In the recent times, traffic congestion and motor accidents have been a major problem for transportation in major cities. Intelligent Transportation Systems has the potential to be an effective solution in order to tackle this issue. Connected Autonomous Vehicles can cooperate at intersections, ramp merging, lane change and other conflicting scenarios in order to resolve the conflicts and avoid collisions with other vehicles. A lot of works has been proposed for specific scenarios such as intersections, ramp merging or lane change which partially solve the conflict resolution problem. Also, one of the major issues in autonomous decision making - deadlocks have not been considered in some of the works. The existing works either do not consider deadlocks or lack a safety proof. This thesis proposes a cooperative driving solution that provides a complete navigation, conflict resolution and deadlock resolution for connected autonomous vehicles. A graph-based model is used to resolve the deadlocks between vehicles and the responsibility sensitive safety (RSS) rules have been used in order to ensure safety of the autonomous vehicles during conflict detection and resolution. This algorithm provides a complete navigation solution for an autonomous vehicle from its source to destination. The algorithm ensures that accidents do not occur even in the worst-case scenario and the decision making is deadlock free.