Forecasting the Impact of Connected and Automated Vehicles on Energy Use: A Microeconomic Study of Induced Travel and Energy Rebound
dc.contributor.author | Taiebat, Morteza | |
dc.contributor.author | Solper, Samuel | |
dc.contributor.author | Xu, Ming | |
dc.date.accessioned | 2019-06-04T16:21:43Z | |
dc.date.available | 2019-06-04T16:21:43Z | |
dc.date.issued | 2019-06-04 | |
dc.identifier.citation | Taiebat, M., Stolper, S., & Xu, M. (2019). Forecasting the Impact of Connected and Automated Vehicles on Energy Use: A Microeconomic Study of Induced Travel and Energy Rebound. Applied Energy, 247, 297–308. https://doi.org/10.1016/j.apenergy.2019.03.174 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/149382 | |
dc.description.abstract | Connected and automated vehicles (CAVs) are expected to yield significant improvements in safety, energy efficiency, and time utilization. However, their net effect on energy and environmental outcomes is unclear. Higher fuel economy reduces the energy required per mile of travel, but it also reduces the fuel cost of travel, incentivizing more travel and causing an energy “rebound effect.” Moreover, CAVs are predicted to vastly reduce the time cost of travel, inducing further increases in travel and energy use. In this paper, we forecast the induced travel and rebound from CAVs using data on existing travel behavior. We develop a microeconomic model of vehicle miles traveled (VMT) choice under income and time constraints; then we use it to estimate elasticities of VMT demand with respect to fuel and time costs, with fuel cost data from the 2017 United States National Household Travel Survey (NHTS) and wage-derived predictions of travel time cost. Our central estimate of the combined price elasticity of VMT demand is −0.4, which differs substantially from previous estimates. We also find evidence that wealthier households have more elastic demand, and that households at all income levels are more sensitive to time costs than to fuel costs. We use our estimated elasticities to simulate VMT and energy use impacts of full, private CAV adoption under a range of possible changes to the fuel and time costs of travel. We forecast a 2–47% increase in travel demand for an average household. Our results indicate that backfire – i.e., a net rise in energy use – is a possibility, especially in higher income groups. This presents a stiff challenge to policy goals for reductions in not only energy use but also traffic congestion and local and global air pollution, as CAV use increases. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Elsevier | en_US |
dc.subject | Autonomous Vehicles | en_US |
dc.subject | Automated Vehicles | en_US |
dc.subject | Self-driving Cars | en_US |
dc.subject | Energy Demand | en_US |
dc.subject | Fuel Economy | en_US |
dc.subject | Induced Travel | en_US |
dc.subject | Rebound Effect | en_US |
dc.subject | Travel Time Cost | en_US |
dc.subject | Vehicle Automation | en_US |
dc.subject | Travel Behavior | en_US |
dc.title | Forecasting the Impact of Connected and Automated Vehicles on Energy Use: A Microeconomic Study of Induced Travel and Energy Rebound | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Natural Resources and Environment | |
dc.subject.hlbtoplevel | Science | |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | University of Michigan | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | https://deepblue.lib.umich.edu/bitstream/2027.42/149382/3/CAV_Rebound_Taiebat_Stolper_Xu_AppliedEnergy2019.pdf | |
dc.identifier.doi | 10.1016/j.apenergy.2019.03.174 | |
dc.identifier.source | Applied Energy | en_US |
dc.identifier.orcid | 0000-0002-2797-7458 | en_US |
dc.identifier.orcid | 0000-0002-7106-8390 | en_US |
dc.description.filedescription | Description of CAV_Rebound_Taiebat_Stolper_Xu_AppliedEnergy2019.pdf : Main article | |
dc.description.filedescription | Description of CAV_Rebound_Taiebat_Stolper_Xu_AppliedEnergy2019.pdf : Main article | |
dc.identifier.name-orcid | Taiebat, Morteza; 0000-0002-2797-7458 | en_US |
dc.identifier.name-orcid | Xu, Ming; 0000-0002-7106-8390 | en_US |
dc.owningcollname | Environment and Sustainability, School for (SEAS/SNRE) |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.