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An integrated incident detection methodology with gps-equipped vehicles
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index.pdf
Date
2007
Author
Demiroluk, Sami
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Recurrent congestion in urban traffic networks, especially on arterials, is a growing problem. Non-recurrent congestion, mainly due to incidents, only aggravates the problem. Any solution requires monitoring of the network, for which many developing countries, such as Turkey, do not have the traditional surveillance systems on arterials mainly due to high costs. An alternative solution is the utilization of Global Positioning System (GPS) technology, which is increasingly used in traffic monitoring. It is easy and cheap to obtain the GPS track information,even in real-time, from a probe-vehicle or a fleet of vehicles; and spatial variation of speed and travel time of the vehicle(s) in a network can be determined. GPS-based data, especially with only one probe-vehicle, would not provide information on the concurrent states of upstream and downstream traffic, needed to define the state of traffic in a network. To overcome this obstacle, a methodology based on statistical analysis of archival traffic conditions obtained through different sources is proposed to analyze traffic fluctuations and identify daily traffic pattern. As a result, bottleneck and resulting queues can be detected on a corridor. Thus, it enables detection of recurrent congestion and queues that may result from incidents. The proposed methodology is tested on a corridor the roadway between METU and Kızılay of İnönü Boulevard. The results show that the methodology can effectively identify bottleneck locations on the corridor and also an incident observed during the data collection is detected correctly by the proposed algorithm.
Subject Keywords
Traffic Engineering.
,
Structural Engineering (General)
URI
http://etd.lib.metu.edu.tr/upload/3/12608653/index.pdf
https://hdl.handle.net/11511/17027
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Graduate School of Natural and Applied Sciences, Thesis
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S. Demiroluk, “An integrated incident detection methodology with gps-equipped vehicles,” M.S. - Master of Science, Middle East Technical University, 2007.