Estimating a large drive time matrix between ZIP codes in the United States: A differential sampling approach

Article

Abstract

Estimating a massive drive time matrix between locations is a practical but challenging task. The challenges include availability of reliable road network (including traffic) data, programming expertise, and access to high-performance computing resources. This research proposes a method for estimating a nationwide drive time matrix between ZIP code areas in the U.S. - a geographic unit at which many national datasets including health information are compiled and distributed. The method (1) does not rely on intensive efforts in data preparation or access to advanced computing resources, (2) uses algorithms of varying complexity and computational time to estimate drive times of different trip lengths, and (3) accounts for both interzonal and intrazonal drive times. The core design samples ZIP code pairs with various intensities according to trip lengths and derives the drive times via Google Maps API, and the Google times are then used to adjust and improve some primitive estimates of drive times with low computational costs. The result provides a valuable resource for researchers.

Attributes

Attribute NameValues
Creator
  • Yujie Hu

  • Changzhen Wang

  • Ruiyang Li

  • Fahui Wang

Journal or Work Title
  • Journal of transport geography

Volume
  • 86

Publication Date
  • 2020-06

Publisher
  • Elsevier

Date Created
  • 2021-10-12

Language
  • English

Departments and Units
Record Visibility Public
Content License
  • All rights reserved

Digital Object Identifier

doi:10.7274/r0-nxk8-pc97

This DOI is the best way to cite this article.

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