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9 <br /> <br />Trip Potential Analysis <br />The Trip Potential Analysis guided the development of the Focus Network by identifying areas in Pleasanton with <br />the greatest potential for walking and bicycling trips, and therefore where walking and bicycling investments might <br />produce the greatest systemwide benefit. In contrast to bicycle or pedestrian counts, which only show existing <br />activity and may be biased to where comfortable facilities already exist, the trip potential analysis reveals latent <br />demand. The factors considered in the trip potential analysis are listed in Table 1. <br />Table 1: Trip Potential Factors <br />Factor Description Data Source <br />Population Where people live, measured as population density. US Census ACS 5-Year Estimates, <br />2019-2023 <br />Jobs Where people work, measured as employment density. US Census Longitudinal Employer <br />Housing Dynamics, 2022 <br />Urban Form Where the built environment encourages more walking and <br />bicycling, based on street grid density. <br />Toole Design-generated data <br />Transit Where transit stop density is highest. Rail stations are <br />counted twice, and bus stations are counted once. <br />Caltrans; BART Stations (2021); <br />ACE Stations (2021) <br />Destinations Where daily destinations are located, including parks, <br />grocery stores, libraries, and other popular locations as <br />identified during public engagement. <br />City of Pleasanton; Open Street <br />Map1; Public engagement, 2025 <br />Education Where K-12 schools are located. City of Pleasanton <br />Mobility Where short trips under two miles (i.e., can be converted to <br />walking or bicycling) are most likely. <br />Replica2, Spring 2025 <br /> <br /> <br /> <br />1 OpenStreetMap provides crowdsourced geographic data that often exceeds the detail of governmental sources in urban areas. <br />2 Replica is an activity-based travel demand model that uses big data sources to calculate multimodal travel activity.