dc.contributor.authorAng, Beverley Chu Yi
dc.date.accessioned2016-05-19T02:16:34Z
dc.date.available2016-05-19T02:16:34Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/10356/67655
dc.description.abstractTraffic jams and traffic incidences can be prevalent in big urban cities, with increasing frequencies during peak hours, when there are more cars on the roads. By predicting and directing traffic appropriately, traffic jams and traffic incidences may be averted and reduced. Tracking and predicting traffic is essential in order to establish productive and useful on-demand route guidance. With accurate prediction, forecast of possible traffic jams and incidences will be possible, and thus able to direct drivers away from the affected links and routes. The aim of this project is to explore and analyse basic traffic models and prediction methods and apply them on historical traffic data obtained from the authorities.en_US
dc.format.extent60 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processingen_US
dc.subjectDRNTU::Engineeringen_US
dc.titleQuantifying the effect of road incidents on urban trafficen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorJustin Dauwelsen_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.description.degreeBachelor of Engineeringen_US


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