (GHG) emissions. In this pilot study, using survey data, a statistical model correlating AEV adoption intention and socioeconomic and built environment attributes was estimated, and a sensitivity analysis was conducted to understand the importance of factors impacting AEV adoption. We found that the market segments range from early adopters who are wealthy, technologically savvy, and relatively young to non-adopters who are more cautious to new technologies. This is followed by a synthetic population microsimulation of market penetration for the San Francisco Bay Area. With five household vehicle replacement scenarios, we assessed the annual VMT and tailpipe carbon dioxide (CO 2 ) emissions change associated with vehicle replacement. It is found that adopting AEVs can potentially reduce more than 5 megatons of CO 2 yearly, which is approximately 30% of the total CO 2 emitted by internal combustion engine (ICE) cars in the region.

Keywords: autonomous electric vehicles; microsimulation; market scenarios; demand model; vehicle miles traveled; greenhouse gas emissions (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/17/23/6127/pdf (application/pdf)
https://www.mdpi.com/1996-1073/17/23/6127/ (text/html)

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:gam:jeners:v:17:y:2024:i:23:p:6127-:d:1537245

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().