Exploring neighbourhood-level mobility inequity in Chicago using dynamic transportation mode choice profiles

This paper develops a method to dynamically model urban passenger mode trade-offs at fine-grained spatial and temporal scales using data from OpenTripPlanner (OTP) and the City of Chicago’s Transportation Network Providers (TNP) dataset. This approach can be used to calculate dynamic modal cost-dist...

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Autores principales:	Kevin Credit, Gustavo Dias, Brenda Li
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Mobility inequity Mode choice Open data Spatial interaction models Built environment Non-auto transportation Transportation and communications HE1-9990
Acceso en línea:	https://doaj.org/article/25e607daeb394f53b03fb0e74ab35782
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spelling	oai:doaj.org-article:25e607daeb394f53b03fb0e74ab357822021-11-10T04:41:03ZExploring neighbourhood-level mobility inequity in Chicago using dynamic transportation mode choice profiles2590-198210.1016/j.trip.2021.100489https://doaj.org/article/25e607daeb394f53b03fb0e74ab357822021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2590198221001949https://doaj.org/toc/2590-1982This paper develops a method to dynamically model urban passenger mode trade-offs at fine-grained spatial and temporal scales using data from OpenTripPlanner (OTP) and the City of Chicago’s Transportation Network Providers (TNP) dataset. This approach can be used to calculate dynamic modal cost-distance trade-offs for specific times, routes, and geographic areas of interest, providing a framework for creating aggregate mode choice profiles for individual cities and neighbourhoods that can be used to assess structural differences in transportation investment and mobility, as well as to test various assumptions about travel behaviour, observe temporal changes in modal trade-offs, and model the system-wide implications of changes to the transportation system to modal trade-offs. Using this dynamic mode choice framework, this paper explores the features underlying observed structural heterogeneity in the ratio of cost to distance (i.e., speed or potential mobility) for observed flows across the city for each mode. It finds that Census tracts with larger proportions of Black and Hispanic population tend to have significantly larger cost-distance ratios (i.e., slower speeds/lower potential mobility) for non-auto modes, while Census tracts with higher proportions of “creative class” employment and features of walkable built environments have significantly lower cost-distance ratios (i.e., faster speeds/higher potential mobility).Kevin CreditGustavo DiasBrenda LiElsevierarticleMobility inequityMode choiceOpen dataSpatial interaction modelsBuilt environmentNon-auto transportationTransportation and communicationsHE1-9990ENTransportation Research Interdisciplinary Perspectives, Vol 12, Iss , Pp 100489- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Mobility inequity Mode choice Open data Spatial interaction models Built environment Non-auto transportation Transportation and communications HE1-9990
spellingShingle	Mobility inequity Mode choice Open data Spatial interaction models Built environment Non-auto transportation Transportation and communications HE1-9990 Kevin Credit Gustavo Dias Brenda Li Exploring neighbourhood-level mobility inequity in Chicago using dynamic transportation mode choice profiles
description	This paper develops a method to dynamically model urban passenger mode trade-offs at fine-grained spatial and temporal scales using data from OpenTripPlanner (OTP) and the City of Chicago’s Transportation Network Providers (TNP) dataset. This approach can be used to calculate dynamic modal cost-distance trade-offs for specific times, routes, and geographic areas of interest, providing a framework for creating aggregate mode choice profiles for individual cities and neighbourhoods that can be used to assess structural differences in transportation investment and mobility, as well as to test various assumptions about travel behaviour, observe temporal changes in modal trade-offs, and model the system-wide implications of changes to the transportation system to modal trade-offs. Using this dynamic mode choice framework, this paper explores the features underlying observed structural heterogeneity in the ratio of cost to distance (i.e., speed or potential mobility) for observed flows across the city for each mode. It finds that Census tracts with larger proportions of Black and Hispanic population tend to have significantly larger cost-distance ratios (i.e., slower speeds/lower potential mobility) for non-auto modes, while Census tracts with higher proportions of “creative class” employment and features of walkable built environments have significantly lower cost-distance ratios (i.e., faster speeds/higher potential mobility).
format	article
author	Kevin Credit Gustavo Dias Brenda Li
author_facet	Kevin Credit Gustavo Dias Brenda Li
author_sort	Kevin Credit
title	Exploring neighbourhood-level mobility inequity in Chicago using dynamic transportation mode choice profiles
title_short	Exploring neighbourhood-level mobility inequity in Chicago using dynamic transportation mode choice profiles
title_full	Exploring neighbourhood-level mobility inequity in Chicago using dynamic transportation mode choice profiles
title_fullStr	Exploring neighbourhood-level mobility inequity in Chicago using dynamic transportation mode choice profiles
title_full_unstemmed	Exploring neighbourhood-level mobility inequity in Chicago using dynamic transportation mode choice profiles
title_sort	exploring neighbourhood-level mobility inequity in chicago using dynamic transportation mode choice profiles
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/25e607daeb394f53b03fb0e74ab35782
work_keys_str_mv	AT kevincredit exploringneighbourhoodlevelmobilityinequityinchicagousingdynamictransportationmodechoiceprofiles AT gustavodias exploringneighbourhoodlevelmobilityinequityinchicagousingdynamictransportationmodechoiceprofiles AT brendali exploringneighbourhoodlevelmobilityinequityinchicagousingdynamictransportationmodechoiceprofiles
_version_	1718440537542885376

Exploring neighbourhood-level mobility inequity in Chicago using dynamic transportation mode choice profiles

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