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Title: An Overview of Technologies for Individual Trip History Collection: Mobility Decision Science Pillar SMART Mobility Consortium

Abstract

WholeTraveler is a project of the Department of Energy's Smart Mobility consortium that explores how an individual's attitudes and lifestyle characteristics are embodied in transportation behaviors throughout one's life trajectory. As a study at the nexus of decision science and urban systems analysis, fine-grained location data (FGLD), or records of an individual's location collected at a resolution sufficient to determine both the unique destinations a traveler visits each day and the modes used to travel between them, underlie high quality results. Moreover, the methods for collecting FGLD and the means through which they are associated with a traveler's personal attributes have significant implications for the burden on research participants, the cost and complexity of the study, as well as the confidence with which hypotheses can be validated. This paper provides a broad overview of existing technologies for FGLD collection and is intended to provide a literature review for researcher exploring similar domain areas. Technologies are categorized as either network or onboard approaches. An onboard system, such as smartphone or GPS device, sends signals to external networks to capture its own location. Conversely, network systems, such as cell towers, are comprised of sensing nodes with known locations that record when individuallymore » identifiable assets come within their range of detection. Our analysis indicates that the most sensible approach to FGLD collection, for the purposes of WholeTraveler, is to leverage onboard devices, and in particular the existing Moves or Google Maps applications for Android and iOS smartphones. Dedicated GPS devices have been widely implemented by the transportation research community and pose an alternatively acceptable form of FGLD collection. Independently developing a custom smartphone application is not recommended because of the notable challenges in establishing minimal viable functionality, as well as in ensuring compatibility across an ever-growing combination of hardware devices and software versions. No matter the technical means of data collection, the secure handling of FGLD is of critical importance.« less

Authors:
 [1];  [1];  [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
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:
1490251
Report Number(s):
NREL/TP-6A20-70331
DOE Contract Number:  
AC36-08GO28308
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
33 ADVANCED PROPULSION SYSTEMS; travel history; location data; trip diary; smartphone; GPS; CDR

Citation Formats

Kwasnik, Ted, Carmichael, Scott P, and Isley, Steven C. An Overview of Technologies for Individual Trip History Collection: Mobility Decision Science Pillar SMART Mobility Consortium. United States: N. p., 2019. Web. doi:10.2172/1490251.
Kwasnik, Ted, Carmichael, Scott P, & Isley, Steven C. An Overview of Technologies for Individual Trip History Collection: Mobility Decision Science Pillar SMART Mobility Consortium. United States. doi:10.2172/1490251.
Kwasnik, Ted, Carmichael, Scott P, and Isley, Steven C. Fri . "An Overview of Technologies for Individual Trip History Collection: Mobility Decision Science Pillar SMART Mobility Consortium". United States. doi:10.2172/1490251. https://www.osti.gov/servlets/purl/1490251.
@article{osti_1490251,
title = {An Overview of Technologies for Individual Trip History Collection: Mobility Decision Science Pillar SMART Mobility Consortium},
author = {Kwasnik, Ted and Carmichael, Scott P and Isley, Steven C},
abstractNote = {WholeTraveler is a project of the Department of Energy's Smart Mobility consortium that explores how an individual's attitudes and lifestyle characteristics are embodied in transportation behaviors throughout one's life trajectory. As a study at the nexus of decision science and urban systems analysis, fine-grained location data (FGLD), or records of an individual's location collected at a resolution sufficient to determine both the unique destinations a traveler visits each day and the modes used to travel between them, underlie high quality results. Moreover, the methods for collecting FGLD and the means through which they are associated with a traveler's personal attributes have significant implications for the burden on research participants, the cost and complexity of the study, as well as the confidence with which hypotheses can be validated. This paper provides a broad overview of existing technologies for FGLD collection and is intended to provide a literature review for researcher exploring similar domain areas. Technologies are categorized as either network or onboard approaches. An onboard system, such as smartphone or GPS device, sends signals to external networks to capture its own location. Conversely, network systems, such as cell towers, are comprised of sensing nodes with known locations that record when individually identifiable assets come within their range of detection. Our analysis indicates that the most sensible approach to FGLD collection, for the purposes of WholeTraveler, is to leverage onboard devices, and in particular the existing Moves or Google Maps applications for Android and iOS smartphones. Dedicated GPS devices have been widely implemented by the transportation research community and pose an alternatively acceptable form of FGLD collection. Independently developing a custom smartphone application is not recommended because of the notable challenges in establishing minimal viable functionality, as well as in ensuring compatibility across an ever-growing combination of hardware devices and software versions. No matter the technical means of data collection, the secure handling of FGLD is of critical importance.},
doi = {10.2172/1490251},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {1}
}

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