Sustainability of Self-Driving Mobility: An Analysis of Carbon Emissions Between Autonomous Vehicles and Conventional Modes of Transportation
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CitationMccarthy, John Francis. 2017. Sustainability of Self-Driving Mobility: An Analysis of Carbon Emissions Between Autonomous Vehicles and Conventional Modes of Transportation. Master's thesis, Harvard Extension School.
AbstractThe primary contribution of this paper is to identify the potential variables through which vehicle automation may affect carbon emissions in the transportation sector, and compare modal shifts between conventional vehicles, public transportation, and pilot autonomous vehicles (AVs). AV programs that are rapidly emerging in cities, states, and nations across the globe mark the early stages of the next transportation revolution akin to the steam engine and assembly line. By safely allowing humans to take their hands off the steering wheel, autonomous technology could potential prevent 90% of car collisions every year, save hundreds of billions of dollars, and reduce carbon emissions. In order to examine how a modal shift to autonomous vehicles will impact carbon emissions specifically, I consolidated a literature review of AV factors that both help and hinder energy consumption and designed a carbon emissions model based on the United Nations (UN) Framework Convention on Climate Change.
I conducted various simulations to compare a modal shift away from public transit and toward AVs to address several research questions: Are AVs a viable mitigation strategy to reduce carbon emissions in the transportation sector? And will a modal shift to AV-based travel in urban areas produce more pounds of carbon per passenger mile than traditional modes of public transportation? Through these simulations, I examined two hypotheses. First, in the event that all public transportation passengers shift to traveling by AVs, carbon emissions in the transportation sector will increase compared to baseline emissions. And second, modes of public transportation have a lower emissions rate (pounds of CO2 per passenger-mile) than AVs.
The scenarios modeled in this paper offer a glimpse into how AV technology might impact carbon emissions at a time when there are already early indicators of a transition to AVs. Based on these scenarios, it appears that Level 4 AVs would reduce emissions more than Level 3. Right-sizing, reduced engine performance, and platooning are AV factors that are available only in Level 4 vehicles and represent an 83.5% improvement in fuel economy. A modal shift to Level 4 AVs coupled with alternative fueled vehicles could substantially reduce carbon emissions. Specifically, emissions from conventional internal combustion engine cars were reduced by 50% as a result of a modal shift to hybrids, electrics, and CNG vehicles. However, a modal shift to public transportation coupled with a clean energy electrical grid reduced emissions by 91% compared to the baseline based on the model, 14% more than a complete modal shift to alternative energy Level 4 AVs.
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