  Currently, human drivers outperform self-driving vehicles in many conditions
such as collision avoidance. Therefore, understanding human driver behaviour in
these conditions will provide insight for future autonomous vehicles. For
understanding driver behaviour, risk assessment is applied so far as one of the
approaches by using both subjective and objective measurement. Subjective
measurement methods such as questionnaires may provide insight into driver risk
assessment but there is often significant variability between
drivers.Physiological measurements such as heart rate (HR),
electroencephalogram (EEG), and electromyogram (EMG) provide more objective
measurements of driver risk assessment. HR is often used for measuring driver
risk assessment based on observed correlations between HR and risk perception.
Previous work has used HR to measure driver risk assessment in self-driving
systems, but pedestrian dynamics is not considered for the research. In this
study, we observed driver behaviour in certain scenarios which have pedestrian
on driving simulator. The scenarios have safe/unsafe situations (i.e.,
pedestrian crosses road and vehicle may hit pedestrian in one scenario), HR
analysis in time/frequency domain is processed for risk assessment. As a
result, HR analysis in frequency domain shows certain reasonability for driver
risk assessment when driver has pedestrian in its traffic.
