U-M study: Induced driving miles could overwhelm potential energy-saving benefits of connected, self-driving cars
The benefits of connected, self-driving cars (CAVs) will likely induce vehicle owners to drive more, and those extra miles could partially or completely offset the potential energy-saving benefits that automation may provide, according to a new University of Michigan study.
In the coming years, self-driving cars are expected to yield significant improvements in safety, traffic flow and energy efficiency. In addition, automation will allow vehicle occupants to make productive use of travel time.
Connected and automated vehicle (CAV) technology is expected to be an indispensable but disruptive factor in the transportation sector, transforming the mobility paradigm, transportation markets, and travelers’ behavior in the coming decades. It will likely increase transportation safety to an unprecedented level, enhance mobility, provide a higher level of comfort and convenience for travelers, and reduce the cost of driving for individuals, all of which will be welfare-improving for society. At the same time, vehicle connectivity and automation will inevitably and significantly change energy demand in the transportation sector. The extent of these changes is still largely unclear and yet will have major consequences for energy supply and the environment alike.
Several characteristics of CAV technology will influence energy consumption, including improvements in route optimization, eco-driving, crash avoidance, and vehicle right-sizing, among others. Many of these improvements will push energy use downwards; however, some will very likely work in the opposing direction. Chief among the factors that will exert upward pressure on energy demand is the marginal cost of driving, which is expected to drop significantly with CAV technology. Higher fuel economy of CAVs will cause the per-mile fuel cost of travel to drop. This, in turn, will induce additional travel that partially offsets the fuel savings of energy efficiency—commonly referred to as a “rebound effect”. In addition, increased comfort and reduced attention requirements3 will cause the per-mile travel time cost to drop, inducing even more additional travel.
The key parameter dictating the magnitude of travel demand induced through these channels is the elasticity of travel demand with respect to the price of travel. … In this paper, we use the most recent empirical microdata available to estimate the elasticity of travel demand with respect to the marginal fuel and time costs of travel in a single, unified framework.—Taiebat et al.
Previous studies have shown that greater fuel efficiency induces some people to travel extra miles, and those added miles can partially offset fuel savings—a behavioral change known as the rebound effect.
In addition, the ability to use in-vehicle time productively in a self-driving car—people can work, sleep, watch a movie, read a book—will likely induce even more travel.
Taken together, those two sources of added mileage could partially or completely offset the energy savings provided by autonomous vehicles, according to a team of researchers at the U-M School for Environment and Sustainability led by Dow Sustainability Doctoral Fellow Morteza Taiebat.
Conceivably, the added miles could even result in a net increase in energy consumption, a phenomenon known as backfire, according to the U-M researchers. Their study is published in the journal Applied Energy.
The core message of the paper is that the induced travel of self-driving cars presents a stiff challenge to policy goals for reductions in energy use.—co-author Samuel Stolper, assistant professor of environment and sustainability at SEAS
Thus, much higher energy efficiency targets are required for self-driving cars.—Ming Xu, associate professor of environment and sustainability at SEAS and associate professor of civil and environmental engineering at the College of Engineering
In the paper, Taiebat and his colleagues used economic theory and US travel survey data to model travel behavior and to forecast the effects of vehicle automation on travel decisions and energy use.
Most previous studies of the energy impact of autonomous vehicles focused exclusively on the fuel-cost component of the price of travel, likely resulting in an overestimation of the environmental benefits of the technology, according to the U-M authors.
In contrast, the study by Taiebat and colleagues looked at both fuel cost and time cost. Their approach adapts standard microeconomic modeling and statistical techniques to account for the value of time.
Traditionally, time spent driving has been viewed as a cost to the driver. But the ability to pursue other activities in an autonomous vehicle is expected to lower this “perceived travel time cost” considerably, which will likely spur additional travel.
The U-M researchers estimated that the induced travel resulting from a 38% reduction in perceived travel time cost would completely eliminate the fuel savings associated with self-driving cars.
The possibility of backfire implies the possibility of net increases in local and global air pollution, the study authors concluded.
In addition, the researchers suggest there’s an equity issue that needs to be addressed as autonomous vehicles become a reality. The study found that wealthier households are more likely than others to drive extra miles in autonomous vehicles “and thus stand to experience greater welfare gains.”
Support was provided by the Dow Sustainability Fellows Program at the University of Michigan.
Morteza Taiebat, Samuel Stolper, Ming Xu (2019) “Forecasting the Impact of Connected and Automated Vehicles on Energy Use: A Microeconomic Study of Induced Travel and Energy Rebound,” Applied Energy, Volume 247, Pages 297-308 doi: 10.1016/j.apenergy.2019.03.174