Abstract

This paper evaluates the potential impacts of various geometric and operational parameters on gap-acceptance behavior for approaches to roundabouts in the metropolitan area of Atlanta, Georgia. Twelve roundabouts were selected to provide a range of different conditions such as number of legs, number of circulating lanes, conflicting volumes, presence of pedestrian crossings, and so forth. Observational data were collected at these roundabouts using a remotely operated drone equipped with a stabilized high-resolution (4K) video camera operating at a sufficient altitude (just less than 400 ft/120 m) to encompass the complete facility within a single frame. The resulting videos were processed using commercial machine vision analysis supplemented by additional computer-assisted analysis to determine vehicle trajectories, spacings, and potential conflicts on a frame-by-frame (0.033 s) basis. These data, in turn, were used to establish gap-acceptance behavior of each roundabout approach and, through the use of logistic regression on the data, to establish observed critical headways (defined as the logistic inflection point [ t50]). The variability of observed headways was compared against known parameters of both the roundabout and of the specific approach to develop a descriptive/predictive model as to how critical headways and gap-acceptance behavior were affected by variations in these parameters. Several factors were observed to have significant impacts on critical headways, including geometric (size category of the roundabout, number of legs, and visual angle to the upstream approach), environmental (presence of a state route on the upstream approach, presence of additional conflicting lanes, presence of a pedestrian crosswalk on the approach), and operational (approach speeds) factors.

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