Analysis of Roundabout Drivers’ Gap-acceptance Behavior Using A Drone-based Measurement Technique
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Wei, Anqi
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Abstract
Collecting real-world transportation operational data from existing facilities is crucial, as this data is often necessary for facility performance evaluation, aiding practitioners in making more informed decisions in transportation management and planning design. Among the wide variety of available technologies for data collection, aerial survey methods offer numerous advantages over others in terms of data collection efficiency, flexibility, and safety. More importantly, these methods provide an unrestricted top-down view of survey sites that can largely eliminate image distortion issues. However, in the past, the lack of accessible equipment and professional operators led most previous research studies to choose ground-based methods like fixed cameras for data collection activities. Nowadays, with the increasing availability of inexpensive high-resolution video drones and advancements in image/video processing techniques, the aerial survey method is expected to have immense application potential in traffic surveillance and operational analysis. This research aims to develop a drone-based measurement technique that combines drone video data collection with image processing tools. This technique can also be easily incorporated with other measuring equipment/software and customized based on users’ data collection interests. A set of standard operating procedures and training material were also created to ensure the reliable production of quantitative measurements of traffic conditions for various purposes.
To demonstrate one potential application of the developed drone-based measurement technique, a case study was conducted to analyze entering drivers’ gap-acceptance behavior under general operational conditions at roundabouts. Since in modern roundabouts, priority is always given to circulating vehicles, entering drivers are often faced with the decision to either accept or reject a gap in the circulating stream as they arrive at the approach yield line. These gap acceptance/rejection decisions can vary significantly among drivers. A commonly used parameter to characterize these decisions is the “critical gap”, defined as the minimum gap in the conflicting flow accepted by almost all drivers and serves as an input into most roundabout entry capacity models. Current practice for estimating the critical gap requires the operational data to be collected under saturated conditions when there is a constant queue. However, as most roundabouts rarely operate near capacity, this requirement significantly restricts measurement of gap acceptance under a variety of conditions. Therefore, this case study establishes a framework to obtain reliable and accurate measurements of drivers’ critical gaps under a wide range of operational conditions using the developed drone-based measurement technique.
In this study, a DJI quadcopter drone equipped with a 4k-camera was used collect aerial video recordings of traffic operations at 24 selected roundabouts in Georgia. From these videos, vehicle trajectory data were automatically extracted and analyzed to establish entering drivers’ gap-acceptance behavior. External factors related to geometric design and operation were also measured using the drone-based technique. A predictive model for roundabout drivers’ critical gap estimation was developed at an approach level to help identify significant factors that influence field-observed gap-acceptance behavior, and provide insights into future intersection design decisions. Since many approaches have seen a substantial number of drivers with inconsistent gap-acceptance behavior, to better understand each driver’s gap-acceptance decision-making process under unsaturated conditions, additional variables related to vehicle dynamics like circulating vehicles’ lateral positions within the travel lanes, turning angle rate of change, etc. that might provide certain visual indications to entering drivers were also collected. Upon further investigation of these variables’ impacts on entering drivers’ gap-acceptance decisions, it was found that entering drivers tend to exhibit more cautious behavior when they are uncertain of the incoming circulating vehicle’s intentions in terms of whether to exit at the approach or continue to circulate through the roundabout. This case study also demonstrates the extent to which vehicle trajectories extracted from drone-based video data can be used to obtain valuable information regarding driver behavior, driving environment, and roadway geometric characteristics, etc., and to further refine our understanding of operations observed in transportation facilities.
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Date
2024-05-17
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Text
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Dissertation