Contributions to bicycle-automobile mixed-traffic science: Behavioral models and engineering applications.

摘要

This dissertation addresses an important need for fundamental understanding of bicycle-automobile 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 shown 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.