USDOT Grant 69A3551747109Caltrans 65A0674Intersection counts are ubiquitous in transportation planning practice and research. They are frequently normalized by area to calculate intersection density, the most common measure of compact street network design in planning practice. However, due to the nature of typical street network data (centerlines) and the typical tools used to count intersections (desktop geographic information systems [GIS]), traditional methods of counting intersections can significantly overcount them. This project addresses this long-standing problem of intersection count bias. First, it develops and distributes an algorithm to automatically and correctly calculate intersection counts and densities anywhere in the world, using a novel topological consolidation method. Second, it conducts a worldwide empirical assessment of traditional intersection counting methods\u2019 bias to quantify the importance of measurement bias and to validate our algorithm. Third, it assesses this bias\u2019s impact on resilience simulations\u2019 results and identifies the street network design characteristics that are most related to resilience. In transportation planning, innumerable downstream models and measures \u2014 from energy efficiency certification schemes to resilience simulations \u2014 rely on intersection counts as input data. A full accounting of input data bias and better methods to overcome misrepresentations of intersections are necessary for data-driven, evidence-based planning for sustainable transportation networks that support active and resilient travel
