Developing a new job accessibility measurement based on crowdsourced traffic data and GTFS

Kim, Junghwan

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https://hdl.handle.net/2142/101647 Copy

Description

Title

Developing a new job accessibility measurement based on crowdsourced traffic data and GTFS

Author(s)

Kim, Junghwan

Issue Date

2018-06-04

Director of Research (if dissertation) or Advisor (if thesis)

Lee, Bumsoo

Committee Member(s)

Braun, Lindsay Maurer

Department of Study

Urban & Regional Planning

Discipline

Urban Planning

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.U.P.

Degree Level

Thesis

Date of Ingest

2018-09-27T16:28:03Z

Keyword(s)

Spatial mismatch, job accessibility, public transit, travel impedance, Google Maps API, General Transit Feed Specification (GTFS)

Abstract

This research aims to develop a new innovative job accessibility measurement that captures actual travel impedance by automobile and public transit. To illustrate the refined job accessibility measurement, this study empirically measures auto-based job accessibility and transit-based job accessibility of regions in the Chicago Metropolitan Statistical Area. This research uses Google Maps Distance Matrix API to get actual auto travel time. Additionally, to capture numerous factors that may affect transit travel impedance, this research computes in-vehicle travel time, out-vehicle travel time, the number of transfers, and the number of feasible alternative routes of transit trips by using the General Transit Feed Specification (GTFS) dataset. These computed data are used to estimate the utility-based travel impedance functions. Based on the utility-based travel impedance functions estimated by the binary logit choice model, this research refines a job accessibility measurement that better captures actual travel impedance of commuters. The refined job accessibility measurement demonstrates more detailed spatial patterns of job accessibility of workers that were not revealed by conventional job accessibility measurements. The significant contribution of this research is to improve job accessibility measurements that capture actual travel impedance by using crowdsourced real-time traffic data and detailed profiles of transit routes. These improvements are possible thanks to recent advances in GIS and Big Data technologies.

Graduation Semester

2018-08

Type of Resource

text

Permalink

http://hdl.handle.net/2142/101647

Copyright and License Information

© 2018 Junghwan Kim

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