| dc.description.abstract | Driver distraction, defined as the scattering of attention from critical activities for safe driving,
is among the key globally recognized contributing factors to road crashes. The trend keeps
increasing with in-vehicle information systems and hand-held devices, leading to inattention.
Of people in all age groups, young novice teenagers are prone to the risk of road crashes and
are also more likely to exhibit risky and unsafe driving behavior. Data shows that the
involvement of distracted drivers in fatal & injury collisions is higher for people aged between
16 -34, which is about 55%. Therefore, young drivers are of great concern for the research
about driving and evaluation of safe driving conditions, which is vital in upcoming
advancements in autonomous vehicles.
Several research studies have explored the effects of distracted driving using face tracking and
eye glance monitoring. Previous research [50] did not consider much about the effect of
distraction on physiological factors and their impact during driving. The current study used
data collected from a previous thesis work titled “Detection of Driver Cognitive Distraction
Using Machine Learning Methods” by Apurva Misra and conducted new data analysis
focusing on new research questions. The main objective of this thesis is to study, identify and
discuss the effects on physiological factors like heart rate (HR), electrodermal activity (EDA),
body temperature, and motion sickness during distracted driving among young drivers.
The data was collected from a driving simulator study comprising 42 participants aged
16 – 23 under normal and distracted driving conditions. Their driving experience ranges from
0 to a maximum of 5 years. Each participant navigated six scenarios, three with distraction and the rest without distraction. Each scenario has a hidden, latent hazard depending on the
surrounding; for example, in the work zone scenario, a worker is hidden behind the bulldozer
in the work zone. The distraction task is a spoken task for which the driver has to respond
verbally, which exerts a workload similar to that observed in conversations using a hands-free
mobile phone. The physiological data collected through the Empatica4 wristband was analyzed
and compared against age, gender, driver experience, and another parameter like motion
sickness score (MSS) obtained from a questionnaire the participants completed after the
experiment. Of the physiological factors stated above, it was found that HR and EDA play a
significant role while studying distraction. Data analysis showed that HR and EDA increase
more during distraction than baseline events. Nearly 80% of drivers with 0 or 1 year of
experience tend to have a higher range of HR and EDA, which reveals that they are more
distracted than their peers with more experience. From the results of the Load index
questionnaire and Motion Sickness susceptibility questionnaire, it is inferred that when MSS
increases, there is an increase in HR and EDA. These findings will provide insights into
physiological factors for developing distraction mitigation systems or in-vehicle warning
systems for distracted drivers. | en |
