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Title: Typology of Cities for Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium

Abstract

Mobility patterns, technology adoption and associated energy outcomes vary tremendously across settlement types. This poster discusses how a highly geographically resolved exploration of the social, economic, techno-infrastructural and environmental domains is key to understanding observed variations in transportation technology adoption and associated mobility and energy outcomes. Current socioeconomic and mobility data sets at the census block group level are integrated in a hierarchical clustering approach to show how variations in mobility and energy outcomes are shaped by these domains - which may enhance progress on investments, or effectively inform planning and other decisions for state-wide goals. In a pilot analysis in New York, the clustering produces four settlement types to predict dependent variables of electric vehicle (EV) adoption rates, commute mode, vehicle fuel economy, and vehicles per household. This typology shows EV adoption rates among the core urban population, which is wealthy and highly-educated, are high - 3 EVs/1,000 vehicles versus 1 EV/1,000 vehicles among the urban working class. Commuting mode is closely linked with population and employment density - more than 90% of core urbanites use transit or active modes, compared with only 22% of suburbanites and 17% of rural residents. Household vehicle ownership also varies, with two vehiclesmore » per household in rural areas and only 0.5 in core urban settings.Important findings on differences among the rural, suburban, urban, and urban core settlement types suggest a need to explore how best to manage and anticipate very different types of services that may be supportive in achieving energy-efficient and affordable mobility systems state-wide.« less

Authors:
ORCiD logo [1];  [1];  [1];  [1];  [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [1];  [2]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
  2. Lawrence Berkely National Laboratory
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Vehicle Technologies Office (EE-3V)
OSTI Identifier:
1557082
Report Number(s):
NREL/PO-5400-73736
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Conference
Resource Relation:
Conference: Presented at the 2019 Vehicle Technologies Office Annual Merit Review and Peer Evaluation Meeting, 10-13 June 2019, Arlington, Virginia
Country of Publication:
United States
Language:
English
Subject:
30 DIRECT ENERGY CONVERSION; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; transportation; geography; mobility patterns; technology adoption; energy outcomes; settlement types

Citation Formats

Romero Lankao, Patricia, Wilson, Alana, Zimny-Schmitt, Daniel, Rames, Clement, Neri, Caro, Young, Stanley E, Duvall, Andrew L, Sperling, Joshua, Nychka, Douglas, and Wenzel, Tom. Typology of Cities for Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium. United States: N. p., 2019. Web.
Romero Lankao, Patricia, Wilson, Alana, Zimny-Schmitt, Daniel, Rames, Clement, Neri, Caro, Young, Stanley E, Duvall, Andrew L, Sperling, Joshua, Nychka, Douglas, & Wenzel, Tom. Typology of Cities for Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium. United States.
Romero Lankao, Patricia, Wilson, Alana, Zimny-Schmitt, Daniel, Rames, Clement, Neri, Caro, Young, Stanley E, Duvall, Andrew L, Sperling, Joshua, Nychka, Douglas, and Wenzel, Tom. Wed . "Typology of Cities for Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium". United States. https://www.osti.gov/servlets/purl/1557082.
@article{osti_1557082,
title = {Typology of Cities for Systems and Modeling for Accelerated Research in Transportation (SMART) Mobility Consortium},
author = {Romero Lankao, Patricia and Wilson, Alana and Zimny-Schmitt, Daniel and Rames, Clement and Neri, Caro and Young, Stanley E and Duvall, Andrew L and Sperling, Joshua and Nychka, Douglas and Wenzel, Tom},
abstractNote = {Mobility patterns, technology adoption and associated energy outcomes vary tremendously across settlement types. This poster discusses how a highly geographically resolved exploration of the social, economic, techno-infrastructural and environmental domains is key to understanding observed variations in transportation technology adoption and associated mobility and energy outcomes. Current socioeconomic and mobility data sets at the census block group level are integrated in a hierarchical clustering approach to show how variations in mobility and energy outcomes are shaped by these domains - which may enhance progress on investments, or effectively inform planning and other decisions for state-wide goals. In a pilot analysis in New York, the clustering produces four settlement types to predict dependent variables of electric vehicle (EV) adoption rates, commute mode, vehicle fuel economy, and vehicles per household. This typology shows EV adoption rates among the core urban population, which is wealthy and highly-educated, are high - 3 EVs/1,000 vehicles versus 1 EV/1,000 vehicles among the urban working class. Commuting mode is closely linked with population and employment density - more than 90% of core urbanites use transit or active modes, compared with only 22% of suburbanites and 17% of rural residents. Household vehicle ownership also varies, with two vehicles per household in rural areas and only 0.5 in core urban settings.Important findings on differences among the rural, suburban, urban, and urban core settlement types suggest a need to explore how best to manage and anticipate very different types of services that may be supportive in achieving energy-efficient and affordable mobility systems state-wide.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {8}
}

Conference:
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