Full metadata
Title
Automated Driving Systems Advancement for Higher Energy Efficiency and Carbon Emissions Reduction
Description
Research studies on improving Automated Driving Systems (ADS) have focused mainly on enhancing safety, through the development of more sophisticated sensors that have the ability to detect objects promptly. Safety is indeed a priority especially when the public has raised concerns regarding unmanned vehicles failing to make informed decisions in unforeseen situations, for example, the Uber Automated Vehicle (AV) crash that happened in Arizona, in 2018 (Griggs & Wakabayashi, 2018). However, one question still remains suppositious: How will the continuous development of AVs impact carbon emissions and energy consumption? Since many automakers claim that automated driving is part of the future of mobility, there is a possibility that automated driving could promote the use of alternative clean fuels like electric batteries and support further travels with the least amount of energy. Therefore, this paper discusses how new ADS technologies with energy-saving benefits, will enable multiple levels of vehicle autonomy to perform efficiently and cause less environmental impacts. In addition, this paper discusses prospective developments in other industries, that could emerge to compliment the next generation ADS technologies and also help decrease the global energy demand that is projected to increase by some 28 percent between now and the year 2040 (“EIA projects 28% increase in world energy use by 2040 - Today in Energy - U.S. Energy Information Administration (EIA),” n.d.)
Date Created
2019-05
Contributors
- Sinyangwe, Stephano Kapya (Author)
- Wishart, Jeffrey (Thesis director)
- Yan, Chen (Committee member)
- Engineering Programs (Contributor)
- School of Sustainability (Contributor)
- Barrett, The Honors College (Contributor)
Topical Subject
Resource Type
Extent
26 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2018-2019
Handle
https://hdl.handle.net/2286/R.I.53003
Level of coding
minimal
Cataloging Standards
System Created
- 2019-04-21 12:00:07
System Modified
- 2021-08-11 04:09:57
- 3 years 2 months ago
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