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• 1. [Article] Webinar: Development of a Pedestrian Demand Estimation Tool

  Why model pedestrians? A new predictive tool for estimating pedestrian demand has potential applications for improving walkability. By forecasting the number, location and characteristics of walking trips, ...

  Citation × Citation Citation Abstract Copy Title: Webinar: Development of a Pedestrian Demand Estimation Tool Author: Clifton, Kelly Year: 2016 Why model pedestrians? A new predictive tool for estimating pedestrian demand has potential applications for improving walkability. By forecasting the number, location and characteristics of walking trips, this tool allows for policy-sensitive mode shifts away from automobile travel. There is growing support to improve the quality of the walking environment and make investments to promote pedestrian travel. Despite this interest and need, current forecasting tools, particularly regional travel demand models, often fall short. To address this gap, Oregon Metro and NITC researcher Kelly Clifton worked together to develop this pedestrian demand estimation tool which can allow planners to allocate infrastructure based on pedestrian demand in the Portland, Oregon metropolitan area. The tool is also designed to be replicable, so that other metropolitan areas can adapt the model to begin estimating pedestrian demand in their cities. This webinar will provide an overview of how the tool functions as well as a framework for applying this method in other cities. Title: Webinar: Development of a Pedestrian Demand Estimation Tool Author: Clifton, Kelly Year: 2016 Why model pedestrians? A new predictive tool for estimating pedestrian demand has potential applications for improving walkability. By forecasting the number, location and characteristics of walking trips, this tool allows for policy-sensitive mode shifts away from automobile travel. There is growing support to improve the quality of the walking environment and make investments to promote pedestrian travel. Despite this interest and need, current forecasting tools, particularly regional travel demand models, often fall short. To address this gap, Oregon Metro and NITC researcher Kelly Clifton worked together to develop this pedestrian demand estimation tool which can allow planners to allocate infrastructure based on pedestrian demand in the Portland, Oregon metropolitan area. The tool is also designed to be replicable, so that other metropolitan areas can adapt the model to begin estimating pedestrian demand in their cities. This webinar will provide an overview of how the tool functions as well as a framework for applying this method in other cities. Close

• 2. [Article] How to Estimate Pedestrian Demand

  There is growing support to improve the quality of the walking environment and make investments to promote pedestrian travel. Such efforts often require analytical non-motorized planning tools to estimate ...

  Citation × Citation Citation Abstract Copy Title: How to Estimate Pedestrian Demand Author: Clifton, Kelly, Singleton, Patrick Allen, Muhs, Christopher D., Schneider, Robert J. Year: 2015 There is growing support to improve the quality of the walking environment and make investments to promote pedestrian travel. Such efforts often require analytical non-motorized planning tools to estimate levels of pedestrian demand that are sensitive to environmental and demographic factors at an appropriate scale. Despite this interest and need, current forecasting tools, particularly regional travel demand models, often fall short. To address this gap, Oregon Metro and NITC researcher Kelly Clifton worked together to develop a pedestrian demand estimation tool. For generations, planners have been using statistical models to forecast travel demand, but these models have traditionally been auto-centered. The new tool will allow planners to allocate infrastructure based on pedestrian demand in the Portland, Oregon metropolitan area. The tool is also designed to be replicable, so that other metropolitan areas can adapt the model to begin estimating pedestrian demand in their cities. Title: How to Estimate Pedestrian Demand Author: Clifton, Kelly, Singleton, Patrick Allen, Muhs, Christopher D., Schneider, Robert J. Year: 2015 There is growing support to improve the quality of the walking environment and make investments to promote pedestrian travel. Such efforts often require analytical non-motorized planning tools to estimate levels of pedestrian demand that are sensitive to environmental and demographic factors at an appropriate scale. Despite this interest and need, current forecasting tools, particularly regional travel demand models, often fall short. To address this gap, Oregon Metro and NITC researcher Kelly Clifton worked together to develop a pedestrian demand estimation tool. For generations, planners have been using statistical models to forecast travel demand, but these models have traditionally been auto-centered. The new tool will allow planners to allocate infrastructure based on pedestrian demand in the Portland, Oregon metropolitan area. The tool is also designed to be replicable, so that other metropolitan areas can adapt the model to begin estimating pedestrian demand in their cities. Close

• 3. [Article] Development of a Pedestrian Demand Estimation Tool

  Most research on walking behavior has focused on mode choice or walk-trip frequency. In contrast, this study is one of the first to analyze the destination choice behaviors of pedestrians. Using about ...

  Citation × Citation Citation Abstract Copy Title: Development of a Pedestrian Demand Estimation Tool Author: Clifton, Kelly, Singleton, Patrick Allen, Muhs, Christopher D., Schneider, Robert J. Year: 2015 Most research on walking behavior has focused on mode choice or walk-trip frequency. In contrast, this study is one of the first to analyze the destination choice behaviors of pedestrians. Using about 4,500 walk trips from a 2011 household travel survey in the Portland, OR, region, we estimated multinomial logit pedestrian destination choice models for six trip purposes. Independent variables included terms for impedance (walk-trip distance); size (employment by type, households); supportive pedestrian environments (parks, a pedestrian index of the environment variable called PIE); barriers to walking (terrain, industrial-type employment); and traveler characteristics. Unique to this study was the use of small-scale destination zone alternatives. Distance was a significant deterrent to pedestrian destination choice, and people in carless or childless households were less sensitive to distance for some purposes. Employment (especially retail) was a strong attractor: doubling the number of jobs nearly doubled the odds of choosing a destination for home-based shopping walk trips. More attractive pedestrian environments were also positively associated with pedestrian destination choice after controlling for other factors. These results shed light on determinants of pedestrian destination choice behavior, and sensitivities in the models highlight potential policy-levers to increase walking activity. In addition, the destination choice models can be used in regional travel demand models or as pedestrian planning tools to evaluate land use and transportation policy and investment scenarios. Title: Development of a Pedestrian Demand Estimation Tool Author: Clifton, Kelly, Singleton, Patrick Allen, Muhs, Christopher D., Schneider, Robert J. Year: 2015 Most research on walking behavior has focused on mode choice or walk-trip frequency. In contrast, this study is one of the first to analyze the destination choice behaviors of pedestrians. Using about 4,500 walk trips from a 2011 household travel survey in the Portland, OR, region, we estimated multinomial logit pedestrian destination choice models for six trip purposes. Independent variables included terms for impedance (walk-trip distance); size (employment by type, households); supportive pedestrian environments (parks, a pedestrian index of the environment variable called PIE); barriers to walking (terrain, industrial-type employment); and traveler characteristics. Unique to this study was the use of small-scale destination zone alternatives. Distance was a significant deterrent to pedestrian destination choice, and people in carless or childless households were less sensitive to distance for some purposes. Employment (especially retail) was a strong attractor: doubling the number of jobs nearly doubled the odds of choosing a destination for home-based shopping walk trips. More attractive pedestrian environments were also positively associated with pedestrian destination choice after controlling for other factors. These results shed light on determinants of pedestrian destination choice behavior, and sensitivities in the models highlight potential policy-levers to increase walking activity. In addition, the destination choice models can be used in regional travel demand models or as pedestrian planning tools to evaluate land use and transportation policy and investment scenarios. Close