Show simple item record

Life cycle greenhouse gas emissions for last-mile parcel delivery by automated vehicles and robots

dc.contributor.authorLi, Luyao
dc.contributor.advisorKeoleian, Greg
dc.date.accessioned2021-05-01T20:23:25Z
dc.date.issued2021-04
dc.date.submitted2021-04
dc.identifier.urihttps://hdl.handle.net/2027.42/167295
dc.description.abstractIncreased E-commerce and demand for contactless delivery during the COVID-19 pandemic have fueled interest in robotic package delivery. We evaluate life cycle greenhouse gas (GHG) emissions for automated ground delivery systems consisting of a vehicle (last-mile) and a robot (final-50-feet) in a suburban setting. Small and large cargo vans (125 and 350 cubic feet; V125 and V350) with internal combustion engine (ICEV) and battery electric (BEV) powertrains were assessed for three delivery scenarios: (i) conventional, human-driven vehicle with human delivery; (ii) partially automated, human-driven vehicle with robot delivery; and (iii) fully automated: connected automated vehicle (CAV) with robot delivery. The robot’s contribution to life cycle GHG emissions is small (2-6%). CAV auxiliary loads offset operational benefits from automated driving. Compared to the conventional scenario, full automation results in 7% lower GHG emissions for the V350-ICEV but 5% higher for the V125-BEV. Conventional delivery with a V125-BEV provides the lowest GHG emissions, 160 g CO2e/package, while partially automated delivery with a V350-ICEV generates the most at 450 g CO2e/package. Sensitivity analysis shows delivery density and fuel economy are key parameters determining GHG emissions for all scenarios, while CAV power requirements and efficiency benefits have a smaller impact on automated scenario emissions.en_US
dc.language.isoen_USen_US
dc.subjectautomated vehicleen_US
dc.subjectlife cycle assessmenten_US
dc.subjectgreenhouse gas emissionsen_US
dc.titleLife cycle greenhouse gas emissions for last-mile parcel delivery by automated vehicles and robotsen_US
dc.typeThesisen_US
dc.description.thesisdegreenameMaster of Science (MS)en_US
dc.description.thesisdegreedisciplineSchool for Environment and Sustainabilityen_US
dc.description.thesisdegreegrantorUniversity of Michiganen_US
dc.contributor.committeememberKim, Hyung Chul
dc.identifier.uniqnamelluyaoen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/167295/1/Li_Luyao_Thesis.pdf
dc.identifier.doihttps://dx.doi.org/10.7302/970
dc.working.doi10.7302/970en_US
dc.owningcollnameDissertations and Theses (Ph.D. and Master's)


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.