The advent of autonomous vehicle is a breakthrough innovation in the field of transportation and the car manufactures aim at continuously developing and improving the complicated systems such vehicles require for increasing driver and user safety. Enabling driver to takeover vehicle control safely due to system malfunctions or failures, emergency (incident occurrence, stop vehicle, etc) or lack of autonomous environment is of vital importance. This PhD aims at investigating the control takeover from the vehicle to its driver and therefore the transition from autonomous to manual driving (transition of control). Through high resolution data from unmanned aerial vehicles (drones), the driver behavior under manual driving will be extensively and deeply analyzed and explored focusing mainly on harsh events and reaction in emergency and adverse conditions (lane changing, overtaking, spatial and temporal headways, etc.).
The results of the data analysis will be used as input for the traffic model which will be developed in a traffic simulation software, where mixed traffic consisted of autonomous and conventional vehicles will be simulated and scenarios where transition of control is required will be developed. Vehicle and driver behavior, reaction times and types and driver performance until he fully gains the control of the vehicle will be investigated. Finally, the impacts of this transition on the overall traffic, the prevailing traffic conditions and road safety will be analyzed.