Destination Prediction with Decision Tree An Intelligent Driver Assistant for Volvo Cars: Destination Prediction, Traffic Notifying and Route Advising

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dc.contributor.authorFeng, Weinan
dc.contributor.departmentChalmers tekniska högskola / Institutionen för data- och informationsteknik (Chalmers)sv
dc.contributor.departmentChalmers University of Technology / Department of Computer Science and Engineering (Chalmers)en
dc.date.accessioned2019-07-03T13:30:51Z
dc.date.available2019-07-03T13:30:51Z
dc.date.issued2014
dc.description.abstractIn this thesis, a destination prediction method based on decision tree model will be presented. The method will be used to support the Volvo Car Intelligent Driver Assistant System. Accurate destination prediction method is useful in many cases, for instances, it helps to free driver's hand of manually inputting destination address, provide traffic jam report before running into traffic jam and recommend the optimal route with the supporting of third parties' services. The mean accuracy of the destination prediction introduced in this thesis can achieve about 75%. By collaborating with the INRIX Traffic API, WirelessCar API and Volvo On Call app, the Intelligent Driver Assistant System achieves the goal to notifying Volvo Car drivers with traffic information and providing possible routes to the predicted destination.
dc.identifier.urihttps://hdl.handle.net/20.500.12380/203066
dc.language.isoeng
dc.setspec.uppsokTechnology
dc.subjectData- och informationsvetenskap
dc.subjectComputer and Information Science
dc.titleDestination Prediction with Decision Tree An Intelligent Driver Assistant for Volvo Cars: Destination Prediction, Traffic Notifying and Route Advising
dc.type.degreeExamensarbete för masterexamensv
dc.type.degreeMaster Thesisen
dc.type.uppsokH
local.programmeComputer science – algorithms, languages and logic (MPALG), MSc
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