Transferability & Forecasting of the Pedestrian Index of the Environment (PIE) for Modeling Applications

Abstract

This project focuses on making our measures, models, and methods more transferable to other locations. Specifically, we re-evaluate, compare and test our pedestrian index of the environment (PIE) measure using data resources more commonly available to planning agencies across the country. Next, we test the results of PIE and its input data in models of pedestrian mode choice for stability of estimation results within a region (intraregional) and between regions (interregional). This research is the next logical step in the MoPeD's enhancement and is critical to enabling its utility beyond the Portland region.The results of this project show that population density and pedestrian connectivity had the most consistent and strong relationship to walk mode choice across all of our regions, which echoed the long literature on this topic. However, the other components of the built environment included in PIE had more variability in their ability to explain walk mode choice. Employment density and its subset urban living infrastructure (ULI), intended to capture retail and service access, had less explanatory power and stability in the cities tested. Based upon these findings, we provide several guidelines for the construct of walkability indices, including variables and spatial scales.Our findings raise questions about the relationship between walking and the built environment within a region and thus, the intraregional transferability of one walkability index is suspect. Estimation results suggest that there may be different responses to the built environment in lower-density vs. higher density regimes and that these relationships may be nonlinear. However, smaller sample sizes of travel survey data in high density areas in all of the US cities tested pose limitations to drawing more confident conclusions from these results.The interregional comparisons of PIE and walk mode share between Los Angeles and Portland showed promise for the use of the index in different regions. In these two regions, model results showed a similar walk mode share for the same values of PIE constructed at the block group level. This provides initial support that the PIEbg construct may be transferrable between metropolitan regions, in part, due to population density's prominent role in PIE.

MoPeD meets MITO: a hybrid modeling framework for pedestrian travel demand

“…MoPeD provides the pedestrian modeling framework in this work. MoPeD was initially developed by Clifton et al (2015Clifton et al ( , 2016aClifton et al ( , 2016bClifton et al ( , 2019 and then further enhanced by Zhang et al (2021). The previous work on MoPeD showed that this tool is sensitive to the small-scale variations in local land use and transport development, and it is capable to assess the planning policies on a regional scale (Zhang et al 2021).…”

Assessing pedestrian impacts of future land use and transportation scenarios

“…In this study, we adopt the framework of MoPeD to quantify the impact of land use and transportation policies on walking behavior. MoPeD was described by Clifton et al, (2015Clifton et al, ( , 2016aClifton et al, ( , 2016bClifton et al, ( , 2019. The framework of MoPeD is illustrated in Figure 1.…”

“…In this study, pedestrian route choices were added to this modeling suite using the shortest path algorithm. We enhanced the model performance and made some modifications to the model stages from the version previously described by Clifton et al (2015Clifton et al ( , 2016aClifton et al ( , 2016bClifton et al ( , 2019. These improvements were made to overcome the following limitations:…”

“…• The Pedestrian Index of the Environment called PIE was less transferable to other applications due to the requirement of detailed land-use data at a fine spatial resolution (Clifton et al, 2019). Also, it was challenging to predict changes to the built environment due to its construct.…”

Participation in Shared Mobility: An Analysis of the Influence of Walking and Public Transport Accessibility to Vehicles on Carsharing Membership in Montreal, Canada

“…The form of the cost function and its parameters have a significant impact on the indicator value, mainly for journeys by public and multimodal transport ( 26 ). As the selection of an accessibility indicator largely depends on the purpose, several studies have aimed at assessing the different indicators for different planning purposes ( 27 – 30 ). Yet, these studies have mainly focused on accessibility to destinations such as jobs and local amenities.…”