Advanced Driver Assistance Systems (ADAS) are primarily radar and camera-based technologies that capture the vehicle’s surrounding environment and assist the driver by keeping him informed about current vehicle state, and if necessary intervene to prevent an impending danger, while the driver is in control of the vehicle at all times. These technologies pose two types of requirements, one on the Human-Machine interface which consists of graphics-based platform or interaction devices like knobs, handles and acoustics etc. for interaction between electromechanical system and the end user, and other, on the Transition of control from manual to automated driving and vice-versa. Whilst the former is a topic of ongoing research in the industry, the latter clearly demands more attention (from a control engineering perspective) than it already receives. The motivation behind this thesis lies in the unavailability of a rigorous mathematical framework, to design and assess the rich dynamic phenomena underlying the steering interactions that take place during a transfer of control authority between human driver and automated vehicle. The current approaches in the academia are based on a monocausal treatment (either from the purview of human factors or from systems engineering) and hence, are too conservative for a sound analysis of combined human-automation interaction. The approach outlined in this thesis addresses these challenges by using a switched system framework to solve the problem of ''effecting a smooth switching of control authority between human driver and automated vehicle, and investigating the underlying parameters to address the issues of driver comfort and safety''. The Human driver has been modeled as preview controller with a neuromuscular dynamics component, whereas the automated vehicle has been developed using PID control strategy for speed control and PD control strategy for steering control. This research uses a 4DOF(degree-of-freedom) ‘two track’ vehicle model for control design and after subsequent linearization, the 2DOF vehicle model for formal verification. Using the concepts of hybrid automata, both the systems were modeled to obtain a two-mode switching automaton. A scheme was then setup using the concept of average dwell time to evaluate stability and temporal logic to incorporate verification of different parameters that affect the switching. Furthermore, the Breach Matlab toolbox was used to perform the parametric verification of the three parameters under investigation, namely, human preview distance, automation preview distance, and driver gain, which were varied for different longitudinal velocities, maximum allowed lateral deviation and time of switching (or the time during the lane change when the switch takes place). In conclusion, the experimental results obtained, validate the correctness and usability of the framework for future developments.