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PhDPROJECTSPECIFICATIONYear2013-2016Studentname:XXXContacttelephonenumber:XXXProjectTitleassubmitted:SmartMobilityProfilingandGamificationBackgroundandMotivationInmanycountries,theproportionofurbanpopulationhasincreasedinrecentdecades.Forinstance,China’stotalurbanpopulationiscurrentlyjustoverahalfofitstotalpopulation,risingfrom26%in1990.Thismirrorsatrendinmostotherdevelopedcountries.Urbanization[1],regardedasastrategyforacceleratingdevelopmentbysomecitygovernors,hasalsoresultedinmanychallengestourbanpublicservices.Oneofthemainurbanpublicservicesistransportation,whichisinpartgovernedbystrategictransportpoliciesintermsofbothsustainability(CO2,airpollution)andcompetitiveness(congestion)andbyincentives(e.g.,cheaperoff-peakprivatetransporttravel).Akeychallengetoallmajorcitiesishowtoconfiguretraveldemandmanagement(TDM),oftenreferredtoasmobilitymanagementpoliciesandincentivestoreducecongestion,accidentsandpollution.Smartertransportationprofilingbothatanindividualleveltoinformtheindividualandata(spatial-temporal)group/publicleveltoinformauthorities,canleadtobeneficialshiftsinmobilitytohelpaddressthesechallenges.TDMincludesanypolicytoencouragebetterwaystousetransportresource,forinstancebyofferingpeopleincentivestoreducetheircaruse.TheuseofGamificationisinvestigatedtosetincentivesandimprovetheengagementoftarget-specificappusers[2].Gamificationistheuseofgametheoryandgamedesigntechniquesinnon-gamecontexts,inthiscaseinurbantravel,inordertoencouragepeopletoadopt,ortoinfluencehowtheyusetransportation.Anexampleofanurbantravelgameconsistoftravelersbeingawardeddifferentlevelsofpointsforuseofdifferenttravelmodes.PROJECT(RESEARCH)AIMSThemainobjectiveofthisprojectistousebothsmartmobilityprofilingandgamificationofurbantraveltoresearchanddevelop(R&D)bettermodelsofindividualandaggregatedurbanmobilityinordertobetterunderstandandaidshiftsinmobilitytomeetstrategicTDMgoals.InordertoachievethisoverallR&Dobjective,threespecificsub-objectivesandmethodsareplanned:First,toR&Dtwoappstoacquiremobilitydatafrombothmobilesensors(e.g.,phones)andfixedinfrastructure(e.g.,trafficsensors)intwocitiesBeijingandLondon;Second,togenerateindividualmobilityprofilesandtodatamineaggregatesofmobilitydatatomodelmobilitypatterns;Third,tocorrelatethemobilitypatternsofactualsenseddatacombinedwithgamificationsimulationsofurbanmobilitytoevaluatetheeffectofwhat-ifscenariosofdifferenttransportationpoliciesandincentives.NOVELTYThenoveltyforthisstudyismainlyreflectedbytheexploitationofbothsmartmobilityprofilingandgamification.Nowadays,almostallpeoplehaveoneormoremobiledevicessuchassmartphones,whichgiveusafacilityfordevelopingsomemobileapplicationstocollectmobilitydatafrommobiledevices.Makingfulluseofindividualmobiledevicesandexistingfixedinfrastructureisquiteimportantintermsofthecostefficiencyofdeploymentandmaintenance.However,theproliferationofmostmobileapplicationsreliesontheusers’engagement.Gamificationcanbeappliedtotheappstomotivatemorepeopletouseandkeepthem.METHODOLOGYThemethodologyforthestudyinvolvesmobilitydatacollection,mobilityprofiling,dataminingandmodeling,gamification.Consideringitsgoodcross-platformabilityandportability,wewilluseJavalanguagetodeveloptwoapps:OnerunsonAndroid(orothermobileplatforms)smartphonestocollectmobilitydatafrommobileusers,withsomegamemotivationstrategiestoencourageuserstrytouseitandkeepit;AnotherrunsonaPCorlaptoptocollectdatafromfixedinfrastructureandtoconductsomenecessarydataprocessing.Afteracquiringmobilitydatarequired,methods(e.g.mobilitypathconstruction,topologyconstruction,patterndiscovery)describedin[3]willbeusedtogenerateindividualmobilityprofiles.Accordingto[3],thereareseveralalgorithmsforthepatternminingsuchasGSP,SPADE,AprioriAll.Itisrecommendedtocontaintime-contextinformationwhenrepresentingmobilityprofiles.Gamificationmethodologyisusedtosetincentivesandimprovetheengagementoftarget-specificappusersinthisresearch.Gamificationgenerallyusesixstrategies[4]:scores,levels,challenges,leaderboards,achievementsandrewards.Forthisstudy,thesestrategiescanbeusednotonlytocollectmobilitydata,butalsotoencouragepeopletoadopt,ortoinfluencehowtheyusetransportation.EXPECTEDOUTCOMESTheexpectedoutcomesforthisstudyasfollows:Twoapps,whichsupportcommoncommunicationtechniques(e.g.,cellularnetworks,bluetooth,WiFi)tosendandreceivemobilitydatarequired.Theappusedtocollecttomobilitydatafrommobileuserswillintegratesomegametechniquestoimprovetheengagementofusersandcandeterminethelocationofusersandenableuserstoreportsomeevents(e.g.,accident)onlybytakingaphotoorothersimpleoperations.Amobilityprofilingframework.Accordingtodatacollected,mobilityprofilescanbeacquiredbyusingthisframework.Thismeansthattheframeworkwillimplementfunctionsnecessarysuchasmobilitypathsconstruction,topologyconstruction,patterndiscovery.Anevaluationreport.Accordingtotheevaluationresultabouttheeffectofwhat-ifscenariosofdifferenttransportationpoliciesandincentives,suggestionswillbegiventoaidtrafficdepartmentstomakepoliciesthatencouragepeopleusetransportresourcemoreefficientandenvironmental-