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Development and application of the Pedestrian Environment Index (PEI)

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  • Peiravian, Farideddin
  • Derrible, Sybil
  • Ijaz, Farukh

Abstract

The objective of this work is to develop a new and easily computable measure of pedestrian friendliness for urban neighborhoods that makes the best use of the available data and also addresses the issues concerning other models in use. The Pedestrian Environment Index (PEI) is defined as the product of four components representing land-use diversity (based on the concept of entropy), population density, commercial density, and intersection density. The final PEI is bound between 0 and 1, and uses data that typically are readily available to planners and metropolitan planning organizations (MPO). The results of this method are region-specific; they are comparable only between the zones within the given study area. As a case study, the city of Chicago is analyzed at the sub-traffic analysis zone (sub-TAZ) level. The results agree closely with the expectation of pedestrian friendliness across different parts of the city. Possible extensions are also listed, including a further study to determine statistical relationships between the PEI and common socio-economic characteristics. The method could also be further improved should more types of data become available.

Suggested Citation

  • Peiravian, Farideddin & Derrible, Sybil & Ijaz, Farukh, 2014. "Development and application of the Pedestrian Environment Index (PEI)," Journal of Transport Geography, Elsevier, vol. 39(C), pages 73-84.
  • Handle: RePEc:eee:jotrge:v:39:y:2014:i:c:p:73-84
    DOI: 10.1016/j.jtrangeo.2014.06.020
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    13. Tilahun, Nebiyou & Thakuriah, Piyushimita (Vonu) & Li, Moyin & Keita, Yaye, 2016. "Transit use and the work commute: Analyzing the role of last mile issues," Journal of Transport Geography, Elsevier, vol. 54(C), pages 359-368.
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    17. Clifton, Kelly J. & Singleton, Patrick A. & Muhs, Christopher D. & Schneider, Robert J., 2016. "Representing pedestrian activity in travel demand models: Framework and application," Journal of Transport Geography, Elsevier, vol. 52(C), pages 111-122.
    18. Pablo Sáinz-Ruiz & José Ramón Martínez-Riera, 2022. "Community Assets for Health Model and Assessment Scale: A Delphi-Based Analysis and Expert Validation," IJERPH, MDPI, vol. 19(21), pages 1-19, October.
    19. Seung-Nam Kim & Juwon Chung & Junseung Lee, 2022. "Exploring the Role of Transit Ridership as a Proxy for Regional Centrality in Moderating the Relationship between the 3Ds and Street-Level Pedestrian Volume: Evidence from Seoul, Korea," Land, MDPI, vol. 11(10), pages 1-22, October.
    20. Xiaodong Xu & Xinhan Xu & Peng Guan & Yu Ren & Wei Wang & Ning Xu, 2018. "The Cause and Evolution of Urban Street Vitality under the Time Dimension: Nine Cases of Streets in Nanjing City, China," Sustainability, MDPI, vol. 10(8), pages 1-19, August.
    21. Ismaïl Saadi & Roger Aganze & Mehdi Moeinaddini & Zohreh Asadi-Shekari & Mario Cools, 2021. "A Participatory Assessment of Perceived Neighbourhood Walkability in a Small Urban Environment," Sustainability, MDPI, vol. 14(1), pages 1-16, December.
    22. Fancello, Giovanna & Congiu, Tanja & Tsoukiàs, Alexis, 2020. "Mapping walkability. A subjective value theory approach," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    23. Eun Jung Kim & Jiyeong Kim & Hyunjung Kim, 2020. "Does Environmental Walkability Matter? The Role of Walkable Environment in Active Commuting," IJERPH, MDPI, vol. 17(4), pages 1-17, February.
    24. Choobchian, Pooria & Mohammadi, Ali & Zou, Bo & Hair, Joseph F. & Valinejad, Mahsa & Shin, Jaeyong & Sriraj, P.S., 2024. "Calibrating walkability indicators for commute walk trips: A structural equation modeling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).

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