Evaluating Alternative Measures of Bicycling Level of Traffic Stress Using Crowdsourced Route Satisfaction Data

Approaches for evaluating the quality of bicycling have become increasingly important for planning bicycle infrastructure improvements. Mekuria, Furth, and Nixon’s (2012) “Level of Traffic Stress” (LTS) approach, which requires minimal data inputs and produces a simple and intuitive output, has emerged as a widely-used framework for identifying streets that are “low-stress” for cyclists. The LTS framework is based on a hierarchy of characteristics, largely related to traffic speed and roadway layout, that are presumed to cause higher or lower levels of stress. Despite the apparent simplicity of LTS, several key challenges emerge from its application. Firstly, multiple LTS classification methods have been developed, and it is difficult to know whether they represent stress in equivalent ways. Secondly, LTS is intended only to define an ordinal scale of stressfulness, but has often been misinterpreted as defining a continuous scale; there is no intended implication that the stress levels are spaced equally. Third, while LTS provides a useful summary of diverse infrastructural variables, it is poorly understood which of these variables are most strongly associated with cyclist satisfaction and may, therefore, be most important to capture in an LTS framework.