The paper aims to develop an integrated modelling framework for urban network traffic control in the presence of connected and autonomous vehicles (CAVs). The framework is further composed of two sub models: the first of which focuses on the traffic control problem in the case of hybrid flow conditions (unequipped vehicles and connected vehicles) and the second aims to control the automated vehicles in terms of speed optimisation. The traffic control strategy drew on the hybrid combination between the centralised approach based on a multi-objective optimisation and a link metering based on a single control function; whilst with reference to the speed guidance, the GLOSA (Green Light Optimal Speed Advisory) procedure was considered. Furthermore, the presence of connected vehicles has also been considered to support the estimation procedure of location and speed of unequipped vehicles. In terms of traffic flow modelling the microscopic approach has been applied. The proposed framework was applied by considering a simple real network (in the city centre of Naples, in the Southern of Italy) that was composed by one origin–destination pair and two alternative paths. The network layout is characterised by one diversion node and two alternative paths connecting the same origin - destination pair; three scenarios were tested: the first was only based on a centralised traffic control procedure, the second on speed guidance optimisation and the third was based on the combination of both sub-models. Finally, the framework effectiveness was analised in terms of within-day dynamics with respect to the travel times and queue length performance indices.