According to a new study published in the journal Nature Climate Change, per-mile greenhouse gas emissions of an electric vehicle deployed as an autonomous taxi in 2030 would be 87 to 94% lower than a 2014 gasoline-powered private vehicle and 63 to 82% lower than a 2030 privately owned hybrid vehicle. Almost half of the savings is attributable to right-sizing, where the size of the robotic taxi deployed is tailored to each trip’s occupancy needs.
Taxis in New York City. Image credit: Prayitno Hadinata / CC BY 2.0.
“When we first started looking at autonomous vehicles, we found that, of all the variables we could consider, the use of autonomous vehicles as part of a shared transit system seemed to be the biggest lever that pointed to lower energy use per mile,” said study first author Dr Jeff Greenblatt of the Lawrence Berkeley National Laboratory.
Many companies are working on autonomous cars. Right-sizing is cost-effective for both the fleet owner and for passengers, and small one- and two-seat vehicles are being explored by researchers and companies.
“Most trips in the U.S. are taken singly, meaning one- or two-seat cars would satisfy most trips. That gives us a factor of two savings, since smaller vehicles means reduced energy use and greenhouse gas emissions,” Dr Greenblatt said.
Another factor contributing to lower emissions for robotic taxis is a cleaner electric grid. By 2030 power plants are expected to be using more renewable energy and emitting less pollution, meaning the greenhouse gas intensity of electricity will be lower.
Dr Greenblatt and his colleague, Dr Samveg Saxena, also from the Lawrence Berkeley National Laboratory, did not try to estimate how widespread robotic taxis would be in 2030.
However, they did calculate that if 5% of 2030 vehicle sales (about 800,000 vehicles) were shifted to autonomous taxis, it would save about 7 million barrels of oil per year and reduce annual greenhouse gas emissions by between 2.1 and 2.4 million metric tons of carbon dioxide per year.
To estimate the number of trips taken by different numbers of occupants, the team analyzed National Household Travel Survey data from the Federal Highway Administration.
Dr Greenblatt and Dr Saxena then modeled hypothetical one- and two-seat vehicles based on Nissan Leaf parameters driving three test-drive cycles as defined by the EPA using Autonomie, a vehicle-modeling tool developed by Argonne National Laboratory.
Furthermore, they explored the net energy effect of combining ride-sharing with right-sized autonomous taxis. For example, if 10% of one-person rides were shifted to two-person rides, the total miles traveled would decrease 3.1% while average energy consumption would increase 0.6%, resulting in a net energy decrease of 2.5%.
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Jeffery B. Greenblatt & Samveg Saxena. Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles. Nature Climate Change, published online July 06, 2015; doi: 10.1038/nclimate2685
