Researchers at Lawrence Berkeley National Laboratory (Berkeley Lab) have found that the per-mile greenhouse gas emissions of an electric autonomous taxi in 2030 would be 63-82% lower than a projected 2030 hybrid vehicle driven as a privately owned car and 90% lower than a 2014 gasoline-powered private vehicle. Their paper appears in the journal Nature Climate Change.
The autonomous vehicles (AVs) gain their through three synergistic effects, the researchers found: (1) future decreases in electricity GHG emissions intensity; (2) smaller vehicle sizes resulting from trip-specific autonomous taxi deployment (i.e., “right-sizing,” where the size of the taxi deployed is tailored to each trip’s occupancy needs); and (3) higher annual vehicle-miles travelled (VMT), increasing high-efficiency (especially battery-electric) vehicle cost-effectiveness.
The substantial GHG savings could enable GHG reductions even if total vehicle miles traveled (VMT), average speed and vehicle size increased substantially, Berkeley Lab scientists Jeffery Greenblatt and Samveg Saxena suggested. Oil consumption would also be reduced by nearly 100%.
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.—Jeffery Greenblatt
Many automakers and other 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. As an example, a single passenger with no luggage would require a much smaller taxi than a party of four with luggage. Right-sizing assumes a fleet of taxis managed by a single entity.
Most trips in the US are taken singly, meaning one- or two-seat cars would satisfy most trips, Greenblatt said. “That gives us a factor of two savings, since smaller vehicles means reduced energy use and greenhouse gas emissions.”
From another perspective, if 10% of one-person rides were shifted to two-person rides, the total miles traveled would decrease 3.1% while average energy consumption (due to the larger vehicle) would increase 0.6%, resulting in a net energy decrease of 2.5%.
Self-driving cars have additional efficiencies that have been covered in other research, such as the ability to drive closely behind other autonomous cars to reduce wind resistance (“platooning”); optimally routing trip;, and smoother acceleration and braking. Greenblatt and Saxena, however, did not include these incremental effects in their baseline results.
The researchers also conducted an economic analysis to determine how cost-effective autonomous taxis would be. At 12,000 miles per year, the average distance traveled in the US for privately owned cars, electric vehicles in 2030 are still expected to be more expensive than owning and operating a gasoline-powered car, the study found.
But if the vehicle is driven 40,000 to 70,000 miles per year, typical for US taxis, they found that an alternative-fuel vehicle (hydrogen fuel cell or electric battery) was the most cost-effective option. This was based on costs for maintenance, fuel, insurance, and the actual cost of the vehicle (assuming a five-year loan). The reason is that despite the higher cost of a more efficient vehicle, the per-mile cost of fuel is lower, so the savings can pay for the extra investment.
An autonomous taxi using today’s technology would still be cheaper than an ordinary taxi not simply due to its greater energy efficiency, but also due to the fact that no operator would be required. By 2030, autonomous taxis could be far cheaper than their driven counterparts.
Greenblatt and Saxena did not try to estimate how widespread this technology would be in 2030. However, they did calculate that if five percent 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 CO2 per year, equal to the emissions savings from more than 1,000 two-megawatt wind turbines.
To estimate the number of trips taken by different numbers of occupants, the researchers analyzed National Household Travel Survey data from the Federal Highway Administration. The scientists then modeled hypothetical one- and two-seat vehicles based on Nissan Leaf parameters driving three test-drive cycles as defined by the Environmental Protection Agency (EPA) using Autonomie, a vehicle-modeling tool developed by Argonne National Laboratory that simulates energy consumption on a second-by-second basis.
Greenblatt said plans for further study on this topic are in the works, including exploring the effect of battery degradation, looking at optimal vehicle designs, and making a more realistic simulation of how a fleet of autonomous taxis would actually operate in a metropolitan area.
The study was funded in part by the Laboratory Directed Research and Development (LDRD) program at Berkeley Lab.
Jeffery B. Greenblatt & Samveg Saxena (2015) “Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles” Nature Climate Change doi: 10.1038/nclimate2685