Analyzing Walkability Through Biometrics: Insights Into Sustainable Transportation Through the Use of Eye-Tracking Emulation Software

in Journal of Physical Activity and Health

Click name to view affiliation

Justin B. Hollander
Search for other papers by Justin B. Hollander in
Current site
Google Scholar
PubMed
Close
,
Ann Sussman
Search for other papers by Ann Sussman in
Current site
Google Scholar
PubMed
Close
,
Peter Lowitt
Search for other papers by Peter Lowitt in
Current site
Google Scholar
PubMed
Close
,
Neil Angus
Search for other papers by Neil Angus in
Current site
Google Scholar
PubMed
Close
, and
Minyu Situ
Search for other papers by Minyu Situ in
Current site
Google Scholar
PubMed
Close
Restricted access

Background: Understanding more about the unseen side of our responses to visual stimuli offers a powerful new tool for transportation planning. Traditional transportation planning tends to focus on the mobility of vehicles rather than on opportunities to encourage sustainable transport modes, like walking. Methods: Using eye-tracking emulation software, this study measured the unconscious visual responses people have to designs and layouts in new built environments, focusing on what makes streets most walkable. Results: The study found key differences between the way the brain takes in conventional automobile-oriented residential developments versus new urbanist layouts, with the former lacking key fixation points. Conclusion: The study’s discoveries significantly explain why new urbanist layouts promote walking effortlessly and conventional automobile-oriented residential developments cannot.

Hollander and Situ are with the Department of Urban and Environmental Policy and Planning, Tufts University, Medford, MA, USA. Sussman is with Human Architecture and Planning Institute, Concord, MA, USA. Lowitt and Angus are with Devens Enterprise Commission, Devens, MA, USA.

Hollander (justin.hollander@tufts.edu) is corresponding author.
  • Collapse
  • Expand
  • 1.

    Hollander JB, Foster V. Brain responses to architecture and planning: a neuro-assessment of the pedestrian experience in Boston, Massachusetts. Arch Sci Revi. 2016;59(6):474481. doi:10.1080/00038628.2016.1221499

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 2.

    Hollander JB, Sussman A, Levering AP, Foster-Karim C. Using eye-tracking to understand human responses to traditional neighborhood designs. Plan Pract Res. 2020;35(5):485509. doi:10.1080/02697459.2020.1768332

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 3.

    Noland RB, Weiner MD, Gao D, Cook MP, Nelessen A. Eye-tracking technology, visual preference surveys, and urban design: preliminary evidence of an effective methodology. J Urban. 2017;10(1):98110.

    • Search Google Scholar
    • Export Citation
  • 4.

    Poole A, Ball LJ. Eye tracking in HCI and usability research. In: Ghaoui C, ed. Encyclopaedia of Human–Computer Interaction. Pennsylvania, PA: Idea Group Inc.; 2006:211219.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 5.

    Duchowski AT. Eye tracking methodology. Theory Pract. 2007;328(614):23.

  • 6.

    Holmqvist K. Eye Tracking: A Comprehensive Guide to Methods, Paradigms, and Measures. Lund Eye-Tracking Research Institute; 2017.

  • 7.

    Lynch K. The Image of the City. Vol 11. Cambridge, MAMIT Press; 1960.

  • 8.

    Hollander JB, Purdy A, Wiley A, et al. Seeing the city: using eye-tracking technology to explore cognitive responses to the built environment. J Urban. 2019;12(2):156171.

    • Search Google Scholar
    • Export Citation
  • 9.

    Ewing R, Hamidi S, Grace JB, Wei Y. Does urban sprawl hold down upward mobility? Landsc Urban Plan. 2016;148:8088. doi:10.1016/j.landurbplan.2015.11.012

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 10.

    3M Corporation. How VAS Works. 3M Visual Attention Software (VAS). (2017). http://solutions.3m.com/wps/portal/3M/en_US/VAS_NA/Home/How2/

    • Search Google Scholar
    • Export Citation
  • 11.

    Klein T.M., Drobnik T, Regamey, A. Shedding light on the usability of ecosystem services-based decision support systems: an eye-tracking study linked to the cognitive probing approach. Ecosyst Serv. 2016;19:6586. doi:10.1016/j.ecoser.2016.04.002

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 12.

    Dupont L, Antrop M, Van EV. Eye-tracking analysis in landscape perception research: influence of photograph properties and landscape characteristics. Landsc Res. 2013;39(4):417432. doi:10.1080/01426397.2013.773966

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 13.

    Lucio JV, De Mohamadian M, Ruiz JP, Banayas J, Bernaldez FG. Visual landscape exploration as revealed by eye movement tracking. Landsc Urban Plan. 1996;34(2)135142. doi: doi:10.1016/0169-2046(95)00208-1

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 14.

    Potocka I. The lakescape in the eyes of a tourist. Quaestiones Geographicae. 2013;32(3):8597. doi:10.2478/quageo-2013-0018

  • 15.

    Kiefer P, Giannopoulos I, Raubal M, Duchowski A. Eye tracking for spatial research: cognition, computation, challenges. Spatial Cogn Comput. 2017;17(1–2):119. doi:10.1080/13875868.2016.1254634

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 16.

    Torralba A, Oliva A, Castelhano MS, Henderson JM. Contextual guidance of eye movements and attention in real-world scenes: the role of global features in object search. Psychol Rev. 2006;113(4):766786. PubMed ID: 17014302 doi:10.1037/0033-295X.113.4.766

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 17.

    Ehinger KA, Hidalgo-Sotelo B, Torralba A, Oliva A. Modelling search for people in 900 scenes: a combined source model of eye guidance. Vis Cogn. 2009;17(6–7):945978. PubMed ID: 20011676 doi:10.1080/13506280902834720

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 18.

    Auffrey C, Hildebrandt H. Do motorists see business signs? maybe. maybe not. a study of the probability that motorists view on-premise signs. Interdiscip J Signage Wayfinding. 2017;1:100. doi:10.15763/issn.2470-9670.2017.v1.i2.a8

    • Search Google Scholar
    • Export Citation
  • 19.

    Ahn HS, Kim JT. Study on visual recognition enhancement of yellow carpet placed at near pedestrian crossing areas: visual attention software implementation. J Info Tech Serv. 2016;5(4):7383.

    • Search Google Scholar
    • Export Citation
  • 20.

    Alexander C, Ishikawa S, Silverstein M. A Pattern Language: Towns, Buildings, ConstructionOxford, UKOxford University Press; 1977.

    • Search Google Scholar
    • Export Citation
  • 21.

    Gehl J. Cities for PeopleWashington, DCIsland Press; 2013.

  • 22.

    Sussman A, Hollander JB. Cognitive Architecture: Designing for how We Respond to the Built EnvironmentNew York, NY/London, United KingdomRoutledge; 2014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 23.

    Jennings HS. Behavior of the lower organisms (No. 10)New York, NYColumbia University Press; 1906.

  • 24.

    Doolittle JH. The role of anterior ganglia in phototaxis and thigmotaxis in the earthworm. Psychonom Sci. 1972;27(3):151152. doi:10.3758/BF03328920

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 25.

    Bilbo SD, Day LB, Wilczynski W. Anticholinergic effects in frogs in a Morris water maze analog. Physiol Behav. 2000;69(3):351357. PubMed ID: 10869602 doi:10.1016/S0031-9384(99)00251-6

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 26.

    Greene MJ., Stark SL, Mason RT. Pheromone trailing behavior of the brown tree snake, Boiga irregularis. J Chem Ecol. 2001;27(11):21932201. PubMed ID: 11817075 doi:10.1023/A:1012222719126

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 27.

    Bannerman Susan. Biodiversity and Interior Habitats: The Need to Minimize Edge Effects. Part 6 of 7. Victoria, BC: Ministry of Forests, Research Program; 1998.

    • Search Google Scholar
    • Export Citation
  • 28.

    Nyberg JB, Janz DW, eds. Deer and elk Habitats in Coastal Forests of Southern British Columbia. Special Rep. Ser. No. 5. Victoria, BC: British Columbia Ministry of Forests and Range; 1990.

    • Search Google Scholar
    • Export Citation
  • 29.

    Kallai J, Makany T, Csatho A, et al. Cognitive and affective aspects of thigmotaxis strategy in humans. Behav Neurosci. 2007;121(1):21. PubMed ID: 17324048 doi:10.1037/0735-7044.121.1.21

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • 30.

    LEED v.4. “Neighborhood Development Guide—Built Project Plan.” USGBC. (2019). https://new.usgbc.org/guide/nd

  • 31.

    Nasar JL. Urban design aesthetics: The evaluative qualities of building exteriors. Environ Behav. 1994;26(3):377401. doi:10.1177/001391659402600305

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 32.

    Kaplan R, Kaplan S. Cognition and Environment: Functioning of an Uncertain World. Ann Arbor: Ulrich’s Bookstore; 1983.

  • 33.

    Veleva V. Devens Sustainability Indicator Report 2000–2012: Progress Report. 2012. Accessed August 2019. http://www.devensec.com/sustain/indicators/2012_Sustainability_Progress_Report_Final.pdf

    • Search Google Scholar
    • Export Citation
  • 34.

    Devens Sustainability Indicator Report. 2000. http://www.devensec.com/sustainreport.html. Accessed August 14, 2019.

  • 35.

    Mumford L. The City in History: Its Origins, Its Transformations, and Its Prospects. New York: Harcourt Brace Jovanovich; 1961.

  • 36.

    Dent L, Bunting T. A comparative study of attachment and change in a comprehensively planned vs. Conventionally Developed Post-war Suburb, ProQuest Dissertations and Theses. 2004.

    • Search Google Scholar
    • Export Citation
  • 37.

    Brown BB, Burton JR, Sweaney AL. Neighbors, households, and front porches. New Urbanist community tool or mere nostalgia? Environ Behav. 1998;30(5):579600. doi:10.1177/001391659803000501

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 38.

    Le AT, Payne J, Clarke C, et al. Discomfort from urban scenes: metabolic consequences. Landsc Urban Plan. (2017). 160:6168 doi:10.1016/j.landurbplan.2016.12.003

    • Crossref
    • Search Google Scholar
    • Export Citation
  • 39.

    Moore RJ. Improving Sign Effectiveness with Visual Attention Modeling Software. 2011. http://www.signresearch.org/wp-content/uploads/Improving-Sign-Effectiveness-with-3Ms-Visual-Attention-Modeling-Software.pdf

    • Search Google Scholar
    • Export Citation
  • 40.

    Cottrell DB. Comparing Multiple Methods of Eye Tracking for Packaging [Master’s thesis]. Clemson University. ProQuest Dissertations Publishing; 2016.

    • Search Google Scholar
    • Export Citation
  • 41.

    Carr A. 3M’s Visual Impact Scanner Knows What Your Eyes Want. Fast Company. 2011. https://www.fastcompany.com/1758454/3ms-visual-impact-scanner-knows-what-your-eyes-want. Accessed October 13, 2017.

    • Search Google Scholar
    • Export Citation
  • 42.

    Williams PT. Reduced risk of brain cancer mortality from walking and running. Med Sci Sports Exerc. 2014;46(5):927932. PubMed ID: 24091993 doi:10.1249/MSS.0000000000000176

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 2771 832 38
Full Text Views 289 10 0
PDF Downloads 99 13 0