Logit-Based Merging Behavior Model for Uncontrolled Intersections in China
Publication: Journal of Transportation Engineering
Volume 140, Issue 12
Abstract
It has been previously documented that under the condition of crossing an uncontrolled intersection, the decision-making process of drivers is rather complex and highly interactive: they need to decide about the timing, direction, and strategy to complete the required maneuver to avoid potential conflicts. Given the significant impact of this behavior on intersection safety and capacity, we model the merging behavior of a straight-moving vehicle facing a turning vehicle at an uncontrolled intersection in China. We expect that this model can predict the probability that a straight-moving driver has a preemptive status (i.e., arrive at the merging point before the turning vehicle). The factors which determine the drivers’ decision behavior are analyzed, and then we propose a logistic regression model using a dataset collected from an uncontrolled intersection in Kunming, China. Our model reveals that the speed difference, the distance between the two vehicles, and the distance of the turning vehicle to the merging point are the major determinants of a straight-moving driver’s decision. In addition, the prediction results from our model are compared with real-world observations, and better validate the decision behavior model in China.
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Acknowledgments
This work was supported by the National Basic Research Program of China (Grant No. 2012CB725404) and the Training Scheme for Excellent Researcher in Beijing “Intersection vehicle motion micro-behavior model and simulation.”
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© 2014 American Society of Civil Engineers.
History
Received: Aug 14, 2012
Accepted: May 14, 2014
Published online: Jul 10, 2014
Published in print: Dec 1, 2014
Discussion open until: Dec 10, 2014
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