Spatial distribution of foot traffic in New York City and applications for urban planning

Abstract

Abstract We present a first city-wide foot traffic model for peak travel periods in New York City. The estimated foot-traffic volumes exhibit over 90% correlations with observed counts and around 25% mean absolute percent errors, extending pedestrian volume estimates to all sidewalk, crosswalk and footpath segments city-wide. We explore the model's use as a baseline for targeted infrastructure investments and hazard analysis using two use cases. First, we examine how estimated pedestrian volumes on different streets can inform sidewalk classification and related public expenditure decisions. Second, we explore how fine-grained pedestrian estimates can be used to understand pedestrian crash hotspots and prioritize them for improvements. The model demonstrates policy and planning relevant outputs that can be applied to a range of different decision-support applications. As cities increasingly prioritize sustainable and active transportation modes, pedestrian land-use-mobility interaction models stand to support a transition to safer, more inclusive, and more vibrant city environments.

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