12.2.20-Mobility-Andres-Sevtsuk

Conference Video|Duration: 65:49
December 2, 2020
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    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 practitioners still lack methods and tools for predicting how development proposals could impact pedestrian activity on specific streets or public spaces at different times of the day. Cities typically require traffic impact assessments, but not pedestrian impact assessments. In this presentation I discuss a methodology for estimating pedestrian trip generation and distribution between detailed origins and destinations in both existing and planned built environments. I demonstrate its application in Cambridge, MA and Melbourne, Australia, where I compare estimated foot-traffic during lunch and evening peak periods to observed pedestrian counts and show how the model can be used to predict changes in foot-traffic that results from changes in real-estate development.
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  • Video details
    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 practitioners still lack methods and tools for predicting how development proposals could impact pedestrian activity on specific streets or public spaces at different times of the day. Cities typically require traffic impact assessments, but not pedestrian impact assessments. In this presentation I discuss a methodology for estimating pedestrian trip generation and distribution between detailed origins and destinations in both existing and planned built environments. I demonstrate its application in Cambridge, MA and Melbourne, Australia, where I compare estimated foot-traffic during lunch and evening peak periods to observed pedestrian counts and show how the model can be used to predict changes in foot-traffic that results from changes in real-estate development.
Locked Interactive transcript