master thesis smartphone crash notification drivers ... · to make a commercially attractive...
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Master’sthesisatDepartmentofElectricalEngineering,spring2018Supervisors:StefanCandefjordandLeifSandsjöExaminer:BengtArneSjöqvist
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Development of a smartphone-based automatic crashnotificationanddrivingcharacteristicsrecognitionsystemformotorcycledrivers
BackgroundThe injury statistics for motorcycle drivers show that only in Sweden around 40peoplearekilledeachyear,andover200areseverelyinjured,withstatisticsbeingmuchworseglobally.Severemotorcyclecrashesleadingtodeathandincapacitatinginjuriesdonotdecreaseattherelativelyfastpaceobservedforcarcrashes.Basedonour lineof researchwestandbeforeanopportunity toestablish smartphonesasatool for improving the safety of motorcycle driving. One of our main goals is toevaluatethefeasibilityofusingsmartphonesforimplementinganemergencyalarm,utilizing an algorithm that automatically can detect a crash or incident. Modernsmartphones can measure acceleration (accelerometers), rotation (gyros), speed(GPS)andotherparameters(e.g.magnetometers),whichcanbeusefulforassessingbodymovements in real-time and automatically distinguishnormal driving fromacrash(Figure1).Theconceptisbasedonjalp!–anautomaticemergencyalarmforbicyclists (see http://jalp.se/en ). Furthermore,we are exploring the possibility touseadvancedalgorithms, includingmachine learning, torecognizerelevantdrivingcharacteristics/parameters, such as driving style, road characteristics, curvehandling,etc.
Figure1:Motorcyclecrashesarecommonandoftenhavesevereconsequences.Acrash
canbedetectedbyusingsophisticatedalgorithmstoanalyzebodymovementsmeasuredbythesensorsinmodernsmartphones(pictureusedwithpermission,from
https://www.flickr.com/photos/72334647@N03/11493300164).
IncollaborationwithChalmersSchoolofEntrepreneurshipwearenowattemptingtomakeacommerciallyattractivesmartphone-basedserviceforthemotorcyclecommunity,includingcrashdetectionandadvancedstatisticsandreal-timefeedbackofdrivingcharacteristicsparametersthatcouldberuninreal-timeonsmartphones.Thegoalistocreateastart-upcompanyintheyearof2018.
Master’sthesisatDepartmentofElectricalEngineering,spring2018Supervisors:StefanCandefjordandLeifSandsjöExaminer:BengtArneSjöqvist
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AimTherearethreeprimaryaimsofthisthesis:
1. Toevaluatenaturalisticdatacollectedfrommotorcycletestdrivers,anddatafrom real/simulated crashes, and assess the accuracy of existing crashdetection algorithms adapted to motorcycle, possibly compared to thestudents’owndevelopedalgorithms.
2. To develop algorithms for automatic recognition of drivingcharacteristics/parametersthatareindicatedtobeofcommercialinterestforthe motorcycle community, in collaboration with the team from ChalmersSchoolofEntrepreneurship.
3. To implementand test thealgorithmsdeveloped in the thesis (aim1and2above)inasmartphoneapp(iOSand/orAndroid), incollaborationwiththeteamfromChalmersSchoolofEntrepreneurship.
MaterialsandmethodsDatacollectionisongoingandwillcontinuethroughspringandsummerof2018.Thedataisstoredinacloud-basedserver,andnewdatarecordingsbecomeavailableassoonasfetchedfromthetestdriver´ssmartphones(expectedtobethesamedaythedrivingwasrecorded).Themain tool for analysiswill beMatlab and/or other statistical/computing software thestudent(s) favor.Fordesigning thecrashdetectionand/or thedrivingdetectionalgorithm,tools for pattern recognition such as support vectormachinesmay be used. The resultingalgorithmsshouldbeimplementedinasmartphoneappandcanbeevaluatedinfieldtestsincollaborationwiththeteamfromChalmersSchoolofEntrepreneurship.
InformationYou are welcome to do this work at MedTech West’s facilities at Sahlgrenska UniversityHospital (students should use their own computers if possible). Start date is as soon aspossible.MajorsubjectsEngineeringGroupsize1-2Prerequisites Students who have background and/or interest in traffic safety andmotorcycledriving,machinelearning/signalprocessing/statisticalanalysis,arewelcometoapply. Good programming skills (mainly using Matlab and/or other powerful computingsoftware,andsecondaryprogrammingofsmartphoneappsinAppleiOS/GoogleAndroid)isadvantageous.Supervisors
• StefanCandefjord,PhDBiomedicalEngineering,ChalmersUniversityofTechnology,073-3821537,[email protected]
• Leif Sandsjö, PhDHuman-centered technology, University of Borås, 073-4606633,[email protected]
Examiner• BengtArneSjöqvist,ProfessorofPractice,ChalmersUniversityofTechnology,
070-7877797,[email protected]