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e‐BikeSAFE: A Naturalistic Cycling Study to Understand how Electrical Bicycles Change Cycling Behaviour and Influence Safety

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Safety is a concern jeopardizing cycling sustainability. In Europe, more than 2.000 cyclists die every year in traffic accidents. Electrical bicycles amplify this concern because of their high speed and increasing prevalence. Previous studies, such as the naturalistic cycling study BikeSAFER, showed that interaction among cyclists and other road users (e.g., drivers, pedes‐ trians or other bicyclists) is crucial to cycling safety. As electrical bicycles become increasingly popular, other road users may need to recalibrate their expectations to maintain a safe inter‐ action with this new type of bicycle. However, the extent to which electrical bicycles fail to meet other road users' expectations because of their higher speed is yet to be confirmed. Fur‐ thermore, whether the growing number of electrical bicycles influences cycling behaviour and results in new safety challenges is still unknown. The e‐BikeSAFE project is currently collecting naturalistic cycling data in Gothenburg. Equipped bicycles in e‐BikeSAFE presently record cyclist behaviour in real traffic from a camera GPS, and kinematics sensors. This data will be used to 1) understand how bicyclists with electrical bicy‐ cles behave in traffic and 2) the extent to which safety critical situations (crash and near‐ crashes) are different for electrical bicycles compared to traditional ones. For this later analy‐ sis, data from BikeSAFE will be used as a reference. This paper explains how the naturalistic methodology was adapted to the electrical bicycles and shows how e‐BikeSAFE data will be combined with existing data from BikeSAFE for safety analyses including cycling behaviour and accident causation.
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Proceedings,InternationalCyclingSafetyConference2013
2021November2013,Helmond,TheNetherlands
ABSTRACT
Safetyisaconcernjeopardizingcyclingsustainability.InEurope,morethan2.000cyclistsdie
everyyearintrafficaccidents.Electricalbicyclesamplifythisconcernbecauseoftheirhigh
speedandincreasingprevalence.Previousstudies,suchasthenaturalisticcyclingstudy
BikeSAFER,showedthatinteractionamongcyclistsandotherroadusers(e.g.,drivers,pedes
triansorotherbicyclists)iscrucialtocyclingsafety.Aselectricalbicyclesbecomeincreasingly
popular,otherroadusersmayneedtorecalibratetheirexpectationstomaintainasafeinter
actionwiththisnewtypeofbicycle.However,theextenttowhichelectricalbicyclesfailto
meetotherroadusers’expectationsbecauseoftheirhigherspeedisyettobeconfirmed.Fur
thermore,whetherthegrowingnumberofelectricalbicyclesinfluencescyclingbehaviourand
resultsinnewsafetychallengesisstillunknown.
TheeBikeSAFEprojectiscurrentlycollectingnaturalisticcyclingdatainGothenburg.Equipped
bicyclesineBikeSAFEpresentlyrecordcyclistbehaviourinrealtrafficfromacameraGPS,and
kinematicssensors.Thisdatawillbeusedto1)understandhowbicyclistswithelectricalbicy
clesbehaveintrafficand2)theextenttowhichsafetycriticalsituations(crashandnear
crashes)aredifferentforelectricalbicyclescomparedtotraditionalones.Forthislateranaly
sis,datafromBikeSAFEwillbeusedasareference.Thispaperexplainshowthenaturalistic
methodologywasadaptedtotheelectricalbicyclesandshowshoweBikeSAFEdatawillbe
combinedwithexistingdatafromBikeSAFEforsafetyanalysesincludingcyclingbehaviourand
accidentcausation.
Keywords:trafficsafety,roaduserbehaviour,naturalisticdata,bicycledynamics.

1INTRODUCTION
RenewedinterestforcyclingiscurrentlyraisingimportantsafetyquestionsinseveralEurope
ancountries,suchastheNetherlands,Germany,Denmark,andSweden.Inaddition,theintro
ductionofnewbicycles,poweredbyanelectricalmotorwiththeabilitytomaintaina25km/h
speedindependentlyfromtheweatherandroadgeometry,changescyclingdynamicsandin
fluencestheinteractionbetweencyclistsandotherroadusers.Nevertheless,cyclingisavery
appealingactivitypromotedinnumerousEuropeancitiessuchasGothenburg[1]asitde
creasescongestionandpollution,whileincreasinghealth[2].
ThenumberofelectricalbicyclesisrapidlyrisinginEurope.IncountriessuchasAustriaand
Germanysalesofelectricalbicycles(pedalecandSpedalec)havedoubledfrom2010to2012,
whileinSwitzerlandsalesincreasedby50%andinItalyandFranceby20%.Furthermore,ac
cordingtoEurostat,in2012theimportofelectricalbicyclestotalled180.000unitsandcon
tributedtoaEuropeanmarketofapproximately1.2millionunits.Theincreasingnumberof
electricalbicyclesontheroadenablesalargernumberofcycliststorideforlongerstretchesof
road,andthusgreatlyincreasesexposuretobicycleaccidents.
eBikeSAFE:ANaturalisticCyclingStudytoUnderstandhowElectrical
BicyclesChangeCyclingBehaviourandInfluenceSafety.
M.Dozza1,J.Werneke1,M.Mackenzie1
1AppliedMechanicsVehicleSafety
ChalmersUniversityofTechnology
41296,Gothenburg,Sweden
email:marco.dozza@chalmers.se
2
Whilewaitingforaccidentdatabasestohavethefinalwordonthesafetyimpactofelectrical
bicyclesinEurope,theeBikeSAFEproject[3]startedcollectingnaturalisticcyclingdatafrom
electricalbicyclesinGothenburg.Naturalisticcyclingdataisdatacollectedfrominstrumented
bicyclesriddenbyvolunteersduringtheirdailyactivities.Thisdatacapturesbothcyclingbe
haviourandbicycledynamicscontinuouslyandcanprovideindepthinformationaboutacci
dentcausationandcyclistbehaviourwhichisnotavailableinaccidentdatabases.Infact,acci
dentdatabasesonlyincludedatacollectedpostcrash,thusanyinformationaboutthe
situationbeforethecrashanditscausesisnotmeasuredorrecorded,butcanonlybesimulat
edoracquiredfrominterviewsaposteriori.Inaddition,naturalisticdatarecordwithcameras
theinteractionbetweentheegobicycleandtheotherroadusersinthesurroundings.
Theabsolutesafetyimpactofelectricalbicyclesisveryimportantbutnotsufficienttodeter
minetheextenttowhichsafetycriticalsituations(crashandnearcrashes)aredifferentfor
electricalbicyclescomparedtotraditionalonesand,asaconsequence,whetherelectricalbi
cyclesaremoreorlesssafethantraditionalones.Toaddresstheseissues,theeBikeSAFEpro
jectwillcomparethedatacurrentlyundercollectionfromelectricalbicycleswithapreexisting
datasetofnaturalisticcyclingdatafromtraditionalbicycles[4].Evenifthesizeofthesenatu
ralisticcyclingdatasetsisrelativelylimitedandnotcomparabletothepresentnaturalisticdriv
ingdatasets[5],thedatacollectedineBikeSAFEisuniqueandpromisestoinforminfrastruc
tureandbicycledesign,technologicalapplications,andregulationsforsafercycling.
2DATACOLLECTION
Naturalisticcyclingdataiscollectedbyinstrumentedbicyclesriddenbyvolunteersduringtheir
dailyactivities.Instrumentingelectricalbicyclespresentsnewchallengesincomparisonwith
traditionalbicyclesbecausetherearemorewaystouseanelectricalbicyclethanatraditional
one.Infact,anelectricalbicyclecanbestillusedasatraditionalone,differentsettingsenable
thecyclisttodecidehowthebicyclewillbehave,andanelectricalbicyclecanbecommanded
Figure1.A:TraditionalbicycleinstallationfromBikeSAFE.B:Electricalbicycleinstalla
tionfromeBikeSAFE.
3
bothwithpedals,andtosomeextent,withahandlebarthrottle.Thissectiondescribeshow
datacollectionwasadaptedfromtraditionalbicyclestoelectricalbicycles,includingthenewly
collecteddata’sabilitytocapturetheinteractionandinterplaybetweenthecyclistandthe
electricalbicycle.
2.1Cyclists’recruitment
eBikeSAFEaimsatcollectingdatafrom1)thesamecyclistswhoparticipatedinBikeSAFEand
2)duringthesameperiodoftheyear.Thus,allcyclistswhoparticipatedintheBikeSAFEcollec
tionwerecontactedandaskedtoparticipatetotheeBikeSAFEstudyaswell.However,new
volunteerswerealsorecruitedtoguaranteeasufficientlylargesampleofparticipants.Never
theless,cyclistswhoparticipatedinBikeSAFEareprioritizedtoenablewithinsubjectanalyses
possiblyavoidingbiasesfromdifferentbicycleusagesorcyclingperformances.

2.2Installation
PreviousexperiencefrompreBikeSAFE[6]wasthebasisforinstrumentingelectricalbicyclesin
eBikeSAFE.Traditionalbicycleinstallationsmadeuseofacustomizablelogger[7]tocollect
datafromavarietyofsensorsincludingGPS,inertialmeasurementunits,brakeforce,and
cameras(Fig.1A).Allcomponentswerefoundofftheshelfwithexceptionofthepressure
brakesensors.However,allsoftwareforoperationoftheloggerandcalibrationofthesensors
wasdevelopedintheBikeSAFEprojectandisdetailedinDozza&Fernandez,2013[8].Thetra
ditionalinstallationalsoincludedacircuitryforautomaticstartandstopofthedatalogging
andasimplehumanmachineinterfacecomprisedofanLEDlightandapushbutton.TheLED
lightsignalledthestatusoftheloggerbylightingupduringrecording,thepushbuttonenabled
thecyclisttotimestampeventsduringtheirjourney.Anytimethebuttonwaspressed,atime
stampwassavedintheloggertoenabletheanalysttoquicklyfindthedata(includingvideo)
correspondingtothatpointintimeduringtheanalysis.
Figure2.A:Throttle.B:Pedalrotationsensor.C:Controlunit.D:Brakesensor.
4
2.3Objectivedata
Anelectricalbicycleisnotjustatraditionalbicyclewithanelectricalmotorandabattery;an
electricalbicyclealsoincludesothercomponentssuchasathrottle(tobringthebicycleupto
a6km/hspeed;Fig.2A),apedalsensor(whichisusedasadigitalindicatorofthecyclist’swill
ingnesstomoveforward;Fig.2B),acontrolunit(enablingthecyclisttochangethebicycle
speed;Fig.2C),andtwobrakeswitches(toautomaticallydisconnectthemotoranytimethe
cyclistbrakes;Fig.2D).Allthesecontrolsenable“novel”cyclingbehavioursandwereconsid
eredaspotentialsignalsfordatacollection.AstheinstrumentationfromBikeSAFEalreadyhad
twobrakepressuresensors,thebrakeswitchessignalswerecombined.Thewirefromthepe
dalsensorwassplitandconnectedtotheloggersothatthisnewsignalcouldbeusedtode
terminethecyclist’sintentiontomoveforward(Fig.1B).Acurrentsensorwasalsoinserted
betweentheelectricalbicyclecontrolunitandthemotorinordertomeasurethepowerthat
themotorwasinstantaneouslyusingtopropelthebicycle(Fig.1B).Asspeediscontinuously
collectednoinformationaboutthecontrolunitsettingswascollected.Further,asthethrottle
isonlyintendedforstartingthebicycleanditsstatuscouldbeinferredbycombiningspeed
withpedalvelocity,noinformationaboutthethrottlepositionwasacquired.Allsignalswere
collectedwitha100HzsampleratewithexceptionfortheGPS(10Hz)andthevideo(30fps).
2.4Subjectivedata
Beforedatacollection,thecyclistswereaskedtosignaconsentformandtofillinaquestion
nairecovering1)demographicdata(e.g.,age,gender,occupationalfield,typeofbicyclethey
mainlyride,etc.)2)theircyclingbehaviourandusageoftheirbicycles(e.g.,overtheyear,for
whichpurpose,helmetuse,etc.),aswellas3)theiropiniontowardselectricbicycles,inde
pendentlyiftheyalreadyhaveordon’thaveexperiencewithelectricbicycles(e.g.,levelof
agreementtostatementssuchas,ebikesareratherforolderpeople).Thisquestionnairewas
againinspiredbytheBikeSAFEproject.Duringcollection,thecyclistswereaskedtofillinatrip
diary,detailingtimeandpurposeforeachtriptakenwiththeelectricalbicyclesimilarlyto
BikeSAFE.Anytimethecyclistsexperienceasafetycriticalsituation,i.e.asituationwhich
madethemfeelsafetyuncomfortable,theywereaskedtopressthepushbuttononthebicycle
handlebarandtoincludethisinthetripdiary.Additionally,thecyclistswereaskedtofillina
protocolforeachsafetycriticaleventinordertodescribethesituationindetail.Furthermore,
theprotocolincludedquestionsconcerningtheexpectationoftheupcomingevent,howcom
fortabletheyfeltinthesituation,anyvisualocclusions,andalsotheroad,lightandweather
conditions.Afterthetwoweeksofdatacollection,thecyclistswereinterviewedconcerning
eachsafetycriticaleventwithananalystfromtheproject,basedontheprotocols.Duringthe
interviewthetimestampsfromthepushbuttonwereusedtopresentthecyclistwiththevid
eocorrespondingtothesafetycriticalsituationunderdiscussion.Finally,allcyclistsalsofilled
inaquestionnairetoreportontheirimpressionsofridingtheelectricalbicycle.Thisquestion
nairewasdevelopedineBikeSAFEtodeterminetheextenttowhichcyclistsfeltsafewhilerid
ingtheelectricalbicycle.
3DATAANALYSIS
Oneoftheadvantagesofnaturalisticdatasetsisthepossibilitytoreusethesamedatasetfor
differenttypesofanalysis.Further,bycombiningnewandexistingdatasetsnovelanalysescan
beenabled.ThisisindeedthecaseineBikeSAFEwherecomparisonswiththeexisting
BikeSAFEdatasetarethebasistodeterminewhetherelectricalbicyclesaremoreorlesssafe
thantraditionalones.
3.1BikeSAFEdataset
TheBikeSAFEdatasetwascollectedin2012fromfiveinstrumentedbicycles(Fig.1A)and20
cyclistswhotookturnsinridingthebicyclesfor2weeks.Allbicyclistsalsocompiledatripdia
ry,twoquestionnaires(onebeforeandoneafterdatacollection)andunderwentaninterview
afterthetwoweeksofdatacollection.Duringtheinterview,thecyclistsdiscussedwithanana
5
lystthesafetycriticalsituationstheyencountered.Intotal,332trips,covering1549kmover
114hourswerecollected.Averagespeedwas13.6km/h(SD=3.2km/h),andaveragetripdu
rationwas22min(SD=8.6min).Intotal,63criticalsituationswerereportedbythepartici
pantsduringcollection.Sixofthesecriticalsituationswereconsideredascrashesastheyin
volvedsomephysicalcontact,inthreecriticalsituationsthecyclistfelloffthebicycle.All
criticalsituationswerereviewedbytwoanalystsandcodedaccordingtotheBikeSAFEcoding
scheme[9].ObjectivedataintheBikeSAFEdatasetincludeddatafromthesensorsinFig.1A.
Alldatawascollectedwitha100HzsampleratewithexceptionfortheGPS(10Hz)andthe
video(30fps).
3.2Cyclingbehaviour
Cyclingbehaviourcanbeassessedinseveralways,oneofwhichisbymeasuringbicycledy
namics.Forinstance,distributionsofspeedanddistributionsofaccelerationsanddecelera
tionsoverspeedintervalscanidentifythecyclistcomfortboundaries.Acomparisonofspeed
distributionbetweentraditionalbicyclesandelectricalbicyclescanhelpindeterminingthepo
tentialimpactonsafety,ashigherspeedhasbeenshowntoleadtomoreandmoresevere
crashesformotorizedvehicles[10].Figure3showsthespeeddistributionfromBikeSAFEin
comparisonwithapreliminarydistributionfromeBikeSAFElimitedtoonlyonecyclistand
suggestingelectricalbicyclesbeingalmost10km/hfasteronaveragethantraditionalones.
Figure3.SpeeddistributionsfromBikeSAFE(left)andeBikeSAFE(onlyonesubject;
right).
Figure4.ObediencetotrafficrulesfromBikeSAFER.
6
Byfurthercomparingthecomfortboundariesofelectricalbicyclesandtraditionalbicyclese
BikeSAFEwilldeterminetheextenttowhichelectricalbicyclesaremoreorlessmanoeuvrable
thantraditionalbicyclesindifferentsituations(forexampleatintersections)andgiveanindi
cationofwhetherandhowcyclinglanesshouldbeadaptedtoelectricalbicycles(forinstance
intermsofminimumwidthandcurvature)topreservemanoeuvrabilityandvisibilityofthecy
clistathigherspeed.
Naturalisticdatacanalsobeusedasobservationaldata(i.e.datacollectedbyanalystsobserv
ingroadusersbehaviourinrealtraffictodeterminetheextenttowhichcyclistsobeytraffic
rulesandrecommendations.Figure4showssomeresultsfromBikeSAFER[11]wheretheuse
ofhelmets,properlightingwhendark,andprevalenceofintersectionspassedwitharedlight
wereestimatedfromvideoclipsrandomlypickedfromthewholedataset.Thesameanalysis
willbecarriedonineBikeSAFEtodeterminetheextenttowhichelectricalbicyclesaremore
orlesspronethantraditionalbicyclestopassaredlight.
3.3Accidentcausation
Asaccidentprobabilityisrelatedtospeed[10],comparingspeedacrossgeographicalcoordi
natesforelectricalandtraditionalbicycleswillbeanimportantstartpointfortheeBikeSAFE
safetyanalysis.BysubtractingfromtheBikeSAFEspeedmapinFigure5aneweBikeSAFE
speedmap,itwillbepossibletovisualizeandlistthelocationswherethedifferenceinspeed
betweenelectricalandtraditionalbicyclesislarge.Thislist,oncerankedaccordingtospeed
andprevalenceofcyclingaccidentinSTRADA,willgeographicallyfocusoursafetyanalysisand
helpdefininglimitsinthecurrentcyclinginfrastructuresdependingonthegeometricalfea
tures(suchascurvature,slope,andproximitytointersections)ofthelistedlocations.
SafetycriticaleventsfromeBikeSAFEwillbereviewedandcodedsimilarlyasinBikeSAFE[9].
ByplottingtheGPScoordinatesofeachsafetycriticalevent,itwillbepossibletocreateamap
similartotheonefromBikeSAFEinFigure6.Further,randombaselineeventswillbeextracted
fromeBikeSAFEsimilarlyasinBikeSAFE.Bycomparingthefourgroupsofevents(baselineand
criticalevents,fromelectricalandtraditionalbicycles)eBikeSAFEwilldeterminetheextentto
whichsafetycriticalsituationsaredifferentforelectricalbicyclescomparedtotraditionalones,
intermsofthedifferentcodingvariables.Forinstancecomparisonbetweencriticalsituations
Figure5.GeographicaldistributionofaveragespeedfromBikeSAFER.
7
mayshowwhetherelectricalbicyclesarelesssafeatintersections.Furthercomparisonof
baselineswillshowwhetherelectricalbicyclesandtraditionalbicyclesareexposedtodifferent
situations.Thislateranalysiswillshow,forinstance,whethertheinteractionwithotherroad
usersismoreprevalentwhenridinganelectricalbicyclethanwhenridingatraditionalbicycle,
whichweexpectasaconsequenceofthehigherspeed.
TheaimoftheanalysisofthesubjectivedataineBikeSAFEwillbesimilartotheoneinthe
BikeSAFEproject.Thegoalwillbetoinvestigatecyclists’perceptionofsafetycriticalsituations
whenridinganelectricalbicycle.AcomparisonofthesafetycriticaleventsfoundinBikeSAFE
withtheonesineBikeSAFEwillmakepossibletoexaminehow1)thefrequencyofsafety
criticaleventsand2)thetypeofconflictencounteredwilldistinguishbetweencyclingwithan
electricalbicyclecomparedtoatraditionalone.Furthermore,withtheinterviewprotocolused
ineBikeSAFEandusingthevideoscenewhileinterviewingthecyclistitispossibletoprovidea
muchmoredetailedinsightintosafetycriticalsituationsfromacyclist’sperspectivewhichis
notavailablefromotherinformationsources,suchasaccidentdatabases,cyclingsimulators,
andonroadtesting.Completingtheinterviewprotocolattheendofthetwoweeksofdata
collectionwillalsoensureamuchbetterrecollectionfromthecyclist.
4DISCUSSION
AstheeBikeSAFEprojectiscurrentlycollectingdata,thissectionfocusesonthelessons
learnedsofarwhileadaptingthenaturalisticmethodologytoelectricalbicycles.
4.1Datacollection
TheeBikeSAFEprojectiscurrentlycollectingdata,prioritizingvolunteerswhoalsoparticipat
edtotheBikeSAFEcollection.Whilesuchprioritizationseemslegitimateasitwillproducea
datasetenablingwithinsubjectanalyses,itmayalsocarryonpotentialsubjects’biasesfrom
thepreviouscollection.AnalysisofsubjectivedatafromBikeSAFEdidnotshowthepresence
ofanyoutliersuggestingthattheparticipantsinBikeSAFEwereindeedareasonablerepresen
tationofthecyclingcommunityinGothenburg.Nevertheless,atthepresenttime,femalecy
Figure6.BaselineandsafetycriticaleventsfromBikeSAFER.
8
clistswhoparticipatedtoBikeSAFEseemmorepronetoparticipatetoeBikeSAFEthanmale
cyclists,thuspotentiallygenderbiasingthenewdataset.
Theinstallationofelectricalbicyclespresentedseveralnewchallengeswhichwereunex
pected.Acquiringsignalsfromthebicyclecontrolunitrequiredadeepunderstandingofthe
electricalbicyclehardwareandwiring.Further,poweringtheBikeSAFEloggerfromthebicycle
batterywasconvenientbutalsocreatednewpossiblemisuseofthesystemasthecyclistispo
tentiallyabletoturntheloggerdownwhileoperational.
Newsignalsfromthepedalsensorsandthecurrentsensorsneededtobeopportunelypre
processedbeforetheycouldbeused.Itisworthnotingthatcorrectlyacquiringinformation
aboutpedalspeedisnotpossiblewitha10Hzfrequency,whichistheusualstandardfornatu
ralisticdatacollection,whilethe100HzsamplingfrequencyusedineBikeSAFEwasdefinitely
sufficient.Forthecurrentsensorthemainissuewasinsteadcalibration,howeverthismaybea
sensorspecific(Phidgets1122CurrentSensor)issue.InSweden,thehandlebarthrottlefor
electricalbicyclescanonlybringabicycleupto6km/h,withoutpedalinput,becauseoflegal
requirements.However,whenbuyinganelectricalbicycle,thecustomerisinformedthatby
removingasmallconnectorfromthecontrolbox,the6km/hlimitationwillbedisabledand
thethrottlewillthenenablethebicycletoreach25km/h.Bycombiningthepedalsensordata
withthecurrentsensordata,itwillbepossibletodeterminewhetheranyofthebicyclistsde
cidedtotakeawaytheconnectorandoperatethebicycleillegally.However,byconnectingthe
throttledirectlytoourlogger,itwouldbemucheasiertoestablishhowthethrottleisactually
used.IfeBikeSAFEwouldprovethatsomebicyclistsareindeedusingthehandlebarthrottle
beyondregulations,futurecollectionshoulddefinitelylogthethrottlesignal.
4.2Dataanalysis
ThemainconcernfordataanalysisintheeBikeSAFEprojectisaboutstatisticalsignificanceof
theresults.BikeSAFEprovedthat100hoursofcyclingaresufficienttoshowstatisticalsignifi
canceforsomeofthemainfactorscontributingtocriticalsituations.However,suchadataset
wasnotalwaysabletoshowsignificanceforrelativelysporadiccircumstances.Forinstance,
thepresenceofconstructionworksonthebicyclelaneseemedtohaveanimpactofthelikeli
hoodtoencounterasafetycriticalsituation,however,theconfidenceintervalsfromthe
BikeSAFEdatasetweretoowidetoclaimsignificanceforsucharesult.Itispresentlynotclear
whethereBikeSAFEwillbeabletoproduceadatasetcomparabletoBikeSAFE.Inpartbecause
oftheverylimitedbudgetofeBikeSAFE,whichresultedinalower(3vs.5)numberofinstru
mentedbicycles.However,iftheelectricalbicycleswoulddrivetheparticipantstoridelonger
durationsthantheydidinBikeSAFE,theeBikeSAFEdatasetmaybecomeaslargeasthe
BikeSAFEonedespitealowernumberofcyclists.
Preliminaryresultssuggestthatelectricalbicyclesareindeedfasterthantraditionalbicyclesin
traffic.However,thisresultisstilltobeconfirmedanditssafetyimplicationstobedefined.In
thisrespect,comparisonswithpreviousstudiessuchastheonespresentedinGehlertetal.,
2011[12]andSEEKING[13]willhelpdeterminewhethersafetyconcernsaboutelectricalbicy
clesareindeedfundedandtheextenttowhichtheseconcernsmaybedifferentindifferent
Europeancountries.Inanycase,ridingfasterincreasescyclists’attentiondemandasinterac
tionwithotherroadusers,suchasovertakingmanoeuvres,becomesmorefrequent.Further,
electricalbicyclesarenotalwaysclearlydistinguishablefromtraditionalones.Asaconse
quence,itmaynotbeobviousforotherroadusers,(e.g.adriveratanintersection),toesti
matetheirspeed(e.g.whendecidingtocrossthebicyclepath).
5CONCLUSIONS
ElectricalbicyclesareincreasinglypopularinEuropeandpromotedbythelocalauthoritiesin
severalEuropeancountries.Safetyconcernsaboutelectricalbicyclesarelegitimateasthese
newbicyclesareoperateddifferentlyandexhibitdifferentdynamicscomparedtotraditional
bicycles.Atimelywaytodeterminethesafetyimpactofelectricalbicyclesisbyusingnatural
9
isticcyclingdataasintheeBikeSAFEproject,whereinstrumentedbicyclescontinuouslycol
lectdatafromacameraandothersensorsintraffic.
Electricalbicyclesaremorecomplexthantraditionalbicyclescreatingnewchallengesfornatu
ralisticdatacollectionandanalysis.Infact,electricalbicyclespresentnewcommandsandpro
pulsionpossibilities.Thisinformationneedstobeloggedtodeterminetheextenttowhichcy
clistsareactuallytakingadvantagefromtheelectricalmotorandthewaycyclistsinteractwith
theelectricalpropulsionsystem.
eBikeSAFEanalysiswillleverageontheexistingBikeSAFEdataset(anaturalisticcyclingda
tasetfromtraditionalbicycles)todeterminethenetsafetyimpactofelectricalbicycles.Anal
yseswillfocusoncyclingbehaviourandaccidentcausationandwillbeguidedbythecentral
hypothesisthatlocationswherethevelocityofelectricalbicyclesdifferthemostfromtradi
tionalbicyclesarethemostrelevantforsafety.

ACKNOWLEDGEMENTS
TrafikverketandtheSwedishStrategicFundsforTransportationarecurrentlysponsoringthe
projectpresentedinthispaper.
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... The e-bikes can reach higher speeds and enable longer rides. Therefore, they increase the probability of accidents involving cyclists [19,20]. To understand the differences between the bicyclist behavior and dynamics of traditional bicycles and e-bikes, Werneke and Dozza [21] and Dozza [20] created two systems called BikeSAFE and e-BikeSAFE to collect naturalistic cycling data from traditional bicycles and e-bikes. ...
... Therefore, they increase the probability of accidents involving cyclists [19,20]. To understand the differences between the bicyclist behavior and dynamics of traditional bicycles and e-bikes, Werneke and Dozza [21] and Dozza [20] created two systems called BikeSAFE and e-BikeSAFE to collect naturalistic cycling data from traditional bicycles and e-bikes. They identified that the collection of data from e-bikes is still not as efficient as on traditional bicycles. ...
Article
The number of bicycle riders in New York City (NYC) has been increasing steadily in the past few years. These numbers include private and shared bicycles. The NYC bicycle network has been expanded to accommodate the needs of the increasing number of riders. Although the new infrastructure has reduced the number of cyclists killed or seriously injured (KSI) in some areas, in other areas similar improvements were not observed. A data-driven approach to study the possible effects of this type of infrastructure inconsistency on the variation of the number of bicycle crashes from one region to another in the city is the primary motivation of this paper. A highly portable and inexpensive sensing device for measuring the distance between a bicycle and lateral objects is designed and developed from scratch. The developed mobile sensing device can also map bicycle trajectories to highlight critical segments where the safe distance from passing vehicles is not respected. This mobile device is powered by a portable power source and it is comprised of two ultrasonic sensors, a Global Positioning System (GPS) receiver, and a real-time clock (RTC). The sensor is secured inside a custom design 3D printed case. The case can be easily attached to any bicycle including shared bikes for testing. The final prototype is entirely functional and used to collect sample data to demonstrate its effectiveness to address safety-related problems mentioned above. Finally, a dashboard is created to display collected key information. This key information can be used by researches and agencies for a better understanding of the factors contributing to the safety of bicycle routes.
... The e-bikes can reach higher speeds and enable longer rides. Therefore, they increase the probability of accidents involving cyclists [17,18]. To understand the differences between bicyclist behavior and dynamics of traditional bicycles and e-bikes, Werneke and Dozza [19] and Dozza [18] created two systems called BikeSAFE and e-BikeSAFE to collect naturalistic cycling data from traditional bicycles and e-bikes. ...
... Therefore, they increase the probability of accidents involving cyclists [17,18]. To understand the differences between bicyclist behavior and dynamics of traditional bicycles and e-bikes, Werneke and Dozza [19] and Dozza [18] created two systems called BikeSAFE and e-BikeSAFE to collect naturalistic cycling data from traditional bicycles and e-bikes. They identified that the collection of data from e-bikes is still not as efficient as on traditional bicycles. ...
Article
Full-text available
The number of bicycle riders in New York City has been increasing steadily in the past few years. These numbers include private and shared bicycles. NYC bicycle network has been expanded to accommodate this new volume. Although this new infrastructure has reduced the number of cyclists killed or seriously injured (KSI) in some areas, in other areas similar improvements were not observed. This inconsistency of how the number of bicycle crashes varies from one region to another in the city is the primary motivation of this paper. A highly portable and inexpensive sensing device for measuring the distance between a bicycle and lateral objects is designed from scratch and developed. The developed mobile sensing device can also map bicycle trajectories to highlight critical segments where the safe distance from passing vehicles is not respected. This device which is powered by a portable power source is comprised of two ultrasonic sensors namely, a Global Positioning System (GPS) receiver, and a real-time clock (RTC). The sensor is secured inside a custom design 3D printed case. The case can be easily attached to any bicycle including shared Citi Bike bicycles for testing. The final prototype is entirely functional and used to collect sample data to demonstrate its effectiveness to address safety-related problems mentioned above. Finally, a dashboard is created to display collected key information. This key information can be used by researches and agencies for a better understanding of the factors contributing to the safety of bicycle routes.
... Regarding the city residents' strong habits of fulfilling their transport needs, and in particular strong attachment to owning passenger cars, it is justifiable to conclude that the shift from passenger cars to bicycles in daily urban travel should be easier in the case of electric bikes. Thanks to the electric power-assisted steering, such travel is easier, more convenient, and faster, which reduces the discrepancy in the perceived difficulty between traveling by bike and passenger car [56,57]. ...
Article
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The current quantitative and qualitative development of bike-sharing systems worldwide involves particular implications regarding the level of sustainability of urban development and city residents' quality of life. To make these implications as large as possible as well as the most positive, it is essential that the people who use municipal bikes on a regular basis to the largest extent possible abandon car travel at the same time. Thanks to their operational characteristics, electric bikes should enable meeting the transport needs of a wider group of city residents compared with traditional bicycles. The main aim of this study was therefore to check whether the municipal electric bike system (MEVO) in Gdańsk-Gdynia-Sopot metropolitan area of Poland lived up to the hopes placed upon it by policymakers. Therefore, the article tests the hypothesis indicating that the municipal electric bike systems constitute a substitutable form of transportation against passenger cars to a larger extent than against collective urban transport and walking trips. The analysis was performed based on the results of primary studies conducted among the users of MEVO. The data show that the MEVO was a substitutable form of transportation against collective transport and walking trips to a larger extent than against passenger cars. Through logistic regression analysis, the variables concerning the probability of replacing car trips by MEVO bicycles were determined. Among the analyzed variables, the following turned out to be statistically significant: age, the number of people in the household, the number of cars in the household, the distance from work, and gender. The results therefore indicate that substituting in favor of electro bikes was more probable for younger people with fewer people in the household and a distance to travel below 3 km, whereas it was less probable for people with more cars in the household or traveling a distance longer than 10 km. Additionally, females were more likely to choose the bike system.
... In addition, e-bicycles are useful for people who are not able to ride conventional bicycles due to physical limitations (MacArthur et al., 2014). In many countries, ebicycles' use has increased recently; in Europe, the growing use was observed particularly in Germany, the Netherlands, Austria, Switzerland, Italy and France (Dozza et al., 2013;Fishman and Cherry, 2016). As estimated, in Israel, over 200,000 e-bicycles were sold in a period of three years. ...
Article
Alternative transport means (ATMs) such as e-bicycles, electric scooters, mobility scooters (for the elderly) and segways, suggest improved mobility for individual road users, with associated benefits of reduced congestion and energy savings. However, the urban space is not adapted to incorporate these means, while ATMs use the infrastructure built for vehicles or pedestrians and are not always in accordance with traffic rules. The growing use of ATMs is accompanied by an increase in related injury. This study aimed to characterize the scope of ATM use in Israeli cities, their behaviours at typical urban locations and risk factors, and to consider solutions for safer ATMs integration into the urban space. The study data were collected by means of an observational survey at 50 representative urban intersections, in 9 city centers. Regression models were adjusted to explore the relationships between the presence of various road users. Profiles of ATM users and their behaviours were examined. The models showed a direct relation between the presence of traditional transport means and ATMs, meaning that they are used for the same destinations in the city. The e-bicycle presence was generally similar to that of regular bicycles; it was low on roadways related to vehicle traffic, but more tangible on sidewalks, related to pedestrian traffic. At sites with higher vehicle volumes, more ATMs rode on sidewalks. Among most ATM users, except for mobility scooters, children below 18 presented about a third and the majority were young adults aged 19-34. Most ATM riders did not wear helmets. The study findings indicated that the ATM volumes in the cities are not negligible and should be accounted for in planning urban facilities. For safer ATMs integration in the cities, more bicycle facilities and wider sidewalks are needed, accompanied by enforcement and publicity efforts.
... Worldwide sales of electric bicycles were estimated to be over 40 million units in 2015, of which 36.8 million (91.9%) were sold in China and over 2.3 million (5.8%) in Europe. In Europe, between the years 2011 and 2015, the total amount of e-bicycle sales increased by 88%, with a particular increase in sales in Germany, the Netherlands, Austria, Switzerland, Italy and France [1,2]. Hurst and Gartner [3] presented a forecast scenario of the e-bike growth by world regions, and suggested that annual e-bike sales in the world (excluding China) will approach 4 million in 2020; an aggressive forecast suggests even higher numbers. ...
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In Israel, a growing use of electric bicycles by youngsters has been noted, with an increase in related injuries. In this study, an observational survey was conducted on typical urban streets, aiming to characterize the riding speeds of young e-cyclists compared to regular cyclists and the associated risk factors in their behaviors. The survey covered 39 sites in eight cities, and included 1054 cyclists. The results showed that mean speeds of young e-cyclists were higher than those of regular cyclists at all types of sites, with a difference of 6–9 km/h. The mean speeds of e-bicycles were below 25 km/h, as prescribed by law, but the 85-percentile speeds were higher. E-cyclist speeds depend on the type of street, road layout and place of riding. More e-cyclists used the roadway compared to regular cyclists, however, on divided roads, more e-cyclists used sidewalks in spite of the law prohibition, thus endangering pedestrians. The majority of cyclists did not wear helmets. The unsafe behaviors of teenage e-cyclists increase the injury risk for themselves and for other road-users. Thus, separate bicycle infrastructure should be promoted in the cities. Road safety education and training of young e-cyclists with stronger enforcement of traffic regulations are also needed.
... It is also possible to transform a conventional bike into an electrical assisted bike, as mentioned in reference [27], but one has to think about costs and gain in performance, as you cannot always get the best of both worlds. Purchase costs Tens/hundreds of thousands € * 3000 to 10,000 € * below 1000€ * 500 to 5000 € * Maintenance costs High: Up to tens of thousands € Medium: Hundreds to thousands of € * Low to medium: Hundreds of € * * According to estimations; ** dependent on charger and battery type; 1 according to references [2,17,19,20], based on average values for the sum of main pollutants: CO (carbon monoxide), NOx (nitrogen oxides), VOC (volatile organic compounds), and PM10 (particulate matter that have 10 micrograms per cubic meter or less in diameter); 2 according to reference [28]; 3 according to references [29,30]; 4 according to reference [26], based on average values for car/bus and e-bike, up to 5 km; 5 according to reference [21], based on average values; 6 according to references [31,32]; 7 according to reference [25]; 8 according to reference [33]. ...
Article
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As the title suggests, the sustainability of personal electric vehicles is in question. In terms of life span, range, comfort, and safety, electric vehicles, such as e-cars and e-buses, are much better than personal electric vehicles, such as e-bikes. However, electric vehicles present greater costs and increased energy consumption. Also, the impact on environment, health, and fitness is more negative than that of personal electric vehicles. Since transportation vehicles can benefit from hybrid electric storage solutions, we address the following question: Is it possible to reach a compromise between sustainability and technology constraints by implementing a low-cost hybrid personal electric vehicle with improved life span and range that is also green? Our methodology consists of life cycle assessment and performance analyses tackling the facets of the sustainability challenges (economy, society, and environment) and limitations of the electric storage solutions (dependent on technology and application) presented herein. The hybrid electric storage system of the proposed hybrid e-bike is made of batteries, supercapacitors, and corresponding power electronics, allowing the optimal control of power flows between the system’s components and application’s actuators. Our hybrid e-bike costs less than a normal e-bike (half or less), does not depend on battery operation for short periods of time (a few seconds), has better autonomy than most personal electric vehicles (more than 60 km), has a greater life span (a few years more than a normal e-bike), has better energy efficiency (more than 90%), and is much cleaner due to the reduced number of batteries replaced per life time (one instead of two or three).
... The number of electric bicycles is rap-idly rising in Europe: between years 2011-2015 the total amount of sales increased by 88% (Fishman and Cherry, 2016). In countries, such as Austria and Germany, the sales of e-bicycles have doubled from 2010 to 2012, while in Switzerland the sales increased by 50% and in Italy and France by 20% (Dozza et al., 2013). Germany and the Netherlands are the leading e-bicycle markets, accounting for 44% and 21%, respectively, of the total European Union sales (Fishman and Cherry, 2016). ...
Article
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Electric power-assisted bicycles (e-bicycles) provide a convenient form of mobility in urban areas, being an attractive alternative to private cars, usual cycling and walking. However, there is a growing concern of their associated injuries, resulting from the increasing exposure and apparently higher speeds. Unlike other countries, in Israel, a growing use of e-bicycles by youngsters (below 18) is observed, in many towns, accompanied by a substantial increase in the number of related injuries. In this study, an observational survey of young e-cyclists was undertaken in Israeli towns aiming to characterize their behaviours at typical urban settings and then to consider measures needed for their safe integration in the urban space. The observational survey was focused on teen e-cyclists' behaviours during their trips to and from school and during leisure hours. The data were collected by means of dynamic video-recording, at five types of urban settings: signalized and un-signalized intersections; roundabouts; street sections with and without bicycle-paths. The survey covered 225 locations in 15 cities, including 150 sites near high-schools and 75 in city centers. In total, over 2000 video-films were collected and their contents were coded for statistical analyses. The results showed that at all types of sites, most teenager e-cyclists were males, older than 16 and not wearing a helmet, despite the traffic law demands. High shares of them rode on sidewalks and crossed at crosswalks, violating the law that prohibits using pedestrian facilities for riding. At signalized intersections, substantial shares crossed on red, both on the roadway and on crosswalks, thus violating the traffic law and increasing accident risk. At various urban settings, young e-cyclists demonstrated a wide range of risky manoeuvres. They move faster than pedestrians and endanger them on sidewalks, but also disturb vehicle traffic and endanger themselves while riding on the road. A wider application of bicycle infrastructure, with better separation between the sidewalks, roadways and bicycle paths, would lead to a safer integration of e-bicycles in Israeli cities. Additionally, road safety education and training of teen e-cyclists supported by stronger enforcement of traffic regulations are required.
Conference Paper
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The aim of this study is to understand the real-world use of both bicycles and Pedelecs in order to contribute to an increased road safety of both vehicle types. Due to a lack of in-depth information in the user research thus far, a quantitative user study was conducted (survey details: period June/ July 2020, countries GER, CH, NL, FR, UK and USA; participants: N = 3026, Ø age 44.07 years, 49.6 % female, bicycle or Pedelec owner). The survey results indicate that Pedelecs compared to bicycles are used more for everyday purposes (+20 % commuting and errands), more frequently (+50 %), and more for traveling longer distances (+60 %). The riders try to compensate for their higher accident exposure by increasing their visibility in road traffic (e.g. light-reflecting vests +9 %) and by wearing a helmet (+9 %). Most accidents occur in urban areas (70 %) and at intersections (29 %), which motivates the improvement of traffic and bicycle infrastructure. Car-and truck-side systems such as turning assistants, reverse driving assistance, and dismounting warning systems can effectively mitigate potential conflicts as well. Single bicycle accidents occur second most frequently after passenger car accidents. In comparison, single Pedelec accidents are 13% less frequent, but accidents involving other vulnerable road users are more frequent. Therefore, the infrastructure should be adapted to the increasingly multimodal use and anti-lock braking systems (ABS) should be used to achieve short braking distances. In 18 % of the cases, the injured cyclists and Pedelec riders did not receive direct medical help, which can be reduced by eCall systems. If these challenges regarding road safety are solved, the user study shows that both bicycles and Pedelecs can be established even more strongly as a sustainable and safe means of transport in the mobility mix of the future.
Article
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The significance of commuting with ebikes as an integral part of the urban mobility of the future can no longer be ignored. The real and perceived hazards of cycling in urban areas and sharing roads with other motorized vehicles have been identified as a major barrier to wider adoption of ebikes. The objective of this study is to investigate parameters that affect the anxiety level of cyclists, which influences their safety and interaction with other road users. An ebike was instrumented with a variety of sensors and equipment to monitor the speed, balance of bike, type, and proximity of vehicles overtaking cyclists, as well as the events on the road. Thirty-two participants rode the instrumented ebike for 12 km on urban roads in Oshawa, ON, Canada. Participants wore a heart rate sensor attached to their chest and a helmet equipped with a peripheral detection task setup to measure stress and mental workload. This naturalistic study showed that most participants had concerns about the threats and risks of crashes when sharing the road with other vehicles. The data showed that the significant difference in acceleration between ebikes and conventional bikes does not change the perception of safety for cyclists. Additionally, the outcomes indicate that mental workload and average heart rate increase at lower speeds when passing a queue of vehicles in traffic or at intersections. Across all participants, the balance of the bike did not change significantly. Also, neither the heart rate nor mental workload showed a significant effect on the balance of the bike. This study suggests that dense traffic in the afternoon and the demands of riding a bike in complex traffic conditions result in a higher mental workload even though cyclists slowed down their speeds. Furthermore, the majority reported perceived risks of cycling on a shared road with other vehicles regardless of the demographic differences. The findings from this study can be used as a framework for the development of active safety features for ebikes.
Conference Paper
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This paper presents the study design and first experiences of a Pedelec Naturalistic Cycling study. There are 90 participants: 30 bicylists, 50 Pedelec cyclists and 10 E-bike cyclists. The bicycles are equipped with a data acquisition system that records among others speed data and videos on the traffic situation over a period of four weeks. Questionnaires assessing current travel and traffic behaviour and changes thereof, motives and experiences with Pedelecs / E-Bikes are used when recruiting participants, before and after the observation period. A one-week time use travel diary was used to collect qualitative information on the cycle trips and related activities. Despite a low modal share of bicycling in the study area there were no problems recruiting participants. Recruiting E-bike user proved to be a challenge as their market share in Germany is quite low. Participants are very cooperative even though the study procedure puts quite considerable demand on them. The data acquisition system provides reliable trip and video data, even though there are problems with the GPS data. Thus we expect an exceptional dataset that will improve our understanding of travel and traffic behaviour of E-Bike users.
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In 2009, 9108 vulnerable road users (VRUs; pedestrians and bicyclists) died in the EU and 4722 in the US. Active safety systems, that is intelligent systems able to predict and prevent crashes, may significantly help to reduce VRU fatalities and injuries; however, current active safety systems for VRUs are only found on high-end vehicles, only support the host vehicle driver, and do not make use of wireless communication. The scope of this study is to describe the set-up and real-world verification of a platform to enable active safety systems for VRU. This platform is carried by VRUs and may support multiple road users using wireless communication. A simple conceptual application, addressing pedestrian safety at crossings, was developed to test the platform. This application was not cooperative (i.e. did not support multiple road users with wireless communication). The results presented in this study suggest that such a platform can be employed (i) as a logger for naturalistic studies on VRUs, (ii) to better understand VRU behaviour and accident causation and (iii) as a basis for the development of novel active safety applications, running on portable devices, such as future generation smart phones, and possibly enabled by wireless communication.
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Although from a societal point of view a modal shift from car to bicycle may have beneficial health effects due to decreased air pollution emissions, decreased greenhouse gas emissions, and increased levels of physical activity, shifts in individual adverse health effects such as higher exposure to air pollution and risk of a traffic accident may prevail.Objective: We describe whether the health benefits from the increased physical activity of a modal shift for urban commutes outweigh the health risks. We have summarized the literature for air pollution, traffic accidents, and physical activity using systematic reviews supplemented with recent key studies. We quantified the impact on all-cause mortality when 500,000 people would make a transition from car to bicycle for short trips on a daily basis in the Netherlands. We have expressed mortality impacts in life-years gained or lost, using life table calculations. For individuals who shift from car to bicycle, we estimated that beneficial effects of increased physical activity are substantially larger (3-14 months gained) than the potential mortality effect of increased inhaled air pollution doses (0.8-40 days lost) and the increase in traffic accidents (5-9 days lost). Societal benefits are even larger because of a modest reduction in air pollution and greenhouse gas emissions and traffic accidents. On average, the estimated health benefits of cycling were substantially larger than the risks relative to car driving for individuals shifting their mode of transport.
Article
Presently, the collection and analysis of naturalistic data is the most credited method for understanding road user behavior and improving traffic safety. Such methodology was developed for motorized vehicles, such as cars and trucks, and is still largely applied to those vehicles. However, a reasonable question is whether bicycle safety can also benefit from the naturalistic methodology, once collection and analyses are properly ported from motorized vehicles to bicycles. This paper answers this question by showing that instrumented bicycles can also collect analogous naturalistic data. In addition, this paper shows how naturalistic cycling data from 16 bicyclists can be used to estimate risk while cycling. The results show that cycling near an intersection increased the risk of experiencing a critical event by four times, and by twelve times when the intersection presented some form of visual occlusion (e.g., buildings and hedges). Poor maintenance of the road increased the risk tenfold. Furthermore, the risk of experiencing a critical event was twice as large when at least one pedestrian or another bicyclist crossed the bicyclist’s trajectory. Finally, this study suggests the two most common scenarios for bicycle accidents, which result from different situations and thus require different countermeasures. The findings presented in this paper show that bicycle safety can benefit from the naturalistic methodology, which provides data able to guide development and evaluation of (intelligent) countermeasures to increase cycling safety.
Article
As technology advances, motorized vehicles employ newer, more intelligent systems to improve drivers' safety and mobility. The evolution of these systems is supported by increasingly accurate models for driver behavior and vehicle dynamics. Despite the significant role of nonmotorized vehicles such as bicycles in traffic accidents, the evolution of in-vehicle intelligent systems has no counterpart for bicycles. Part of the reason is that, to date, models for bicyclist behavior are absent and models for bicycle dynamics are limited. This paper presents a platform for collecting field data from bicycles and shows how such data can support the development of intelligent systems by offering novel insights into bicycle dynamics and bicyclist behavior.
Article
This paper presents a re-analysis of the Power Model of the relationship between the mean speed of traffic and road safety. Past evaluations of the model, most recently in 2009, have broadly speaking supported it. However, the most recent evaluation of the model indicated that the relationship between speed and road safety depends not only on the relative change in speed, as suggested by the Power Model, but also on initial speed. This implies that the exponent describing, for example, a 25% reduction in speed will not be the same when speed changes from 100km/h to 75km/h as it will when speed changes from 20km/h to 15km/h. This paper reports an analysis leading to a re-parameterisation of the Power Model in terms of continuously varying exponents which depend on initial speed. The re-parameterisation was accomplished by fitting exponential functions to data points in which changes in speed and accidents were sorted in groups of 10km/h according to initial speed, starting with data points referring to the highest initial speeds. The exponential functions fitted the data extremely well and imply that the effect on accidents of a given relative change in speed is largest when initial speed is highest.
preBikeSAFE (TRV 2011 86383) Slutrapport -Forskningsrapporter (Tillämpad mekanik) ISSN 1652-8549
  • M Dozza
M. Dozza, "preBikeSAFE (TRV 2011 86383) Slutrapport -Forskningsrapporter (Tillämpad mekanik) ISSN 1652-8549; nr 2012:12," Chalmers University of Technology 2012. [7]
Introducing naturalistic cycling data: What factors influence bicyclists' safety in the real world? Transportation Research Part F-Traffic Psychology and Behaviour -accepted pending revisions
  • M Dozza
  • J Werneke
M. Dozza and J. Werneke, "Introducing naturalistic cycling data: What factors influence bicyclists' safety in the real world?," Transportation Research Part F-Traffic Psychology and Behaviour -accepted pending revisions, 2013. [10]