There have been important advances in non-motorized planning tools in recent years, including the development of the MoPeD pedestrian demand model (Clifton et al., 2013, 2015). This tool and others are increasingly requested by governments and agencies seeking to increase walking activity and create more walkable places. To date, the MoPeD tool has been piloted with success in the Portland region using data unique to Metro, the metropolitan planning organization. However, there is increasing interest from planning agencies in adapting the pedestrian modeling tools and their inputs for use in their own jurisdictions. Unfortunately, other regions often do not have uniform access to the same kinds of pedestrian environment data as Metro, particularly at such a fine-grained scale.
In this next phase of our pedestrian modeling work (see Clifton et al., 2013, 2015), this project focuses on making our measures, models, and methods more transferable to other locations. Specifically, we will 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.
In terms of index inputs, 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.