Citation

Figliozzi M, Wheeler N, Monsere C. Transp. Res. Rec. 2013; 2387: 66-75.

Copyright

(Copyright © 2013, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.3141/2387-08

PMID

unavailable

Abstract

As cities across North America install infrastructure to accommodate a growing number and variety of bicyclists, installation of bicycle-specific traffic signals is a common design element. A recent survey showed a lack of consistency in design and timing. In particular, minimum green signal timing is highly dependent on the assumed acceleration and speed performance of bicyclists, but no detailed methodology exists to estimate these performance values. Recently, AASHTO, the California Department of Transportation, and the National Association of City Transportation Officials issued documents that required the provision of an adequate clearance interval and recommended that, in the determination of this minimum interval field, an investigation of bicyclist speed be conducted. Even if detailed video trajectories are available, the determination of a value for field speed and acceleration is not trivial, because values of speeds and accelerations are a function of time and individual bicyclist performance. The purpose of the research reported here was to develop and apply a general methodology to estimate bicyclist acceleration and speed for traffic signal timing applications. With the use of physical equations of motion, this research analytically derived expressions that could be used to classify an individual bicyclist's performance as a function of the observed acceleration profile. The analysis indicated that four basic acceleration profiles were possible and that the profiles could be obtained with a parsimonious field data collection method. The methodology was applied successfully to two intersections in Portland, Oregon. A detailed statistical analysis showed that the results were intuitive and that the methodology successfully categorized bicyclist performance variations as a result of topography or demographic characteristics.