THE EFFECTIVENESS OF THE METHODOLOGY IN MONITORING DRIVER BEHAVIOUR K Muronga N Ruxwana 36 th Annual Southern African Transport Conference Traffic Management Safety and Security 11 July 2017 ID: 757863
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NATURALISTIC DRIVING STUDIES: THE EFFECTIVENESS OF THE METHODOLOGY IN MONITORING DRIVER BEHAVIOUR
K. Muronga, N Ruxwana* 36th Annual Southern African Transport ConferenceTraffic Management, Safety and Security
11 July 2017Slide2
Contents
BackgroundIntroductionPurpose Methodology
Research Findings
Recommendations
ConclusionFuture studies Key referencesSlide3
BackgroundPart of a bigger Masters level projectRoad traffic crashes unacceptably high (cost=143bil)The right to life and protection of life is a constitutional right in South Africa (13k died in 2015)RTMC invested about R800 mil in 2012/13 on road safety initiativesMove to make use of ICT’s to address road fatalitiesResearchers focusing on driver behaviour and computerised vehicles.Slide4
IntroductionNaturalistic driving studies:A novel approach to the way that road safety research can be conductedRefers to an unobtrusive approach to studying driver behaviour
Learn about driving task and road environmentInforms about driver actions and vehicle environment during crashes or near crashesSlide5
IntroductionData Acquisition System:Collects data from various sensors including camerasSlide6
PurposeTo address questions and concerns raised during the previous NDS discussionsTo inform on the effectiveness of the Methodology in monitoring driver behaviour.Slide7
Research MethodologyA mixture of qualitative and quantitative methodologiesQuestionnaires for quantitative data collectionContent analysis for qualitative data collectionConceptual Framework
The Theory of Planned Behaviour (TPB)TPB, a model to measure how human actions are guidedSlide8
The Theory of Planned Behaviour (TPB)Slide9
The Theory of Planned Behaviour (TPB)Behavioural beliefsAttitude toward the behaviourOutcome evaluationsNormative beliefsSubjective norms, estimate of social pressure to perform
Beliefs about how other people would want one to behaveControl BeliefsPerceived behavioural controlHow much control a person has over the behaviourHow confident a person feels about performing a behaviourSlide10
Data Collection and AnalysisCar carrier transportation organisationMember of RTMS programme137 vehicles/drivers participated82 Cross-border drivers55 Local distribution (Gauteng)
More than 3 000 behaviours analysedSlide11
Research FindingsDemographicsAges between 30 and 45Code EC driving licence or Foreign driving licence10 years of driving experience
Driving a minimum of 500km per week96% rating score for driving confidenceSlide12
Research FindingsManagement perceptions of NDS TechnologyAble to successfully identify risky driver behaviourReduces risk exposure to drivers (crime and accidents)Continuous improvement of driver’s driving ability (training)
Driver perceptions of NDS TechnologyConcerned with the fact that they are being monitoredA way for managers to fire themHappy to monitored for the benefits, e.g. hijack alert, driver training
83% agree that its for driver training programmes implementationSlide13
Research FindingsEffectiveness of NDS in improving driver behaviourTPB constructs from equation “constructs = (D-Ave + O-Ave)/2”66.7% chance of improving driver behaviourTrigger Attributes Considered
Driver DistractionsFundamentalsTraffic ViolationsSlide14
Attribute
Points
Description
Distractions:
Distractions are common while driving. A driver’s attention may be divided between driving, navigating, talking to passengers and other activities. Distractions that cause an event to be activated or lead to a risky situation are scored as distraction.
Cell phone
3
This is selected if the driver is using a handheld cell phone.
Food and Drink
3
This is selected if attention to food and drink put the driver in a risky situation.
Passenger (s)
3
This is selected if the driver dedicates too much attention to a passenger and it contributes to a risky driving situation.
Fundamentals:
These categories involve the fundamentals of safe driving and go to the very root of most crashes.
Failed to keep an Out
3
Space is the key to avoiding mistakes by other drivers. This behaviour is marked if a risky situation is clearly visible, yet the driver ignores it and positions the vehicle in a space that reduces outs available.
Too fast for Conditions
5
This will be triggered if the driver is driving at a speed that puts the vehicle in a tight spot or if the driver does not slow down for pedestrians looming around.
Unsafe lane change
5
This will be selected if the driver makes a lane change that leads to a risky situation.
Traffic Violations:
these refer to traffic violations regulated by the relevant traffic authority and the driver is aware of them.
Rolling stop
3
(Yielding at a stop sign) an instance when a vehicle driver slows down but does not stop at a stop sign.
Stop sign
5
Not stopping at a stop sign and/or not following stop sign rules.
Red light
5
Driving through a red light and/or flashing red light without following the rules.
Speeding
5
Not following set speed limit. Either roadway speed limit or type of vehicle set speed.
Designated roadway
3
Driving in a wrong lane, without any distractions on the correct lane.Slide15
ConclusionsTo address questions and concerns raised during the previous NDS discussionsFrom this study drivers are happy to be monitoredIt is important to inform the drivers of the reasons behind the monitoring
Driver training should be implemented instead of punishmentSignificant others should be involved in awareness programmes to reduce cabin distractionsSlide16
ConclusionsTo inform on the effectiveness of the Methodology in monitoring driver behaviour.The technology picked up more than 3000 behavioural attributesLocal drivers found to have a 12.6% rating of risky drivingCross-Border drivers had 9.24% rating
Local drivers violated more road rules and are more riskier66.7% chance of the Technology succeeding in improving driver behaviour.Slide17
ConclusionsThe results were in favour of the NDSConcerns are in communication between management and driversSlide18
RecommendationsMore logistics companies to participate in an NDS programmesA study to be conducted focusing on other road transport servicesLegislative discussions to be initiated to discuss the possibility of making some of the technology being made a legal requirement.Slide19
Future StudiesSecurity awareness during NDS (Information and Physical)NDS studies in public transportInstrumenting Taxis, Buses and TrainsSlide20
Key ReferencesMuronga, K. & Venter, K. 2014, "Naturalistic driving data : managing and working with large databases for road and traffic management research", 33rd Annual Southern African Transport conference, 8 July 2014.Venter, K. & Muronga, K. 2016, "Synthesizing naturalistic driving data: a further review", Southern African Transport Conference, .Peters, E.D. 2014, 3rd Africa Road Safety Seminar, http://www.transport.gov.za/Portals/0/Speeches/2014/SPEECH MINISTER 3 GRSP AFRICA SEMINAR.pdf edn.
Ajzen, I. 1991, "The theory of planned behaviour", Organizational behaviour and human decision processes, vol. 50, no. 2, pp. 179-211.Slide21
Thank you
Khangwelo
Muronga (kmuronga@gmail.com)