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http://nopr.niscair.res.in/handle/123456789/4857
Title: | Modeling vehicle delays at signalized junctions: Artificial neural networks approach |
Authors: | Murat, Y Sazi Baskan, Ozgur |
Keywords: | Artificial neural networks;Intersections;Signalization;Traffic flows;Vehicle delay model |
Issue Date: | Jul-2006 |
Publisher: | CSIR |
Abstract: | Delay of vehicles at signalized junctions is one of the main criteria used for evaluation of control systems’ performances. The vehicle delay is uniform and non-uniform delay types. The uniform part consists of signal timings; the non-uniform part includes vehicle queuing, random arrivals and over-saturation cases of traffic flows. The uniform part of the vehicle delays is basically determined using conventional delay formulas. But for the non-uniform part, artificial neural network (ANN) approach is used and a vehicle delay estimation model [artificial neural network delay estimation of traffic flows (ANNDEsT)] is developed. ANNDEsT model compared with Webster, HCM and Akçelik delay calculation methods and field observations, shows encouraging results especially for the cases of over-saturation or non-uniform conditions. |
Page(s): | 558-564 |
URI: | http://hdl.handle.net/123456789/4857 |
ISSN: | 0975-1084 (Online); 0022-4456 (Print) |
Appears in Collections: | JSIR Vol.65(07) [July 2006] |
Files in This Item:
File | Description | Size | Format | |
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JSIR 65(7) 558-564.pdf | 285.45 kB | Adobe PDF | View/Open |
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