Estimating Pedestrian Flows on Street Networks
Name
Estimating Pedestrian Flows on Street Networks.pdf
Description
Published version
Size
2.47 MB
Format
Adobe PDF
Checksum (MD5)
54e09cda518211fe95e34b87c95a0bc7
Author(s)
Sevtsuk, Andres
Date Issued
October 2, 2021
Journal
Journal of the American Planning Association
Publisher
Taylor & Francis
Citation
Sevtsuk, A. (2021). Estimating Pedestrian Flows on Street Networks: Revisiting the Betweenness Index. Journal of the American Planning Association, 87(4), 512–526.
Version
Final published version
Abstract
City governments and planners alike commonly seek to increase pedestrian activity on city streets as part of broader sustainability, community building, and economic development strategies. Though walkability has received ample attention in planning literature, most planners still lack practical methods for predicting how development proposals could affect pedestrian activity on specific streets or public spaces at different times of the day. Cities typically require traffic impact assessments (TIAs) but not pedestrian impact assessments. In this study I present a methodology for estimating pedestrian trip generation and distribution between detailed origins and destinations in both existing and proposed built environments. Using the betweenness index from network analysis, I introduce a number of methodological improvements that allow the index to model pedestrian trips with parameters and constraints to account for pedestrian behavior in different settings. I demonstrate its application in the Kendall Square area of Cambridge (MA), where estimated foot traffic is compared during lunch and evening peak periods with observed pedestrian counts. The proposed approach can be particularly useful for TIAs, neighborhood plans, and large-scale development projects, where pedestrian flow estimates can be used to guide pedestrian infrastructure and safety improvements and public space investments or for locating pedestrian priority streets during the COVID-19 pandemic.
MIT Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivatives
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1080/01944363.2020.1864758
