Does haptic steering guidance instigate speeding? A driving simulator study into causes and remedies

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Delft University of Technology

Does haptic steering guidance instigate speeding? A driving simulator study into causes

and remedies

Melman, Timo; de Winter, Joost; Abbink, David

DOI

10.1016/j.aap.2016.10.016

Publication date

2017

Document Version

Final published version

Published in

Accident Analysis & Prevention

Citation (APA)

Melman, T., de Winter, J., & Abbink, D. (2017). Does haptic steering guidance instigate speeding? A driving

simulator study into causes and remedies. Accident Analysis & Prevention, 98, 372–387.

https://doi.org/10.1016/j.aap.2016.10.016

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ContentslistsavailableatScienceDirect

Accident

Analysis

and

Prevention

j o ur na l h o me pa g e :w w w . e l s e v i e r . c o m / l o c a t e / a a p

Does

haptic

steering

guidance

instigate

speeding?

A

driving

simulator

study

into

causes

and

remedies

T. Melman,

J.C.F.

de

Winter

∗

,

D.A.

Abbink

DepartmentofBioMechanicalEngineering,DelftUniversityofTechnology,Mekelweg2,2628CDDelft,theNetherlands

a

r

t

i

c

l

e

i

n

f

o

Articlehistory: Received22May2016 Receivedinrevisedform 17September2016 Accepted13October2016 Keywords:

Behavioraladaptation Hapticsteeringguidance Human-automationinteraction Drivingsimulator

a

b

s

t

r

a

c

t

Animportantissueinroadtrafficsafetyisthatdriversshowadversebehavioraladaptation(BA)todriver assistancesystems.Hapticsteeringguidanceisanupcomingassistancesystemwhichfacilitates lane-keepingperformancewhilekeepingdriversintheloop,andwhichmaybeparticularlypronetoBA. Thusfar,experimentsonhapticsteeringguidancehavemeasureddriverperformancewhilethevehicle speedwaskeptconstant.Theaimofthepresentdrivingsimulatorstudywastoexaminewhetherhaptic steeringguidancecausesBAintheformofspeeding,andtoevaluatetwotypesofhapticsteeringguidance designednottosufferfromBA.Twenty-fourparticipantsdrovea1.8mwidecarfor13.9kmonacurved road,withconesdemarcatingasingle2.2mnarrowlane.Participantscompletedfourconditionsina counterbalanceddesign:noguidance(Manual),continuoushapticguidance(Cont),continuousguidance thatlinearlyreducedfeedbackgainsfromfullguidanceat125km/htowardsmanualcontrolat130km/h andabove(ContRF),andhapticguidanceprovidedonlywhenthepredictedlateralpositionwasoutside alateralbandwidth(Band).Participantswerefamiliarizedwitheachconditionpriortotheexperimental runsandwereinstructedtodriveastheynormallywouldwhileminimizingthenumberofconehits. ComparedtoManual,theContconditionyieldedasignificantlyhigherdrivingspeed(onaverageby 7km/h),whereasContRFandBanddidnot.Allthreeguidanceconditionsyieldedbetterlane-keeping performancethanManual,whereasContandContRFyieldedlowerself-reportedworkloadthanManual. Inconclusion,continuoussteeringguidanceenticesdriverstoincreasetheirspeed,therebydiminishing itspotentialsafetybenefits.ItispossibletopreventBAwhileretainingsafetybenefitsbymakingadesign adjustmenteitherinlateral(Band)orinlongitudinal(ContRF)direction.

1. Introduction

AdvancedDriverAssistanceSystems(ADAS)supportdriversin taskssuchaslane keeping,car following,braking,and obstacle avoidance(e.g.,EichelbergerandMcCartt,2016;Fergusonetal., 2008).Generally,ADASaredevelopedwiththegoaltoincrease comfortandsafety,andnumeroussimulator-basedandtest-track studieshaveindeedshownsuchbeneﬁts(Bengleretal.,2014;Piao andMcDonald,2008).Inreality,however,theanticipatedsafety beneﬁtsare often diminished because drivers showbehavioral adaptation(BA),suchasdrivingwithahigherspeed,drivingcloser toaleadvehicle,performingdistractivenon-drivingtasks,or driv-inglongertripsascomparedtodrivingwithoutADAS(Elvik,2013; Hiraokaetal.,2010;MartensandJenssen,2012;Mehleretal.,2014; OECD,1990;Saad,2006).

∗ Correspondingauthor.

E-mailaddress:j.c.f.dewinter@tudelft.nl(J.C.F.deWinter).

Theabilitytoadaptisintrinsictohumans,andalthough adap-tationcanhavepositiveeffectsincertaincircumstances(e.g.,close followingmaybebeneﬁcialintermsofhighwaycapacity),most transportationresearchers are concernedwithadaptations that degradethesafetybeneﬁtsthatcanbeachievedwithADAS.For example,Sagbergetal.(1996)observedareducedtimeheadway among taxisequipped withanAnti-lockBraking System(ABS), comparedtotaxiswithoutABS.Theirresultssuggestthatthetaxi driversexploitedthefactthatABSreducesthebrakingdistanceby drivingclosertothevehicleinfront.SuchBAwithnegative con-sequenceshasbeenimplicatedinmanytypesofADASincluding notonlyABS,butalsoadaptivecruisecontrol(Panouetal.,2007), lanedeparturewarningsystems(Rudin-BrownandNoy,2002),and collisionavoidancesystems(JanssenandNilsson,1993).

ThepsychologicalmechanismsbehindBAareyettobe eluci-dated,butithasbeenpostulatedthatdriversexhibitatrade-off betweentwoconﬂictingmotivations,namelyarrivingata desti-nationintime (efﬁciency)versusavoiding dangeroussituations (safety),andwherebythedriver’slevelofsubjectiverisk(Näätänen

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T.Melmanetal./AccidentAnalysisandPrevention98(2017)372–387 373 and Summala,1974; Wilde, 2013,1998), taskdifﬁculty (Fuller,

2005), or time/safety margins (Gibson and Crooks, 1938; Van Winsumetal.,1999)areimportanthomeostaticvariables. Accord-ingly,driversadoptahigherspeedorashorterheadwaywhenthe drivingtaskbecomeseasier,lessrisky,orlesstemporally demand-ingdue to a changein theroad-vehicle-driversystem,suchas improvedenvironmentalconditions(e.g.,whenaddingroad light-ing;Assumetal.,1999)orincreasedassistanceinthecardriving task(e.g.,whenusingadaptivecruisecontrol;Dragutinovicetal., 2005).

ThemagnitudeoftheBAeffectisthoughttodependonthetime drivenwiththeADAS,thedriver’sattitudetowardstheADAS(e.g., whetherthedriverusesthesystemtodrivetothelimit),driver experience,andthedesignofADAS(Carstenetal.,2012;Saadetal., 2004;Sullivanetal.,2016).Onesupposedlyimportantpredictorof BAisthe‘noticeability’oftheADAS:IthasbeensaidthatADAS which causedirectlynoticeabledifferences inthe road-vehicle-driversystemsufferfromBAtoagreaterextentthanADASthat donot(Elviketal.,2004a,b).Thatis,ifdriversaremoreawarethat ADASinterfereswiththeirdrivingtask,itismorelikelythatthey willadapttheirbehavior.Forexample,largerBAeffectshavebeen demonstratedfordrivingwithanightvisionenhancementsystem thanforanon-visiblefeaturesuchaselectronicstabilitycontrol (e.g.,Hiraokaetal.,2010;Jiménezetal.,2008).Basedonthese ﬁnd-ingsitisexpectedthatADASthatcontinuouslyinteractwiththe driveraremorelikelytosufferfromBAthanforinstanceemergency systems.

OnetypeofADASthatisgrowinginpopularityandwhichmay beparticularlypronetoBAishapticsteeringguidance.The phi-losophyofhapticsteeringguidanceistousethecontrolinterface asamediumofcooperationbetweenthedriverandanintelligent vehicle,withtheaimtokeep thedriverinformedand involved inthedrivingtask,andtopreventtheout-of-the-loopproblems thatoccurinhands-freeautomateddriving(Abbinketal.,2012; Flemischetal.,2008;GrifﬁthsandGillespie,2005;Johnsetal.,2016; Marsetal.,2014a;O’Malleyetal.,2006;Soualmietal.,2014,see

Petermeijeretal.,2015bforareview).Concretely,haptic steer-ingguidancecontinuouslyassistsdriversinthesteeringtaskby providingtorquesonthesteeringwheelbasedonthetarget steer-ingbehaviorofanautomatedcontroller.Thedrivermay‘relax’his musclesandconformtotheappliedtorque,ormaysteeragainst it.Thus,thehumanandthemachinearejointlysteeringthecar, andthedegreeofsupportcanvaryalongacontinuousscalefrom driver-in-control(i.e.,thedriverhasaﬁrmgriponthesteering wheelandoverridestheappliedtorques)tomachine-in-control (i.e.,thedriverhasaverylightgriponthesteeringwheel). Pre-viousresearchhasshownbeneﬁcialeffectsintermsofimproved lane-keepingperformance,increasedsafetymargins,andreduced self-reportedworkloadfordrivingwithsteeringguidanceas com-paredtounsupporteddriving(Marsetal.,2014b; Mulderetal., 2012;O’Malleyetal.,2006).Insummary,duetothecontinuous interaction,increasedcontrollability,andreducedworkload,haptic steeringguidancemaybehighlysusceptibletoBA.

Recently,researchershavestartedtoinvestigatethehypothesis that the beneﬁcial effects of hapticguidance might be accom-paniedbyunintendedsideeffects.Adrivingsimulatorstudyby

Petermeijeretal.(2015a) foundthatdrivers showeddangerous steering oscillations, alsocalled ‘aftereffects’, after the steering guidancefailedpriortoenteringacurve.Aswithmostresearch onhaptic steering guidance (e.g., Grifﬁths and Gillespie, 2005; Mohellebietal.,2009;Mulderetal.,2012),thevehiclespeedin thisstudywasheldconstant.Itisyetunknownwhether partici-pantsdrivingwithhapticsteeringguidancewillshowBAinterms ofincreaseddrivingspeedwhentheguidancesystemisactiveand functioningnormally.TheonlystudyonthistopicfoundnoBAwith continuoushapticsteeringguidancecomparedtomanualdriving

(Marsetal.,2014b).Theauthorscomparedtwogroupsof partici-pantsinadrivingsimulator;onegroupdrovewithhapticsteering guidanceandtheotherdrovewithout.Nostatisticallysigniﬁcant speed differencewasfoundbetweenthetwogroups;however, duetothebetween-subjectdesign,thisparticularstudymayhave lackedthestatisticalpowertodetectadifferenceinmeandriving speed.

Theaimofthepresentresearchwastwofold.Asindicatedabove, hapticsteering guidanceis a noticeabletype of ADASand may thereforebehighlysusceptibletoBA.Ourfirstaimwastotestthe hypothesisthathapticsteeringguidancecausesBA operational-izedasdrivingspeed.DrivingspeedisaprimemeasureofBAwith strongimplicationsforroadsafety(Elvik,2013):Anincreaseof speedreducesadriver’stimetorespondinanemergencyscenario, increasestheprobabilityofbeinginvolvedinacrash,increasesthe driver’sseverityofinjuryifacrashoccurs,andincreasesthe sever-ityofinjuryof(vulnerable)roadusersthatarehitbythedriver (AartsandVanSchagen,2006;Elviketal.,2004a,b;Hedlund,2000). Oursecondaim,anticipatingonthehypothesizedBAcaused byhapticsteeringguidance,wastoinvestigatetheeffectiveness oftwotypesofhapticsteeringguidancethatweredevelopedto mitigatespeedingwithoutcompromisingthebeneficialeffectsof guidanceonsafetyandcomfort.Thefirstdesign(Band) incorpo-ratesalateralbandwidthwherebytheguidanceengagesonlywhen thevehicledeviatessubstantiallyfromthelanecenter.Thisdesign waspreviouslytestedataconstantdrivingspeedandwasfound tomitigateeffectsof over-relianceincase thesystemsuddenly failed(Petermeijeretal.,2015a).Theseconddesignisalongitudinal boundarysystem(ContRF)thatremovesthecontinuousguidance whendrivingfasterthanapre-definedspeedthreshold.These fun-damentallydifferentsystemswerebothhypothesizedtoreduce speeding:theBand conditionisequivalenttodriving manually unlessmakingalargelateralerror(therebyprovidingguidanceonly whenneeded),andtheContRFconditionprovidesguidancein nor-malconditions,butceasestofunctionwhenthedriveradoptsahigh speed(therebyremovingthebenefitsof guidancewhendriving fast).

Thisstudyevaluateddrivingbehaviorwhendrivingwith hap-ticsteeringguidancesystemsonanarrowroadwithconesalong theentireroad,comparedtounsupporteddriving.Priortoeach guidancecondition,drivers werefamiliarizedwiththeworking mechanismsofthesteeringguidance.ThiswasdonebecauseaBA effectmayappearonlyafteralearningperiodthatallowsdrivers todevelopamentalmodelofthesystem(Beggiato etal.,2015; Bianchi Piccininiet al.,2014;Martens and Jenssen,2012; Saad, 2006;Sullivanetal.,2016).Toenhancethefamiliarizationprocess, eachguidanceconditionwasexplainedtotheparticipantsindetail. Duringtheactualexperiment,driverswereinstructedtodriveas theynormallywouldwhileminimizingthenumberofconehits. Driversreceivedreal-timefeedbackontheirlane-keeping perfor-mance:aconehitwasindicatedbymeansofareddotappearing onthescreen.Theaugmentedfeedback(i.e.,reddots)andnarrow roadwereassumedtoenhancethesubjectiveriskandnoticeability ofthelane-keepingbeneﬁtsofthehapticguidance,andto discour-ageparticipantsfromdrivingatfullspeed(seeZhaietal.,2004for aspeed-accuracytrade-offinlanekeeping).Duetothesefactors,it wasexpectedthatifhapticsteeringguidancesuffersfromBA,this effectwouldbedetectedsooner.Toinvestigatethepotentialrisks ofspeeding,asharpcurvewasintroducedattheendofthetrial trajectory.

The aimof this study wasto investigatethe effectof three differentdesignsofhapticsteeringguidanceonspeeding.Itwas hypothesizedthat whendrivingwithcontinuoussteering guid-anceparticipantswouldadoptahigherspeedthanwhendriving manuallywithoutsupport.Furthermore,alateraland longitudi-nalalternativesteeringguidanceweretested.Bothdesignswere

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Fig.1.Simulatorenvironmentincludingthecarfrontandconehitwarning(i.e.,red dot).(Forinterpretationofthereferencestocolourinthisﬁgurelegend,thereader isreferredtothewebversionofthisarticle.)

hypothesizedtonotsufferfromspeedadaptationswhile retain-inga highlane-keepingperformance comparedtounsupported driving.Inordertoofferacomprehensiveevaluationand compar-isonbetweenconditions,eachdesignwasassessedwithrespectto ﬁvecategoriesofmeasures:speed,lane-keepingaccuracy,safety margin,workload,andsystemacceptance.

2. Method 2.1. Participants

Twenty-fourparticipants(7female)between23and52years old(M=28.0,SD=9.6)withnormalorcorrected-to-normalvision volunteeredfora drivingsimulatorexperiment. Allparticipants hadtheirdriver’slicenseforatleastﬁveyears.Inresponsetothe questionofhowoftentheydroveinthepast12months,6 partici-pantsreportedtodriveeveryday,4drove4–6daysaweek,5drove 1–3daysperweek,5droveonceamonth,3drovelessthanoncea month,and1never.Regardingmileageinthepast12months,the mostfrequentlyselectedresponsecategorywas1.001–5.000km (8respondents),followedby10.001–15.000km(6respondents), and25.001–35.000km(3respondents).Inanattempttomeasure participants’familiaritywithautomateddrivingsystems,weasked themwhethertheyhadeverheardoftheGoogleDriverlessCar. Themajorityofparticipants(21of24,or88%)indicated‘yes’tothis question,whichishigherthanapreviouslymeasuredglobal aver-ageof52%obtainedviaaninternationalInternetsurvey(Kyriakidis etal.,2015).

2.2. Apparatus

Theexperimentwasconductedinaﬁxed-basesimulatoratthe ControlandSimulation Department atthefaculty ofAerospace Engineering,Delft UniversityofTechnology.Thesteering wheel waselectronicallyactuatedbyaMOOGFCSECol8000SActuator runningat2500Hz.Vehicledynamicsweresimulatedwitha single-trackmodel (heavy sedan of 1.8mwide), havingan automatic gearbox,and a maximum speed of 160km/h. Thescenery was visualizedusingthreeLCDprojectorswithahorizontaland ver-ticalﬁeld-of-viewofrespectively180◦and40◦.Thevisualswere refreshedat50Hz,whereasthesimulationanddataloggingwere updatedat100Hz.Acarfrontwasvisualizedtofacilitateperception ofthecar’spositionrelativetotheroadboundaries.Carvibrations (‘roadrumble’)weresimulatedwithaseatshakerimplementedin thedriver’sseat.

2.3. Designsofhapticsteeringguidance

InadditiontotheManualcondition,whichsimulatednatural self-alignmenttorques,threedifferentmethodswereusedto pro-videsuperimposedhapticguidancetorquesonthesteeringwheel. Eachof thesethreemethods useda two-levelalgorithm which wasidenticaltopreviouslypublishedresearch(AbbinkandMulder, 2009;Mulderetal.,2008;Petermeijeretal.,2015a).Theﬁrstlevel calculatedthedesiredsteeringanglebasedonatwo-parameter modelthatpredictsthefuturelateralerrorbetweenthelane cen-terandthemiddleofthecar(efuture lat)andthefutureheadingerror

ofthecar(efuture heading)atalook-aheadtimeof0.7s.Theﬁrstlevel

wasidenticalforeachofthethreetestedguidanceconditions.At thesecondlevel,thetwovariablescalculatedintheﬁrststepwere convertedtofeedbacktorquesaccordingtoanalgorithmthatwas differentforeachofthethreeguidanceconditions.

2.3.1. Continuoussteeringguidance(Cont)

ThesystemContformsthebaselineforthehapticsteering guid-ance.Itprovidescontinuousfeedbacktorquesonthesteeringwheel usingthetwo-levelarchitecturedescribed above,forwhichthe secondlevelisshowninEq.1.

Tfeedback=

efuture lat·P+efuture heading·D

·Kf (1)

ThefeedbackgainswereidenticaltoMulderetal.(2008),with theforcefeedbackgain(Kf)=2.0,theproportionalgain(P)=0.08,

andthederivativegain (D) =0.9.

2.3.2. Continuoussteeringguidancewithareducingfeedback gain(ContRF)

The ContRFis a speed-dependent version of thecontinuous guidanceCont.Atspeeds below125km/h theContRFcondition functionsidenticallytoCont.Ifthespeedisgreaterthan125km/h, thefeedbacktorque(Tfeedback)linearlyreducestozero,andbeyond

speedsof130km/hitisidenticaltotheManualcondition(seeEq.

2).TheworkingprincipleofContRFistoremovetheguidancewhen drivingatexcessivespeeds,therebytheoreticallymitigatingspeed adaptation.Theboundaryof125–130km/hwaschosenbasedon resultsofpilotstudies.

Tfeedback=

⎧

⎪

⎨

⎪

⎩

efuturelat·P+efutureheading·D

·Kf forv < 125

efuturelat·P+efutureheading·D

·Kf· 130−v 5 for125 ≤v ≤130 0 forv > 130 (2)

2.3.3. Bandwidthguidance(Band)

Thebandwidthguidancewassimilartothe‘doublebandwidth’ systempreviouslyintroducedbyPetermeijeretal.(2015a).This designwasshowntomitigateover-relianceonhapticguidance, andmaybeaviablesolutiontospeedadaptationaswell.TheBand conditionhastwostatesofoperation.InState1theBandsystem doesnotexertanytorquewhenthevirtualcarisinthelane(i.e., absoluteefuturelatissmallerthan0.2m).Oncetheefuturelatexceeds

thisthreshold,thesystemswitchestoState2.InState2thesystem exertstorqueuntiltheabsoluteefuturelatisbelow0.1mofthelane

center,asshowninEqs.3and4.

Tstate1feedback=

0 for|efuturelat| < 0.2

efuturelat·P·Kf for|efuturelat| ≥ 0.2

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T_state2_feedback₌

0 for|efuturelat| < 0.1

efuturelat·P·Kf for|efuturelat| ≥ 0.1

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T. Melman et al. / Accident Analysis and Prevention 98 (2017) 372–387 375 Table1

Means(M),standarddeviations(SD),effectsizes(dz),andresultsoftherepeatedmeasuresANOVA(F,p)perdependentmeasure.

Manual(1) ContRF(2) Band(3) Cont(4) Pairwisecomparisons

1–2 1–3 1–4 2–3 2–4 3–4

M(SD) M(SD) M(SD) M(SD) pvalueF(3,69) p(dz) p(dz) p(dz) p(dz) p(dz) p(dz)

Speed

Meanspeed(km/h) 105.7(12.7) 106.4(9.0) 108.3(11.3) 113.3(13.1) p=0.001F=5.96 (0.22) (0.31) xx(0.74) (0.19) x(0.71) (0.43) Percentageoftimeabove125km/h(%) 9.8(22.2) 5.3(10.6) 13.4(24.2) 23.8(31.6) p=6.57×10−4_F₌_6.44 _(0.20) _(0.28) _x_(0.72) _(0.43) _xx_(0.76) _(0.38)

Lane-keepingperformance

Percentagetimeoff-road(%) 7.21(4.36) 3.32(2.24) 3.92(2.49) 3.40(2.67) p=2.51×10−10_F₌_22.68 _xxx_(1.58) _xxx_(1.07) _xxx_(1.36) _(0.37) _(0.00) _(0.32) Meanabsolutelateralerror(m) 0.087(0.014) 0.074(0.010) 0.086(0.011) 0.074(0.012) p=1.08×10−11F=27.10 xxx(1.47) (0.01) xxx(1.13) xxx(1.33) (0.06) xxx(1.31) Maximumabsolutelateralerror(m) 0.47(0.15) 0.33(0.06) 0.37(0.14) 0.38(0.24) p=2.17×10−7F=14.42 xxx(1.32) xx(0.75) xxx(1.22) (0.35) (0.04) (0.24) Meanlanereturntime(s) 3.19(1.64) 2.03(1.16) 2.00(1.07) 1.72(0.73) p=4.41×10−6_F₌_11.22 _xx_(0.85) _x_(0.70) _xxx_(1.35) _(0.02) _(0.28) _(0.22)

Workload

Meanabsolutefeedbacktorque(Nm) 0.19(0.03) 0.06(0.03) 0.21(0.04) p=1.95×10−22_F₌_179.15 _xxx_(3.38) _x_(0.60) _xxx_(3.90) Steeringreversalrate(Hz) 0.73(0.23) 0.49(0.17) 0.64(0.17) 0.51(0.17) p=6.04×10−14_F₌_35.31 _xxx_(2.09) _(0.57) _xxx_(1.58) _xxx_(1.45) _(0.17) _xx_(0.83) NASA-TLX(%) 47.78(12.12) 33.26(11.70) 42.19(16.07) 32.81(13.19) p=2.64×10−6_F₌_11.74 _xxx_(1.22) _(0.42) _xx_(0.86) _(0.58) _(0.00) _(0.50) Meanabsolutedrivertorque(Nm) 0.75(0.07) 0.72(0.06) 0.75(0.06) 0.76(0.08) p=0.047F=2.78 (0.37) (0.06) (0.16) (0.37) x(0.61) (0.20)

Systemacceptance

Satisfactionscale(−2,2) 0.88(0.52) 0.52(0.69) 0.79(0.73) p=0.076F=2.72 (0.45) (0.10) (0.31) Usefulnessscale(−2,2) 0.98(0.35) 0.83(0.44) 0.92(0.50) p=0.410F=0.92 (0.23) (0.12) (0.17) x:p<0.05,xx:p<0.01,xxx:p<0.001.

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Fig.2.Fromtoptobottom:First:curvature(1/curveradius)ofthetrajectory.Second:meanspeedacrossallparticipantspercondition.Thehorizontaldashedlinesindicate thespeedthresholdsoftheContRFcondition.Third:cumulativenumberofconehitsforallparticipantscombinedpercondition.Coneswere8mapart.Theconehitresults fortheContandContRFconditionsareoverlapping.Fourth:thepercentageofparticipantswhodrovefasterthan125km/hpercondition.

2.4. Roadenvironment

Allparticipantsdroveeachtrialonthesamenarrowsingle-lane road(2.2mwideand13.9kmlong),drivinginoneofthefour con-ditions(Manual,ContRF,Band,orCont).Theroadwidthof2.2m andcarwidthof1.8mallowed0.2monbothsidesofthecarbefore aconewouldbehit.Thefirst12km ofthetrajectorycontained threetypesofcurveswithinnerradiiof1500m,750m,and500m, respectively.Thisroaddesignassuredthatnobrakingwasrequired beforecurves(i.e.,curvescouldbetakenfullthrottle),andthatthe lateralaccelerationsstayedatalltimesinthelinearregionwhere thesimulatedcardynamicsarevalid(Dixon,1988).Toinvestigate thedownsidesofpotentialspeeding,asharpcurvetotherightwas introducedattheendofthetrajectory(innerradiusof300mand 300mlong)forwhichthephysicallymaximumspeedwas approxi-mately125km/h.Thatis,drivingfasterthan125km/hwouldresult inthecarveeringofftheroadontheoutsideofthecurve.Before eachexperimentaltrial,participantswerefamiliarizedwiththe guidancebymeansofatrainingrun.Theroadsofthetrainingruns wereidenticaltothefirstthreequarters(10.5km)oftheroadinthe subsequentexperimentaltrials.Speedperceptionwasenhanced bymeansoftreesalongsidetheroad.Coneswereplacedalongthe entireroadwithadistanceof8mbetweencones.Aconehitwas visualizedwithareddotonthesidewherethecarhitacone(Fig.1). Noon-roadobstaclesandnotrafficweresimulated.

2.5. Experimentaldesign

The four conditions were presented in a counterbalanced within-subjectsdesign.Priortotheexperimentparticipantsread and signed an informed consent form, explaining thepurpose, instructions, and procedures of the study. Participants were informedabouttheavailabilityofeachsteeringguidanceandwere toldtokeep bothhands onthesteering wheel ina ten-to-two positionatalltimes.Participantswereinstructedtodriveasthey normallywouldandtominimizethenumberofconehits.Nospeed advicewas given and any questions regarding speed were not answered.

Beforeenteringthedrivingsimulator,participantscompleteda questionnaireregardingtheirdrivingexperienceaswellasaDriver BehaviourQuestionnaire(DBQ)containingsevenviolationitems (DeWinterandDodou,2016).Apreviousmeta-analysisindicated thattheDBQviolationsscalehasamoderatelystrongrelationship (r=0.24)withrecordedmeasuresofspeedandspeeding(DeWinter etal.,2015).

Priortoeachtrial,atrainingrunofapproximatelysixminutes wasperformed(i.e.,ﬁxeddistanceof10.5km).Sixminuteswas consideredsufﬁcienttobecomefamiliarwithaguidancesystem (McGeheeetal.,2004).Toenhancethefamiliarizationprocess,two actionsweretaken.First,theexperimenterexplainedthe work-ingmechanismofeachguidancesystem,butnottheunderlying hypothesis.Second,participantswerestimulatedtoexperiencethe guidance’sworkingmechanismbyallowingthemtodrivewithout negativeconsequences(i.e.,conehitswerenotcountedbutstill visualized).Toemphasizetheimportanceofunderstandingeach guidancecondition,theexperimenterorallymotivatedthedriver toexperiencethemechanismofeachguidanceconditionatleast once.ForContRF,thismeantthatthedrivingspeedwasatleast onceabove130km/h,sothattheparticipantscouldfeelthe steer-ingguidancebeingabsentwhendrivingfast.ForContthiscame downtodrivingwithlargelateralerrorstofeelthefeedbackforce increasing,andforBanddriverswereaskedtoletgoofthesteering wheeltoobservethattheguidanceturnsonjustbeforehittingthe cones.

Aftereachtrial,participantswereinformedaboutthenumber ofconehitsandwererequestedtostepoutofthesimulatorfora 5minbreakandtoﬁlloutthreequestionnaires:aNASATaskLoad Index(NASA-TLX)(HartandStaveland,1988)toassessworkload, anacceptancequestionnaire(VanderLaanetal.,1997)toassess satisfactionandusefulnessoftheguidance,andasimulator sick-nessitem.Inthelatter,participantsneededtoindicatewhether theywerefeelingsimulatorsicknessonascalefrom1to6(1=not experiencinganynausea,nosignofsymptoms,2=arising symp-toms(likeafeelingintheabdomen),butnonausea,3=slightly nauseous,4=nauseous,5=verynauseous,retching,6=vomiting). Aresponseof4orhigherwouldstoptheexperiment.Thetotal

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T.Melmanetal./AccidentAnalysisandPrevention98(2017)372–387 377

Fig.3. Theparticipants’meandrivingspeeds(km/h)fortheContRFconditioncomparedtoContcondition.Thebluelineindicatesequalspeedforbothconditions.The differentmarkersdesignatethenumberoftimesaparticipantexceededthe125km/hspeedthresholdwhendrivingwithContRF.18outofthe24participantsdrovefaster withContthanContRF.10participantsexperiencedthereductionofContRFguidance(circlesandtrianglescombined).

experiment,includingﬁllingoutallquestionnaires,took approxi-mately1.5hperparticipant.

2.6. Dependentmeasures

Thedatameasuredontheﬁrstandlast400mofthetrajectory werediscarded,becauseoftheinitialaccelerationsandﬁnal decel-erationsofthesimulatedvehicle.Thisresultedina13.1kmlong trajectorythatwasusedintheanalysis.Thedependentmeasures thatwerecalculated werecategorizedintospeed, performance, workload,safety,andsystemacceptance.

2.6.1. Vehiclespeed

MeanSpeed(km/h).ThiswastheprimaryBAeffectofinterest. PercentageofTimeAbove125km/h(%).The125km/hthreshold correspondstothelowerspeedthresholdoftheContRFguidance.

2.6.2. Performance

PercentageTimeOff-Road(%),whichistheamountoftimethat thecardrivesoutsidetheconeboundaries(i.e.,themiddleofthe cardeviatesmorethan0.2mfromthelanecenter),expressedasa percentageofthetotaldrivingtime.

MeanandMaximumAbsoluteLateralError(m).Theabsolute lat-eralerrorwasdeﬁnedasthedistancefromthemiddleofthecar towardsthecenterofthelane.Theabsolutelateralerrorandtime off-roadaremeasuresoflane-keepingaccuracy.

MeanLaneReturnTime(s).Thismeasurerepresentsthetime fromthemomentthecarcrossestheconeboundary(i.e.,centerof thecarwithin0.2mofthelanecenter)tothemomentofreturning thecarbackwithintheconeboundariesforatleast5s.Thisserves asmeasureofcontrollability.

2.6.3. Workload

NASA-TLX Subjective Workload (%). After each trial, partici-pantswereaskedtoindicatetheirworkloadonsixitems:Mental Demand,PhysicalDemand,TemporalDemand,Performance,Effort, andFrustration.Itemswerescoredona21-pointscalefromvery lowtoveryhigh,exceptforPerformance,whichrangedfrom per-fecttofailure.Theoverallworkloadwascalculatedasthearithmetic meanofthesixitems(Cain,2007;HartandStaveland,1988).

Steering ReversalRate (reversals/s).Thesteering reversalrate wasdeﬁnedasthenumberoftimesthatthesteeringwheelwas reversedbyamagnitudegreaterthan2deg(McLeanandHoffmann, 1975).Itwascalculatedbydeterminingthelocalminimaand max-imaofthesteeringwheelangle,andifthedifferencebetweentwo adjacentpeakswasgreaterthan2deg,itwascountedasareversal. Thismeasurecanbeconsideredanobjectiveindicatorofworkload (Johanssonetal.,2004).

MeanAbsoluteFeedbackTorque(Nm).Thefeedbacktorqueisthe torquesuperimposedonthedriverbythehapticsteering guid-ance.Ahighmeanfeedbacktorquemeansthatmoreguidancewas applied.

Mean Absolute Driver Torque(Nm). The driver torque is the torqueappliedbythedriveronthesteeringwheel,andwas con-sideredasameasureofthedriver’sphysicaleffort.

2.6.4. Safetymargins

Median Time toLine Crossing (TLC)(s). Themedian TLC was approximatedusingthelateralspeedandlateralacceleration(Van Winsumetal.,2000).TheTLCwassetat0swhendrivingoutside thelaneboundaries.BecauseTLCvariesmuchduringlane keep-ing,anadditionalﬁne-grainedanalysiswasperformedbybinning theTLCvaluesintofourgroupsofsafetymargins:outofbound (TLC=0s),lowsafetymargin(0s<TLC_≤2s),moderatesafety mar-gin(2s<TLC≤4s),andhighsafetymargin(TLC>4s).TheseTLC binswereroughlybasedonpreviousstudieswhichhaveassessed

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Fig.4.Speeddistribution(km/h)ofallparticipantscombined.Thebinwidthis5km/h.Thefractionisplottedinthemiddleofeachbin.Theredandgreenlinesindicatethe speedthresholdsofContRF.Thesumofallfractionsequals1foreachcondition.(Forinterpretationofthereferencestocolourinthisﬁgurelegend,thereaderisreferredto thewebversionofthisarticle.)

TLCortime-to-collision(TTC)intermsofsubjectiverisk(Kondoh etal.,2006),criteriafordriverimpairment(Brookhuisetal.,2003), andself-chosenocclusiontimes(Godthelpetal.,1984).

2.6.5. Systemacceptance

Anacceptance questionnaire(VanderLaanetal.,1997)was usedtoassesssystemacceptanceontwodimensions,ausefulness scaleand an affectivesatisfaction scale.Thisquestionnaire con-sistedofnineitems,scoredbetween+2and−2.Theusefulnessscale wasobtainedbytakingtheaveragescorefortheitems: Useful-Useless, Bad-Good*, Effective-Superﬂuous, Assisting-Worthless, andRaisingAlertness-Sleep-inducing.Thesatisfactionscalewasthe averagescorefortheitems:Pleasant-Unpleasant,Nice-Annoying, Irritating-Likable*, and Undesirable-Desirable*.Appropriatesign reversalswereconductedfortheitemsindicatedwithanasterisk.

2.7. Statisticalanalyses

Foreachdependentmeasure,amatrixof24×4numberswas obtained(24participantsand4conditions).Thismatrixwas rank-transformedaccordingtoConoverandIman(1981)toaccountfor possibleviolationsoftheassumptionofnormalityassociatedwith parametrictests.Therank-transformedmatrix,consistingof num-bersfrom1to96,wassubmittedtoarepeatedmeasuresANOVA withthefourconditionsaswithin-subjectsfactor.Bonferroni cor-rectionswereappliedtothesixpairwisecomparisonsbetweenthe conditions.Thedzeffectsizesforpairwisecomparisonswere

cal-culatedusing Eq.5 (Faul etal.,2007), where _x−y is themean ofthe differenceand x−y is thestandard deviation ofthe

dif-ference.Redundancies/associationsbetweendependentmeasures wereassessedbymeansofSpearmanrank-ordercorrelation coef-ﬁcients.

dz= |x−y|

x−y (5)

3. Results

During the training run, all participants had experienced the mechanism of each guidance condition at least once. This exploratorybehaviorduringtrainingwasnotanalyzed.

3.1. Vehiclespeed

Table1showsthemeansandstandarddeviationsforall depen-dentmeasures,theresultsofrepeatedmeasuresANOVA,andthe pairwisecomparisons.Participants’meanspeedsweresignificantly different between the four conditions, F(3,69)=5.96, p=0.001. WhensupportedbyCont,participantsdrovesignificantlyfaster(on averageby7km/h,withmediumeffectsizes)comparedto Con-tRFandManual.Nostatisticallysignificantspeeddifferenceswere observedbetweenManualandthetwoguidanceconditionsthat werehypothesizednottosufferfromBA(i.e.,ContRFandBand).

Fig.2showsthemeanspeed,cumulativenumberofconehits,and percentageofparticipantsexceedingthe125km/hthresholdasa functionoftravelleddistance.Itcanbeseenthatparticipantsinall fourconditionsdrovefasteronthelongstraightthanontheother partsoftheroute.ThedifferenceinmeanspeedsbetweenContand thethreeotherconditionsoccurredbothonstraightsandincurves (Fig.2).

Theaverage(SD)completiontimes ofthe13.1km trajectory were440s(52),435s(39),428s(45),and411s(48),forManual, ContRF,Band,andCont,respectively.Notethatthemeanspeed andcompletiontimesshowaperfectnegativeSpearman correla-tion(␳=−1),andsothecompletiontimeswerenotsubjectedto statisticaltests.

Participants in the ContRFcondition drove slower than the 125km/hthresholdforonaverage94.7%ofthetime,effectively resultinginanidenticalguidanceasthecontinuousguidance.A majorityof14outof24participantsintheContRFconditionnever exceededthe lower speed thresholdof 125km/h (Fig.3).Even thoughContRFandConteffectivelywereidenticalconditionsfor mostofthe drivingtime,the speeddistributionbetweenthese twoconditionswasnotablydifferent(Fig.4).Fig.4showsadrop fortheContRFjustbeforethelowerspeedthreshold,whereasfor

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Fig.5. MeanscoresontheNASA-TLX.x:p<0.05,xx:p<0.01,xxx:p<0.001.

theContcondition,nosuchdropcanbeseen.Fig.4furthershows thatalargerfractionofthespeeddistributionoftheCont condi-tionislocatedabovethe125km/hthresholdascomparedtothe threeotherconditions,aneffectthatisstatisticallysigniﬁcantwith respecttotheManualandContRFconditions(Table1).

3.2. Performance

All three steering guidance conditions yielded strongly improvedlane-keepingperformancecomparedtotheManual con-dition,intermsofalowertimeoff-road,lowermaximumabsolute lateralerror,andlowerlanereturntime(Table1;Fig.2).Bandand Manualyieldedsigniﬁcantlyhighermeanabsolutelateralerrors thanContRFandCont(Table1),whichmaybecausedbythefact thatBandprovided noguidanceforonaverage84%ofthe driv-ingtimeandthereforemostlyfunctionedidenticallytotheManual condition.Nostatisticallysigniﬁcantdifferencesinlane-keeping performancewerefoundbetweenContRFandCont.

3.3. Workload

Table1showsthattheself-reportedworkload(NASA-TLXscore) andobjectiveworkload(steeringreversalrate)weresignificantly higherforManualthanforContandContRF.Foreachofthesix NASA-TLXitems,theManualconditionyieldedhigherworkload scoresthantheContandContRFconditions,withstatistically sig-nificanteffects fortheMental Demand,Performance,andEffort items(Fig.5).Furthermore,theBandconditionyieldedsignificantly higherMentalDemandthantheContcondition.

Themeanfeedbacktorqueprovidedbytheguidancewas signif-icantlydifferentbetweenallconditions.Bandyieldedsigniﬁcantly lessfeedbacktorque(M=0.06Nm)thanthecontinuousguidance conditions(ContRFM=0.19NmandContM=0.21Nm).No feed-backtorquewasappliedduringtheManualcondition.Moreover, theresultsshowedthatlowerphysicaleffort(drivertorque)was obtainedfordrivingwithContRFthanfordrivingwithCont guid-ance.

3.4. Safetymargins

SubstantiallyhighersafetymarginsintermsofmedianTLCwere foundforContRFandContcomparedtoManualandBand(Table2). Additionally,slightlyhighersafetymarginswereadoptedfor Con-tRFthanCont,althoughnotstatisticallysigniﬁcant(p=0.071).In theContRFandContconditions,participantsdrovelessoftenwith alowsafetymarginbutmoreoftenwithahighsafetymargin,as comparedtotheManualandBandconditions.Overalldrivingwith

ContRFandContresultedinthehighestsafetymarginsintermsof medianTLCandTLC>4s.

3.5. Systemacceptance

Table1showsalowersatisfactionscoreforBandthanfor Con-tRFandCont,althoughnotstatisticallysigniﬁcant(F(2,46)=2.72, p=0.076).Nodifferencewasfoundfortheusefulnessscaleeither (F(2,46)=0.92,p=0.410).

3.6. Sharpcurve

Theperformancemeasureswerecalculatedseparatelyforthe 300mlongsharpcurvesegmentattheendofthetrajectory.The resultsdidnotshowsigniﬁcantdifferencesinlane-keeping perfor-mancebetweenthefourconditions.Nevertheless,thetwolargest absolutelateralerrors(1.4mand0.6m,respectively)werefound forthetwoparticipantsdrivingintheContcondition.Thesetwo participantsadoptedrelativelyhighspeedsattheentranceofthe sharpcurveof135km/h(rank1/96)and117km/h(rank12/96), respectively.Fig.6shows(1)thecurvature,(2) themeanspeed (km/h), (3)themeanabsolutelateralerror(m),(4)themedian TLC(s),and(5)thestandarddeviationofthesteeringwheelangle amongtheparticipantsasafunctionoftravelleddistanceinthe sharpcurve.Thesharpcurveresultedintwodistinctpeaksinthe meanabsolutelateralerror.Theﬁrstpeak(about 10mintothe curve)iscausedbymostparticipantsslightlycuttingthecurveon theinside,whereasthesecondpeak(70mintothecurve)ismainly causedbymostparticipantsveeringtotheoutsideofthecurve. Criticalsafetymargins(medianTLC<1s)wereobservedforall con-ditionswhenenteringthesharpcurve.Forcontinuousguidance, therewerelargesteeringangledifferencesbetweenparticipants. Largemeanmaximumabsolutelateralerrors wereobtainedfor theCont(0.20m)andManual(0.19m)conditionscomparedtothe ContRF(0.16m)andBand(0.16m)conditions.

3.7. Supplementaryanalyses

TheSpearmancorrelationcoefficientsbetweenthemeanspeed andthemeanabsolutelateralerrorwere0.40,0.31,0.14,and0.11 fortheManual,ContRF,Band,andContconditions,respectively (see Appendix A). This suggeststhat driving speed moderately yetconsistentlyinfluencedtaskperformance,presumablydueto a speed-accuracytrade-off(cf.Zhaiet al.,2004).In the simula-torsicknessitem,noneoftheparticipantsresponded4(nauseous) orhigher,andthuseveryonefinishedtheexperiment.Specifically, thenumberofresponsesbeing1(notexperiencinganynausea),2

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Fig.6. Meanspeed(km/h),meanabsolutelateralerror(m),medianTLC(s),andstandarddeviationofthesteeringwheelangle(deg)amongtheparticipantsasafunction oftraveleddistanceinthesharpcurve.Thetopﬁgureshowsthecurvature(i.e.,1/radiusinmeters).

(arisingsymptoms),and3(slightlynauseous) were61,27, and8, respectively.TheSpearmancorrelationcoefficients betweenthe meanspeedontheonehand,andthemeanDBQviolationsscore, thedrivingfrequency,andthemileageinthelast12months,onthe other,rangedbetween−0.06and0.25(AppendixA).When averag-ingthespeedacrossthefourconditions,theDBQ-speedcorrelation was0.24,whichisinlinewithapreviouslypublishedmeta-analysis (DeWinteretal.,2015)butnotsignificantlydifferentfromzero (p=0.262).Thesefindings suggestthatthedegreeofbehavioral adaptationisnotassociatedwiththesepersonalcharacteristicsin apracticallysignificantmanner.

4. Discussion 4.1. Mainresults

Theaimofthisstudywastoinvestigatetheeffectsofhaptic steeringguidanceonspeeding,andtoevaluatetwovariationsof hapticdriversupportthatweredesignedtomitigatesuch speed-ing.Tounderstanddrivingbehaviorbetter,wealsoassessedthe effects onlane-keepingperformance, safety margins,workload, anddriveracceptance.ThemeanspeedsintheManual,ContRF, Band,andContconditionswere105.7,106.4,108.3,and113.3km/h, respectively,withstatisticallysignificantdifferencesbetweenCont andManualandbetweenContandContRF.Theseresultsconfirm thehypothesisthat continuoushaptic steeringguidancecauses driverstodrivefaster,whichdiminishesthesafetybenefitsofthis assistivetechnologyascomparedtofixed-speedsimulatorstudies. TheresultsareinaccordancewithresultsfromearlierBAstudies regardingothertypesofADAS,suchasobstacleavoidancesystems andnightvisionenhancementsystem(Hiraokaetal.,2010;Janssen andNilsson,1993).

Thelaterallyadjusted(Band)andlongitudinallyadjusted (Con-tRF)guidanceconditionsthatweredesignedtomitigatespeeding werebothsuccessfulinachievingthisobjective,whileretaininga highlane-keepingperformance.ComparedtotheManualandBand

conditions,participantsdrivingwithContandContRFwere bet-terabletocenterthecarinthemiddleoftheroadatareduced workload.Theresultsfurthershowedthatcomparedtothe Man-ualcondition,Contprovidedincreasedsafetymarginsintermsof TLCdespiteahighermeanspeed(whichcorrelatesnegativelywith TLC,seeSupplementarymaterials),signifyingthatdrivers could affordtosafelyincreasetheirspeedduetothebeneﬁtsofferedby thehapticsteeringguidance.ContRFhadevenslightlyhighersafety marginsthanCont,possiblyduetothelowerdrivingspeedinthis condition.

4.2. EffectivenessofContRFinpreventingspeeding

EventhoughContandContRFwereeffectivelyidenticalsystems for95%ofthedrivingtime,ContRFsuccessfullypreventedspeed adaptation.TheContRFthresholdof125km/hwaswellabovethe averagedrivingspeedof108.4km/h,and14ofthe24participants neverexperiencedthereductionofguidanceduringtheirtrials(i.e., theirspeedwasalwaysbelow125km/h).Theeffectivenessofthe ContRFguidancedespitethefactthatdriversonlyrarely experi-enceditsuggeststhatBAdoesnotnecessarilymanifestitselfas afunctionofcurrentADASinterventionandvisibilitybutrather thatexpected(loss)offunctionalityoffersaremedyagainstBA.The effectsmaybeexplainedwiththehelpofthetheoriesofsafety marginsandriskcompensationintroducedabove:arguably,drivers intheContconditionspeededupcomparedtotheManual condi-tionbecausetheguidanceloweredtheirsubjectiveriskleveland increasedsafetymargins.WithContRF,participantsdidnot expe-riencesuchareductioninsubjectiveriskbecausetheyhadbeen instructedandtrained thatthebeneﬁtsofthis assistive system woulddisappearwhendrivingfast.

TheworkingmechanismoftheContRFsystemmaybefurther explainedbymeansofananalogypreviouslyintroducedbyWilde (1998):ontheonehandengineersmakedrivingsaferbyoffering forgivenessincaseofanaccident(e.g.,seatbelts,airbags, crash-worthycar design, etc.),yet onthe otherhand theymake the

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T.Melmanetal./AccidentAnalysisandPrevention98(2017)372–387 381 Table 2 Means (M ), standard deviations (SD ), effect size s (dz ), and results of the repeated measures ANOVA (F , p ) for time to line crossing (TLC). Manual (1) ContRF (2) Band (3) Cont (4) Pairwise comparisons 1–2 1–3 1–4 2–3 2–4 3–4 M (SD ) M (SD ) M (SD ) M (SD ) p value F (3,69) p (dz ) p (dz ) p (dz ) p (dz ) p (dz ) p (dz ) Median TLC (s) 1.32 (0.48) 2.09 (0.67) 1.36 (0.46) 1.89 (0.65) p = 4.73 × 10 − 17 F = 48.86 xxx (1.97) (0.07) xxx (1.56) xxx (1.90) (0.56) xxx (1.33) Percentage low safety margin (0 s < TLC ≤ 2 s) (%) 54.20 (6.59) 46.87 (7.01) 56.32 (6.78) 49.27 (7.57) p = 1.61 × 10 − 13 F = 33.67 xxx (1.79) (0.45) xx (0.75) xxx (2.06) x (0.63) xxx (1.10) Percentage moderate safety margin (2 s < TLC ≤ 4 s) (%) 14.08 (2.68) 15.97 (1.47) 13.90 (2.26) 15.51 (1.75) p = 2.48 × 10 − 7F = 14.24 xx (0.83) (0.23) x (0.62) xxx (1.20) (0.31) xxx (1.10) Percentage high safety margin (TLC > 4 s) (%) 24.51 (6.46) 33.84 (6.84) 25.86 (5.68) 31.82 (7.22) p = 2.07 × 10 − 16 F = 45.83 xxx (2.46) (0.23) xxx (1.66) xxx (1.80) (0.52) xxx (1.03) x: p < 0.05, xx: p < 0.01, xxx: p < 0.001. Note : The results for TLC = 0 are identical to the time off-road results in Table 1 .

consequencesofdangerousbehaviormoresevere(e.g.,by imple-mentingspeedbumps).Asimilartypeofconﬂictingsafetypolicy appliestotheContRFsystem,whereontheonehanddrivingsafety isenhancedbyofferingguidanceonthesteeringwheel,yet speed-ing is discouraged bytaking away the sameguidance. Perhaps peopleneedsuchopposingmotivationtouseADASinaresponsible manner.

Atpresent,itisdifﬁculttoestablishwhethertheeffectivenessof ContRFiscausedbyconscious(‘explicit’)mechanismsorby uncon-scious(‘implicit’)mechanisms(cf.Evans,2008).Regardingimplicit mechanisms,itmaybearguedthattheContRFsystemgives physi-calfeedbackabouttheobjectivelevelofrisk(speed)atasubcortical neuromuscular level(cf. Abbinket al.,2011).Loosely speaking, becauseparticipantsreceivedthehapticfeedbackdirectlyontheir hands,theymayhavereﬂexivelyandhabituallyrespondedtothis feedback,withoutbeingconsciouslyawareofthis.Alternatively, participantsmayhavebeenexplicitlyawareofthefactthatthe hapticfeedbackdisappearswhendrivingfast,eitherthroughthe trainingtheyhadreceivedorthroughthefactthatthe disappear-anceoffeedbackisemotionallyarousingandleavesaconsciously accessible trace in memory. Futureresearch should investigate which implicitorexplicitmechanismsareunderlyingfactorsin BApreventiontechnologies.Forexample,togainmoreinsightinto theexplicitfactorsbehindabehavioralchange,averbalprotocol methodcouldbeused(Banksetal.,2014).

4.3. SpeedparametersoftheContRFsystem

TheContRFsystemdoesnotnecessarilyrepresenttheoptimal solutiontopreventBAandmayberefinedinvariousways.Inthis study,thelowerspeed thresholdwassetfairlyhigh(125km/h) withthereductionoccurringoverarelativelysmallspeedrange (125–130km/h),inordertokeepthebenefitsofcontinuous guid-anceandtoensureanoticeablefeedbackreduction.Thequestion remainswhatwouldhappenifonechangesthesedesign param-eters. For example,it ispossibletolower thespeed thresholds towardstheaveragespeedinmanualdriving,sothatalmostall par-ticipantshavetomakeadecisionbetweenusingguidanceversus adoptingahighspeed.Similarly,itispossibletoconceiveasystem thatreducestheguidanceoverabroadspeedrangesothateach driverhastoachieveatrade-offalongacontinuumbetweensafety andefficiency.Thesetopicscanbeaddressedinfutureresearchto improvetheunderstandingofBApreventingtechnologies.

4.4. Effectivenessofthebandsystem

In accordance withpreviousresearch,drivingwithboth the continuousguidanceandthebandwidthguidancewasfoundto improvedrivers’lane-keepingperformancecomparedtomanual driving(Flemischetal.,2008;Kienleetal.,2012;Marchal-Crespo et al.,2010;Petermeijeret al.,2015a).More speciﬁcally,in our study,theBandconditionyieldedsubstantiallyimprovedtime off-roadcomparedtotheManualcondition,butitdidnotimprovethe meanabsolutelateralerror.Furthermore,nostatisticallysigniﬁcant differenceinoverallself-reportedworkloadwasfoundbetween ManualandBand.Theseeffectscanbeexplainedbythefactthat BandandManualwerelargelyidenticalwhendrivinginsidethe lane,withnohapticguidanceofferedin theBandconditionon averagefor84%of thetime.Theworkingprincipleof theBand systemcorrespondstomarketedlane-keepingassistancesystems (e.g.,Daimler,2013;VolvoCarCorporation,2015),whichalsoguide thedriverawayfromlaneboundariesratherthantowardsthelane centerastheContsystem.

ThefactthattheBandsystemcloselyresemblesmanual driv-ingforthemajorityofthedrivingtimemaybethereasonthat itpreventsBAintheformofspeedingandaftereffectswhenthe

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systemfailsordisengages.Thelatterstatementisinlinewitha previousfieldstudyconductedbyBreyeretal.(2010),whichdid notfindevidenceofadverseaftereffectsforacorrectivesteering systemthatwasdeactivatedafteraprolongedexposuretothe sys-tem.OurbandwidthconditionfunctionedsimilarlytoBreyeretal.’s correctivesteeringsystembysupportingthedriverwhen cross-inga laneboundary,yetallowingthedrivertosway withinthe laneboundaries.Insummary,thesatisficingapproach(i.e., keep-ingthedriverfullyinchargewhendrivinginthelane;seealso

Goodrichetal.,2000;Summala,2007),asopposedtothe optimiz-ingapproach(i.e.,continuousguidance),hastheadvantagethatno BAoccursandnoadversesteeringaftereffectsareevokedduringa suddentransitionofcontroltomanualdriving(Breyeretal.,2010; Petermeijeretal.,2015a).However,thisoccursatthecostofan ele-vatedworkloadandworselane-centeringperformancecompared tocontinuousguidance.

4.5. Experimentalconditionsthatgiverisetobehavioral adaptation

Thespeedadaptationof7km/hforcontinuousguidanceis dif-ferentfrom findingsby Marsetal. (2014b)who didnotfind a statisticallysignificantspeeddifferencebetweenagroupof12 par-ticipantsdrivingwithhapticsteeringguidanceandanothergroup of12participantsdrivingmanually.First, thefocusof theMars etal.studyisdifferentfromours:whereasMarsetal.measured howdrivingspeedevolveswithpracticeacrosstwelve4.3kmlaps over twodays, thepresent studyinvestigated more immediate speed adaptations in 24.4km of driving percondition(10.5km trainingplusanexperimentaldriveof13.9km).Second,although abetween-subjectsdesignismethodologicallystrongbecauseit preventscarry-overeffectsbetweenconditions,largeindividual differencesinspeedmakeitlesslikelytoobservestatistically sig-nificanteffects in a between-subjects design as compared to a within-subjectdesign.Third,inourexperiment,theroadwas nar-rowandsalientconcurrentperformancefeedbackwasprovided bymeansofareddotwhenhittingacone,whereasinthestudy byMarsetal.thiswasnotthecase.Duetothenarrowroadand knowledge-of-resultsfeedback,drivers canbeassumed tohave beenwellawareoftheimprovedlane-keepingperformance facili-tatedbyhapticguidance.Thenoticeabilityoftheguidancebenefits combinedwiththeextendedfamiliarizationperiodcouldexplain whystrongspeeddifferenceswereobservedinthepresent1.5h longexperiment.

4.6. Risksofbehavioraladaptation

Despiteitshigher speed,Contyielded highersafetymargins andbetterlane-keepingperformance(intermsoflowertime off-road,maximumlateralerror,andabsolutelateralerror)thanthe Manualcondition.Thisraisesthefundamentalquestion:whyisBA regardedasundesirableifdrivingperformanceandsafetymargins areactuallyimproved?Whenhapticsteeringguidanceiswithin its operational limits it can indeed be considered favorable to unsupporteddriving.However,whenhapticsteeringguidanceis outsideitsoperationallimitsahigherspeedimplieshighercrash risk,higherinjuryseverity,andlowertimetorespond.Infact,for agivenspeedthecrashriskmaybeevenworsethaninmanual drivingduetotheaforementionedaftereffects(Petermeijeretal., 2015a).Theadverseeffectsofspeedingwereillustratedbyalarge laneexitwhenenteringasharpcurveathighspeed(Fig.6). Hav-ingtheunrealistictrustthathapticsteeringguidance(oranyother intelligentvehicleorautomateddrivingsystemforthatmatter)can anticipatesharpcurvesatalltimes,mayleadtodangerous situa-tions.Thesharpcurveismerelyoneexample;therearenumerous otherexampleslikesensorfailure,anobstacleontheroad,or

com-puterfailure,thatcanunexpectedlypushhapticsteeringguidance outside its operationalenvelope. Thephilosophy behindhaptic steeringguidanceistoincorporatethebestofboth—ahuman’s cre-ativesolutionscombinedwithamachine’saccurateandconsistent performance.However,ifdriversover-trustthemachineandadopt anexcessivespeedthecalibrationinthisteamperformanceisoff, whichmayinturnresultinalossofcontrol.

4.7. Self-reportedsatisfactionandusefulnessofthehaptic steeringguidance

Asupportsystemshouldbeperceivedusefulandsatisficingto beacceptedbydriversinacommercialvehicle.Theresultsofthe acceptancequestionnaireshowedthatallthreeguidance condi-tionswerewellliked,withaveragescoresabovezeroforboththe usefulnessandsatisfactiondimensions.TheBandsystemshowed slightlyandnon-significantlyloweracceptancethanContand Con-tRF;itmightbethatparticipantsexperiencedthesuddenincrease infeedbackforcewhencrossingalaneasannoying.Thisisin accor-dancewithresultsbyNavarroetal.(2010)andDeWinteretal. (2008),whofoundthatparticipantsgaverelativelylowratingsof acceptancetoadiscontinuoushapticinterventiononthesteering wheelorgaspedal, respectively.Discontinuoushapticfeedback maycauseunwantedreflexes/overshoots,excessivewearof hard-ware,ortimingproblemsassociatedwiththebalancebetweenfalse alarmsandmisseddetections(DeWinteretal.,2008;Navarroetal., 2010).ItisinterestingthattheContRFcondition,which didnot functionabove130km/h,didnotshowloweracceptancethanthe threeotherconditions.TherelativelyhighacceptanceforContRF mayhavebeencausedbythefactthatittooktheguidanceawayin agradualmanneryetclearlycommunicatedtheADASfunctionality andavailability.Alternatively,participantsmayhavethought Con-tRFwashelpfulforthereasonthatitpreventedthemfromdriving excessivelyfast.

4.8. Temporaleffectsofbehavioraladaptation

Duringthisstudy,participantswereexposedtoeachcondition forabout13min,henceonlymeasuringtheinitialandshort-term BAeffects.Previousresearchsuggeststhatthedegreeof experi-encewiththesystemisimportantinassessingBA(Martensand Jenssen,2012;Panouetal.,2007;seealsoMarsetal.,2014bwho foundthat drivingspeed increasedwiththeamountof experi-ence).Considering that trustin ADASand mental modelsgrow overperiodsofweeksormonths(Beggiatoetal.,2015),itis plau-siblethatthespeeddifferencebetweenContandManualmaybe evenlargerthan7km/hinthelongrun.Thepresentparticipants, manyofwhomwererecruitedfromthetechnicaluniversity com-munity,maybemorefamiliarwithintelligentvehicletechnology, andmorelikelytounderstandtheworkingmechanismsofsuch technology,thanthegeneralpublic.Thiswasexempliﬁedbythe factthat only3 of24 participantshadnot heardoftheGoogle DriverlessCarbefore,whichisconsiderablylowerthanKyriakidis etal. (2015)who reportedthat48% of4845respondents inan internationalcrowdsourcedsamplehadnotheardoftheGoogle Driverlesscar.Thus,itremainstobeinvestigatedhowourBA ﬁnd-ingsgeneralizetothegeneralpopulation,whomayneedalonger periodtogrowaccustomedtohapticguidancetechnology.The cor-relationsbetweenthedrivingexperiencevariablesandthemean speedwere0.25atmaximumand soexplainedupto6%ofthe variance,suggestingthatthedegreeofBAofadriverisnoteasily predictablefromaperson’slevelofdrivingexperience.Atpresent, therelationbetweenshort-andlong-termBAeffectsisunknown (DeWinterandDodou,2011),anditisrecommendedtoobtaina betterunderstandingofthistopicbymeansoflongitudinalstudies.

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Inourstudy,BAwasoperationalizedasincreaseddrivingspeed, anddrivingperformancewasquantiﬁedintermsoflane-keeping performance and safety margins, which are measures that are causallyrelatedtosafety.Wealsomeasuredworkload,andfound that Contyielded lower scoresonthe Mental Demand item of NASA-TLXthan ManualandBand.Thismaybebecausethe lat-tertwoconditionsrequiredthedrivertokeepvisuallyattentive, whereastheformerprovidedcontinuousassistanceonthe steer-ingwheel.Researchershavepointedoutthatreducedattentiveness itselfshouldalsoberegardedasamanifestationofBA(e.g.,Elvik, 2013).Indeed,itispossiblethatlowmentalworkloadassociates withlow attentiveness and complacency, poor performance in reclaimingmanualcontrol,andaninclinationtowards perform-ingnon-drivingtasksbehindthewheel(DeWinter andDodou, 2011;YoungandStanton,2002).Futureresearch,conductedacross multipledaysor months,shouldestablishtheoptimalrange of workload(seealsoDeWaard,1996).Thatis,ontheonehand,it canbearguedthatareductionofworkloadleavesmentalspare capacityforscanningobjectsintheenvironmentandforenhancing situationawareness(e.g.,McDowelletal.,2008),whereasonthe otherhandtheaforementionedmentalunderloadisariskfactor too(YoungandStanton,2002).

4.9. Drivingsimulatorsversuson-roaddriving

Thelane-keepingperformanceobtainedinthisstudyisslightly betterthanfoundin realcars,witha standarddeviationof lat-eralposition[SDLP]ofabout0.10m,whereasvaluesof0.15–0.20m aretypicallyobservedinon-roadexperiments(seeVeldstraetal., 2015;VersterandRoth,2011).Thisdifferencemaybecausedbythe factthatourstudyfeaturedanarrowroadandreal-timefeedback onperformance.

Participantsinourstudyadoptedhighmeanspeedsof110km/h despitethefactthattheroadwasnarrowandcontainedvarious curves.Therelativelyhighspeedin adrivingsimulator maybe explainedbythefacttherewerenoroaduserssharingtheroad withtheparticipant,aswellasbyincorrectspeedperceptionand lowperceivedriskwhendrivinginasimulator(DeWinteretal., 2012;Wallisetal.,2007).Driversinasimulatordonotexperience arealriskofcrashing,whichisadownsideofusingadriving sim-ulatorasopposedtoarealcar,especiallybecausesubjectiverisk isconsideredtobeanimportantdeterminantofBA(Näätänenand Summala,1974;Wilde,1998).

Nevertheless,simulatorsofferimportantadvantagescompared totestsinrealcars.Forexample,itwouldbetechnically,legally, andethicallychallengingtoexposeparticipantstoasharpcurve onarealroadinacontrolledmanner.Regardingethicalandlegal implications,itmaybedebatedwhethertheContRFsystem,which removeshapticguidancewhen drivingfaster than125km/h so thatdriversare‘ontheirown’,isanacceptabletypeofdriver sup-portin realtrafﬁc.Here, valuable lessons maybelearnedfrom existinglane-keepingassistancesystems,whichallhavevarious functionallimitations.Forexample,currentlane-keepingsystems donotfunctionabove200km/h,whenlanemarkersareabsent, insharpcurves,oronnarrowroads(e.g.Daimler,2013;VolvoCar Corporation,2015).

Although simulators have various limitations, their relative validity(i.e.,theeffectsizesbetweenthepairwisecomparisons) maystillbehigh,aswasillustratedrecentlybyKlüveretal.(2016). Theseauthorsfoundthatparticipantshadsubstantiallydifferent SDLPvaluesbetweenﬁxedbasesimulators,movingbase simula-tors,andarealcarbuttheeffectsizesasafunctionofsecondary taskconditionsweresimilarforthesethreehardwareconditions. Inourstudy,thelackofsubjectiveriskwastriedtobeaccountedfor byprescribingataskthatpenalizesriskybehavior(i.e.,‘minimize thenumberofconehits’).Nevertheless,thefactremainsthatthe environmentinthecurrentstudywasrelativelyuncomplicated, featuringasingle-laneroadandnootherroadusers,and there-forefurtherresearchshouldinvestigatetheexternalvalidityofthis simulator-basedresearch.

4.10. Forced-pacedversusself-pacedexperimentaldesigns

Finally, this research indicates that future ADAS developers shouldtakeintoaccounthumanadaptationswhenassessingand designingnewsystems.Thespeedadaptationfoundinthisstudy showedthatdrivingata fixedspeed, asisdoneinmuch ADAS research,maygiveadistortedviewofasystem’sbenefits.Although fixingthespeedisconvenientbecauseithomogenizesthe chrono-logicaltimingofeventsamongparticipants,italsorestrictsdrivers fromadaptingtoasysteminarealisticway.

4.11. Conclusionsandrecommendations

Inadrivingsimulatorexperiment,threedesignsofhaptic guid-ance were compared to unsupported driving, with the aim of quantifyingtheinﬂuence ofhapticsteering guidancedesign on speeding. Ashypothesized,continuoushapticsteering guidance sufferedfromBA,intermsofanincreasedspeedof7km/h com-pared to the Manual condition. We tested two fundamentally differentremedialtechnologies(Band&ContRF):Bandonly pro-videdfeedbackwhendrivingoutofbound,resultinginasystem thatwasidenticaltoManualfor84%ofthedrivingtime,whereas ContRFprovidedcontinuousfeedbackin95%oftime.Thesetwo differentapproachesbothsuccessfullypreventedBAwithsimilar lane-keepingperformanceandself-reportedacceptanceas contin-uousguidance.Participantsinourexperimentdrove13minineach ofthefourconditions;futureresearchshouldaddressreal-world andlong-termeffects,andestablishwhichcognitivemechanisms areatplayregardingthecausesandremediesofBA.

Acknowledgements

The authors would like to thank Sjors Oudshoorn, Dimitra Dodou,andBastiaanPetermeijerfortheirusefulsupportand well-foundedcomments.

AppendixA. –CorrelationMatrices

For eachcondition,theSpearmancorrelationwascalculated betweendependentmeasures(with anadditionalmeasure, the meanabsolutesteeringspeed[deg/s]).Thecorrelationmatricesare showninthetablesbelow.

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TableA1

Spearmanrank-ordercorrelationmatrixfortheManualcondition(N=24).

Mean speed Percentage time above 125 km/h Percentage time off-road Mean absolute lateral error Max absolute lateral error Mean lane return time Median TLC NASA-TLX Mean steering reversal rate Mean absolute driver torque Mean steering speed DBQ violations Mileage Meanspeed 1.00

Percentagetimeabove125km/h 0.68 1.00 Percentagetimeoff-road 0.33 0.29 1.00 Meanabsolutelateralerror 0.40 0.44 0.93 1.00

Maxabsolutelateralerror 0.55 0.29 0.66 0.72 1.00 Meanlanereturntime 0.21 0.13 0.67 0.64 0.42 1.00 MedianTLC −0.68 −0.68 −0.72 −0.77 −0.71 −0.47 1.00

NASA-TLX 0.03 0.00 0.23 0.37 0.37 0.27 −0.27 1.00

Meansteeringreversalrate 0.20 0.24 −0.16 −0.10 0.10 −0.21 −0.39 0.21 1.00 Meanabsolutedrivertorque 0.92 0.67 0.30 0.37 0.51 0.23 −0.75 0.10 0.45 1.00 Meanabsolutesteeringspeed 0.37 0.40 −0.04 0.05 0.23 −0.14 −0.52 0.20 0.93 0.62 1.00 DBQviolations 0.08 0.16 −0.07 −0.10 −0.02 −0.14 −0.03 0.09 0.06 0.19 0.12 1.00

Mileage 0.25 0.04 0.03 0.05 0.04 0.18 −0.11 0.35 0.01 0.23 0.08 0.13 1.00

Weeklydriving 0.20 −0.02 0.07 0.08 0.10 0.17 −0.11 0.26 −0.06 0.26 0.05 0.22 0.81 Note:p<0.05for||≥0.41,p<0.01for||≥0.52andp<0.001for||≥0.63.

TableA2

Spearmanrank-ordercorrelationmatrixfortheContRFcondition(N=24).

Mean speed Percentage time above 125 km/h Percentage time off-road Mean absolute lateral error Max absolute lateral error Mean lane return time Median TLC NASA-TLX Mean steering reversal rate Mean absolute feedback torque Mean absolute driver torque Mean steering speed Usefulness scale Satisfaction scale Meanspeed 1.00

Percentagetimeabove125km/h 0.57 1.00 Percentagetimeoff-road 0.19 0.20 1.00 Meanabsolutelateralerror 0.31 0.23 0.86 1.00 Maxabsolutelateralerror 0.00 0.13 0.83 0.59 1.00 Meanlanereturntime 0.26 0.16 0.66 0.44 0.50 1.00 MedianTLC −0.54 −0.53 −0.42 −0.46 −0.50 −0.28 1.00 NASA-TLX 0.11 0.21 0.33 0.40 0.15 0.22 −0.13 1.00 Meansteeringreversalrate 0.15 0.16 −0.07 −0.08 0.09 0.05 −0.66 −0.17 1.00 Meanabsolutefeedbacktorque 0.19 −0.13 0.73 0.76 0.59 0.33 −0.51 0.24 0.23 1.00 Meanabsolutedrivertorque 0.77 0.47 0.06 0.14 0.05 0.20 −0.57 0.28 0.31 0.10 1.00 Meanabsolutesteeringspeed 0.29 0.18 −0.01 0.06 0.06 0.09 −0.69 −0.14 0.96 0.34 0.37 1.00 Usefulnessscale −0.11 −0.19 −0.06 −0.20 0.15 −0.02 0.11 −0.24 −0.10 −0.03 0.13 −0.11 1.00 Satisfactionscale 0.19 0.19 0.13 0.08 0.38 0.05 −0.30 −0.25 0.05 0.05 0.11 0.06 0.54 1.00 DBQviolations 0.25 0.23 −0.22 −0.17 −0.05 −0.20 −0.30 −0.03 0.27 0.04 0.31 0.32 0.32 0.35 Mileage 0.01 0.25 −0.11 0.08 −0.10 −0.06 −0.03 0.39 −0.08 −0.28 0.05 −0.09 −0.32 0.04 Weeklydriving −0.04 0.07 −0.02 0.27 −0.05 −0.14 −0.08 0.30 −0.12 0.03 −0.06 −0.07 −0.37 −0.07 Note:p<0.05for||≥0.41,p<0.01for||≥0.52andp<0.001for||≥0.63.

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TableA3

Spearmanrank-ordercorrelationmatrixfortheBandcondition(N=24).

Percentagetimeabove125km/h 0.77 1.00 Percentagetimeoff-road 0.10 0.15 1.00 Meanabsolutelateralerror 0.14 0.09 0.87 1.00 Maxabsolutelateralerror 0.32 0.41 0.77 0.63 1.00 Meanlanereturntime 0.10 0.08 0.89 0.71 0.67 1.00 MedianTLC −0.65 −0.68 −0.55 −0.39 −0.73 −0.55 1.00 NASA-TLX 0.33 0.16 0.41 0.39 0.52 0.31 −0.37 1.00 Meansteeringreversalrate 0.27 0.32 −0.22 −0.44 0.13 −0.05 −0.44 0.04 1.00 Meanabsolutefeedbacktorque 0.36 0.35 0.89 0.81 0.73 0.83 −0.77 0.35 −0.04 1.00 Meanabsolutedrivertorque 0.83 0.58 −0.04 −0.09 0.16 0.03 −0.63 0.28 0.54 0.28 1.00 Meanabsolutesteeringspeed 0.35 0.43 −0.10 −0.30 0.25 0.05 −0.53 0.08 0.97 0.09 0.56 1.00 Usefulnessscale 0.04 0.16 −0.11 −0.09 −0.08 −0.16 −0.01 −0.32 −0.07 −0.07 −0.13 −0.04 1.00 Satisfactionscale −0.24 −0.07 −0.15 −0.07 −0.22 −0.25 0.31 −0.62 −0.28 −0.20 −0.43 −0.28 0.63 1.00 DBQviolations 0.07 −0.06 −0.03 −0.09 0.06 −0.03 −0.15 0.04 0.36 −0.07 0.10 0.37 −0.04 −0.04 Mileage 0.20 0.26 0.16 0.02 0.25 −0.05 −0.35 0.37 0.02 0.19 0.23 0.01 0.02 −0.25 Weeklydriving 0.20 0.12 0.17 0.04 0.11 0.07 −0.35 0.11 −0.03 0.21 0.26 −0.05 0.11 −0.13 Note:p<0.05for||≥0.41,p<0.01for||≥0.52andp<0.001for||≥0.63.

TableA4

Spearmanrank-ordercorrelationmatrixfortheContcondition(N=24).

Percentagetimeabove125km/h 0.80 1.00 Percentagetimeoff-road 0.22 0.38 1.00 Meanabsolutelateralerror 0.11 0.31 0.93 1.00 Maxabsolutelateralerror 0.41 0.36 0.79 0.67 1.00 Meanlanereturntime 0.16 0.17 0.73 0.65 0.70 1.00 MedianTLC −0.49 −0.57 −0.60 −0.53 −0.56 −0.51 1.00 NASA-TLX −0.08 −0.13 0.28 0.26 0.24 0.16 −0.02 1.00 Meansteeringreversalrate 0.03 0.26 0.16 0.18 0.04 0.29 −0.62 −0.15 1.00 Meanabsolutefeedbacktorque 0.45 0.60 0.84 0.79 0.66 0.60 −0.86 0.04 0.40 1.00 Meanabsolutedrivertorque 0.90 0.71 0.32 0.19 0.42 0.35 −0.64 −0.05 0.21 0.59 1.00 Meanabsolutesteeringspeed 0.33 0.49 0.30 0.27 0.22 0.36 −0.77 −0.21 0.92 0.60 0.51 1.00 Usefulnessscale 0.21 0.09 −0.44 −0.47 −0.31 −0.30 0.10 −0.50 −0.23 −0.20 0.22 −0.13 1.00 Satisfactionscale 0.29 0.20 −0.28 −0.28 −0.12 −0.28 −0.06 −0.49 −0.09 −0.07 0.18 −0.01 0.70 1.00 DBQ 0.11 0.09 −0.14 −0.15 −0.12 −0.19 −0.01 −0.19 0.00 −0.03 0.17 0.06 0.37 0.37 Mileage 0.12 0.00 0.21 0.28 0.19 0.10 −0.09 0.44 −0.23 0.18 0.18 −0.08 −0.20 −0.41 Weeklydriving −0.06 −0.13 0.27 0.35 0.15 0.20 −0.06 0.35 −0.15 0.18 0.06 −0.06 −0.24 −0.44 Note:p<0.05for||≥0.41,p<0.01for||≥0.52andp<0.001for||≥0.63.

References

Aarts,L.,VanSchagen,I.,2006.Drivingspeedandtheriskofroadcrashes:areview. Accid.Anal.Prev.38,215–224,http://dx.doi.org/10.1016/j.aap.2005.07.004. Abbink,D.A.,Mulder,M.,2009.Exploringthedimensionsofhapticfeedback

supportinmanualcontrol.J.Comput.Inf.Sci.Eng.9,011006,http://dx.doi.org/ 10.1115/1.3072902.

Abbink,D.A.,Mulder,M.,VanderHelm,F.C.T.,Mulder,M.,Boer,E.R.,2011. Measuringneuromuscularcontroldynamicsduringcarfollowingwith

continuoushapticfeedback.IEEETrans.Syst.ManCybern.PartB:Cybern.41, 1239–1249,http://dx.doi.org/10.1109/TSMCB.2011.2120606.

Abbink,D.A.,Mulder,M.,Boer,E.R.,2012.Hapticsharedcontrol:smoothlyshifting controlauthority?Cogn.Technol.Work14,19–28,http://dx.doi.org/10.1007/ s10111-011-0192-5.

Assum,T.,Bjørnskau,T.,Fosser,S.,Sagberg,F.,1999.Riskcompensation—thecase ofroadlighting.Accid.Anal.Prev.31,545–553,http://dx.doi.org/10.1016/ S0001-4575(99)00011-1.

Banks,V.A.,Stanton,N.A.,Harvey,C.,2014.Whatthedriversdoanddonottell you:usingverbalprotocolanalysistoinvestigatedriverbehaviourin