Behavioral Models and Characteristics of Bicycle - Automobile Mixed - Traffic : Planning and Engineering Implications

This report addresses an important need for fundamental understanding of bicycleautomobile mixed-traffic. It presents models of (1) gap acceptance behavior and (2) bicyclist behavior at the onset of a yellow traffic signal indication, in addition to analysis of (3) coordinating traffic signals to provide (simultaneous) progression for both bicycles and automobiles. Fundamental insights into mixed-traffic behavior are derived and applied to selected problems in mixed-traffic engineering and operations. Discrete choice (probit) models are developed for both motorist and cyclist gap acceptance behavior. An important fundamental insight from these models is that both cyclists and motorists (on average) require a longer gap when the gap is closed by a large vehicle (e.g. bus), and both will accept a shorter gap when the gap is closed by a bicycle, relative to a gap closed by a . passenger car. A methodology for determining an adequate clearance interval (normally consisting of part yellow change and part all-red clearance intervals) for bicycles is developed from a deterministic model based on kinematic relations. A probability of stopping model is calibrated from observations of actual bicyclist behavior. It was show to be a useful tool to evaluate clearance intervals, because it reflects actual bicyclist behavior. Fundamental insights into bicyclist behavior at the onset of a yellow signal indication are obtained from both models (e.g. the reasons that bicycles may require longer clearance intervals, relative to automobiles, at sufficiently wide intersections). Finally, a conceptual foundation, consisting of three primary contributions, is developed for analyzing bicycle-automobile mixed-traffic progression along signalized streets. The principal considerations for bicycle progression are articulated. Several concepts and techniques that provide improved (or alternative) multiobjective solutions are presented and analyzed. A multiobjective formulation framework for solving the mixed-traffic design problem is proposed. This framework formally incorporates the elements introduced as part of the first two contributions and provides a way to handle the inherent competing objectives.