Intellitraffic computer vision based hightwa y traffic parameter estimation system

dc.contributor.authorDe Silva, CR
dc.contributor.authorDharmawardana, KATS
dc.contributor.authorRatnayake, ADSE
dc.contributor.authorRodrigo, SAKC
dc.contributor.authorSandeepani, LAA
dc.date.accessioned2013-12-30T15:36:12Z
dc.date.available2013-12-30T15:36:12Z
dc.date.issued2007
dc.description.abstractThe Traffic Control System of a country is a main area that has the potential to affect the development of a country in a very extensive scale. The existing traffic control systems in Sri Lanka, UniRoadl and UniRoad2 are highly dependent on the statistical traffic information gathered from time to time using manual methods(using people etc.) which are more difficult to rely on. The main drawback of all these systems is that they cannot adapt signal timing dynamically according to the situation. A system with the capability of altering signal timing as per real time situations will be more effective and productive. For that it needs a proper traffic parameter estimation system which should offer features like reliability and efficiency to a far beyond the manual methods. This will save time wasted at highway while reducing fuel consumption, noise and air pollution in urban areas. Various parties like Traffic Police, the Road Development Authority and ultimately the whole community will be benefited from such a system. The basis of such a system would be a method for reliably approximating the traffic flow in real time, at a low cost. This research paper discusses how to approximate the traffic flow from video streams and why some of the methods attempted are not suitable for such a system.en_US
dc.identifier.conferenceERU Research for industryen_US
dc.identifier.pgnos112-114en_US
dc.identifier.proceedingProceeding of the 13th annual symposiumen_US
dc.identifier.urihttp://dl.lib.mrt.ac.lk/handle/123/9708
dc.identifier.year2007en_US
dc.language.isoenen_US
dc.titleIntellitraffic computer vision based hightwa y traffic parameter estimation systemen_US
dc.typeConference-Extended-Abstracten_US

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