Chapter
Apr 26, 2012
Estimation of Traffic Flows at Intersections Based on Traffic Assignment and Neural Network Model
Authors: Qin Fang [email protected], Shanhua Wu, and Zhognzhen Yang [email protected]Author Affiliations
Publication: ICCTP 2011: Towards Sustainable Transportation Systems
Abstract
Traffic flows are key parameters for design, channelization, and signal control of the intersection. Thus, it is important to study how to correct the output of the assignment model so it can be used for the intersection design. This paper uses the assigned and observed traffic flows of some intersections as the input/output factors to train the neural network to obtain an intersection traffic forecast model. In order to train the neural network, the number and location of the sampled intersections are determined, and traffic flows in the intersection are collected. Then, the surveyed and assigned data neural network is trained. Finally, the accuracy of the trained model is examined.
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© 2011 American Society of Civil Engineers.
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Published online: Apr 26, 2012
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Guizhou University, Guiyang.E-mail: [email protected]
Shanhua Wu
Dalian Maritime University, Dalian
Dalian Maritime University, Dalian.E-mail: [email protected]
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