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,stefan.candefjord@chalmers.se

• Leif Sandsjö, PhDHuman-centered technology, University of Borås, 073-4606633,leif.sandsjo@medtechwest.se

Examiner• BengtArneSjöqvist,ProfessorofPractice,ChalmersUniversityofTechnology,

070-7877797,bengt.arne.sjoqvist@chalmers.se