Model Predicts Electric, Fully-Automated Taxis in San Francisco Can Reduce Net Energy Consumption and Emissions by 54.39 Percent and 33.07 Percent, Respectively.

Researchers Studied the Viability of Autonomous Taxis as a Pathway Towards Reduced Energy Consumption and Emissions Using Publicly Available Data from a Select Market.

Date Posted
03/22/2023
Identifier
2023-B01722
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Estimating the energy impact of electric, autonomous taxis: evidence from a select market

Summary Information

Electric, autonomous vehicles offer great potential for energy savings and emission reductions. This study used publicly available data collected from 2016-2017 from a selected market (San Francisco) to examine the magnitude of the envisioned benefits and the determinants of the financial payoff of investing in vehicle electrification, automation, and sharing based on a mathematical model. In this study, hypothetical Autonomous Taxis (AT) were envisioned to be co-functioning in a target market alongside Conventional Taxis (CT), Personnel Vehicles (PV), and public transit.

METHODOLOGY

This study considered a hypothetical vehicle as the AT; a mid-sized, electric automobile. A two-staged model was developed to first quantify and compare the financial proposition of electric, ATs to CTs and PVs, then assess the energy impact of AT deployment. Expenditures considered included vehicle financing, licensing, insurance, maintenance, cleaning, fuel and safety oversight (specifically for ATs). AT cost estimates also considered heterogeneity, annual mileage and consumer travel time in terms of hourly wages. For emission evaluation, estimates included vehicle production, extraction, processing, transportation, and fuel distribution. AT’s energy profile was assumed to be consistent with an electric automobile; one with a fuel economy and emissions footprint of 114 miles per gallon equivalent and 159.1 CO2 grams per mile, respectively. For comparison purposes, the energy profiles of CTs and PVs were also taken into consideration, using pre-existing market data.

FINDINGS

  • Considering a scenario in which AT fares were comparable to those offered by CTs, presuming demand for AT services parallels that associated with CTs, the model in this study predicted net consumption and emissions reductions of up to 54.39 percent and 33.07 percent, respectively.
  • ATs were found to offer fares comparable to or better than CTs today. At current $3.55 per mile fares, the study estimated that operator profits would rise from $0.27 to between $0.95 and $1.38 per mile, respectively, depending on ATs’ technological maturity. If fleet operators’ profits did not increase, per mile fares would decline from $3.55 to between $1.42 and $2.24.
  • While ATs should be competitive with CTs, it was found that they would be unlikely to offer a financial proposition comparable to PVs.
  • At high levels of technological maturity, AT fares remained costlier than PV ownership ($1.42 versus $0.95 per mile). However, the findings from this study based on profiled AT and specific market characteristics suggested that the confluence of vehicle electrification, vehicle automatization and vehicle sharing may be insufficient to achieve favorable energy outcomes, relative to the status quo.
Results Type
Deployment Locations