New Berkeley Lab analysis simulates fleet of self-driving taxis in Manhattan
It may be only a matter of time before urban dwellers can hail a self-driving taxi, so researchers at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) and UC Berkeley decided to analyze the cost, energy, and environmental implications of a fleet of self-driving electric vehicles operating in Manhattan.
Using models they built and data from more than 10 million taxi trips in New York City, they found that shared automated electric vehicles, or SAEVs, could get the job done at a lower cost – by an order of magnitude – than present-day taxis while also reducing greenhouse gas emissions and energy consumption. What’s more, they found that “range anxiety” is moot because smaller cars with a smaller battery range were sufficient to complete the trips, although more charging stations would be needed.
Their study, “Cost, Energy, and Environmental Impact of Automated Electric Taxi Fleets in Manhattan,” was published recently in the journal Environmental Science & Technology. The corresponding author is Gordon Bauer of UC Berkeley’s Energy and Resources Group, and co-authors are Jeffery Greenblatt and Brian Gerke of Berkeley Lab.
“The EV industry is focusing on the personal car market, trying to make the range as large as possible,” said Greenblatt. “The standard now is 200 miles. We suspected you wouldn’t need as much for taxis. We found plenty of times during the day when a portion of taxis could slip off to recharge, even if just for a few minutes. This greatly reduces the need to have a big battery and therefore drives down cost. It is dependent on having a fairly dense charging network.”
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