Comparing methods and data sources for classifying bicycle level of traffic stress: How well do their outcomes agree?

Abstract

Level of Traffic Stress (LTS) metrics are widely used to examine how bicyclists may perceive stress along urban streets and identify opportunities for infrastructure improvements. The intuitiveness of the original method, which condensed 18 input variables into four levels, has made LTS very popular among practitioners. Nonetheless, it can be challenging to collect all required inputs. In response, numerous alternative methods have been developed with fewer or different inputs drawn from more general sources, such as OpenStreetMap (OSM) or GIS datasets from local agencies. These methods tend to use the same four-level schema, suggesting that they are commensurate, though this may be an inappropriate assumption. We examine agreement between seven LTS methods calculated from three data sources throughout two major U.S. cities and find substantial differences between many outcomes. Interestingly, the simplest LTS method and the least precise dataset, OSM, provided the most consistent outcomes. This suggests using simpler albeit less precise approaches to improve commensurability between LTS analyses. For more detailed analyses, we recommend site studies with on-the-ground measurements rather than relying on LTS to characterize subtleties. We also encourage clear labeling of LTS methods and data sources to avoid confusion about how results can be interpreted and compared.