1. NATURALISTIC DRIVING STUDIES: THE EFFECTIVENESS OF THE METHODOLOGY IN MONITORING DRIVER BEHAVIOUR
K. Muronga, N Ruxwana*
36th Annual Southern African Transport Conference
Traffic Management, Safety and Security
11 July 2017

2. Contents Background Introduction Purpose Methodology Research Findings
Recommendations
Conclusion
Future studies
Key references

3. Background Part of a bigger Masters level project
Road 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 initiatives
Move to make use of ICT’s to address road fatalities
Researchers focusing on driver behaviour and computerised vehicles.

4. Introduction Naturalistic driving studies:
A novel approach to the way that road safety research can be conducted
Refers to an unobtrusive approach to studying driver behaviour
Learn about driving task and road environment
Informs about driver actions and vehicle environment during crashes or near crashes

5. Introduction Data Acquisition System:
Collects data from various sensors including cameras

6. Purpose
To address questions and concerns raised during the previous NDS discussions
To inform on the effectiveness of the Methodology in monitoring driver behaviour.

7. Research Methodology
A mixture of qualitative and quantitative methodologies
Questionnaires for quantitative data collection
Content analysis for qualitative data collection
Conceptual Framework
The Theory of Planned Behaviour (TPB)
TPB, a model to measure how human actions are guided

8. The Theory of Planned Behaviour (TPB)

9. The Theory of Planned Behaviour (TPB)
Behavioural beliefs
Attitude toward the behaviour
Outcome evaluations
Normative beliefs
Subjective norms, estimate of social pressure to perform
Beliefs about how other people would want one to behave
Control Beliefs
Perceived behavioural control
How much control a person has over the behaviour
How confident a person feels about performing a behaviour

10. Data Collection and Analysis
Car carrier transportation organisation
Member of RTMS programme
137 vehicles/drivers participated
82 Cross-border drivers
55 Local distribution (Gauteng)
More than behaviours analysed

11. Research Findings Demographics Ages between 30 and 45
Code EC driving licence or Foreign driving licence
10 years of driving experience
Driving a minimum of 500km per week
96% rating score for driving confidence

12. Research Findings Management perceptions of NDS Technology
Able to successfully identify risky driver behaviour
Reduces risk exposure to drivers (crime and accidents)
Continuous improvement of driver’s driving ability (training)
Driver perceptions of NDS Technology
Concerned with the fact that they are being monitored
A way for managers to fire them
Happy to monitored for the benefits, e.g. hijack alert, driver training
83% agree that its for driver training programmes implementation

13. Research Findings Effectiveness of NDS in improving driver behaviour
TPB constructs from equation “constructs = (D-Ave + O-Ave)/2”
66.7% chance of improving driver behaviour
Trigger Attributes Considered
Driver Distractions
Fundamentals
Traffic Violations

14. 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
This is selected if attention to food and drink put the driver in a risky situation.
Passenger (s)
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
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
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
(Yielding at a stop sign) an instance when a vehicle driver slows down but does not stop at a stop sign.
Stop sign
Not stopping at a stop sign and/or not following stop sign rules.
Red light
Driving through a red light and/or flashing red light without following the rules.
Speeding
Not following set speed limit. Either roadway speed limit or type of vehicle set speed.
Designated roadway
Driving in a wrong lane, without any distractions on the correct lane.

15. Conclusions
To address questions and concerns raised during the previous NDS discussions
From this study drivers are happy to be monitored
It is important to inform the drivers of the reasons behind the monitoring
Driver training should be implemented instead of punishment
Significant others should be involved in awareness programmes to reduce cabin distractions

16. Conclusions
To inform on the effectiveness of the Methodology in monitoring driver behaviour.
The technology picked up more than 3000 behavioural attributes
Local drivers found to have a 12.6% rating of risky driving
Cross-Border drivers had 9.24% rating
Local drivers violated more road rules and are more riskier
66.7% chance of the Technology succeeding in improving driver behaviour.

17. Conclusions The results were in favour of the NDS
Concerns are in communication between management and drivers

18. Recommendations
More logistics companies to participate in an NDS programmes
A study to be conducted focusing on other road transport services
Legislative discussions to be initiated to discuss the possibility of making some of the technology being made a legal requirement.

19. Future Studies
Security awareness during NDS (Information and Physical)
NDS studies in public transport
Instrumenting Taxis, Buses and Trains

20. Key References
Muronga, 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 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, 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

21. Khangwelo Muronga (kmuronga@gmail.com)
Thank you
Khangwelo Muronga