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Existing walking/biking data are often insufficient to support active transportation planning activities. This study used an emerging large-scale human mobility dataset to identify places where there are a higher number of short-distance trips to public places (expressed by a mobility index). Demographic variables were integrated into the mobility index to prioritize access for more people and address equity concerns. In addition, a safety index (reflecting crash injuries/fatalities involving pedestrians/bicyclists) and a connectivity index (reflecting the density of existing active transportation infrastructure) were also considered together with the mobility index in generating an investment potential score. All the indices/scores were mapped at hexagon and segment level on an online dashboard. The developed dashboard is expected to support statewide active transportation planning and project selection/prioritization decision-makings. The proposed methodology is replicable for any places that have few active transportation facilities and where pedestrian/bicyclist count data are not sufficient to model demand directly.
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Bian et al. (2024) studied this question.
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