Use case 1 (UC1) refers to integrated traffic management with intermodality. It takes into consideration CCAM solutions intended to provide recommendations to balance demand and supply, optimize performance of the overall transport network, and support transport network recovery from accidents and planned and unplanned events. The solutions envisaged in this area of application ​take into account the traffic conditions (both real-time and predicted) to respond to a specific transport network scenario. In this light the concept addressed can be ascribed in the overall framework of those CCAM applications related to multimodal traffic management ecosystems and traffic orchestrators.


The focus of the Almelo use case is on improving traffic flow along a major logistics corridor and reduce the number of vehicles stops at traffic signals.

It will bring considerable benefits to the sector because every time a truck stops at a traffic light it results in major costs, both monetarily and in terms of emissions. A total amount of 27 intelligent traffic control systems (iTLCs) will be implemented to communicate with vehicles and road users in an effective, safe and platform-independent way. This will bring information from the traffic controllers to the road users and vice versa. Specific emphasis will be placed on freight traffic, where truck drivers will receive information to adjust their speeds and form platoons in order to receive green lights at signalized intersections.

A network-wide prioritisation of vehicles at signalised intersections will be introduced in order to guarantee a seamless trip and help governmental bodies in their transition towards net-zero emissions in transport and improved community wellbeing.


The UC1 Athens solution will optimize the synchronization of buses and on-demand services with metro and tram by means of adjusting their schedules to reduce the door-to-door travel times of passengers, while using traffic management centres (Attica TMC Attica Tollway MC), and Maas platforms. The solutions to be offered by CONDUCTOR will make use of novel traffic management strategies for CAM including Al assisted traffic signal control for multimodal traffic; road space allocation strategies; transit fleet integration to traffic management; rescheduling and rebalancing strategies.

These strategies will consider the needs and oblectives of ditterent stakeholders and users in the CAM eco-system and enable optimized mobility of people through diversion/transfers to shared mobility fleets (including on-demand services), urban rail and use of Park&Ride Hubs as well as encouraging modal shifts towards public transport.


The Madrid use case will be focussed on the management of events/incidents for recovering the transport network operations, considering connected and autonomous vehicles (CAVs).

Planned events (e.g., roadworks) and unplanned events (e.g., accidents) will be considered. The M-30 ring road section of Madrid has been selected as the network for the use case. The vehicles in the simulated environment will have an on-board unit or smart device that will enable communication with the surroundings. Different scenarios will be tested including routes/lanes for evacuation, prioritization of emergency vehicles, control of access on the ring highway, lane management, alternative routes for avoiding specific road stretches in the M-30. With the results obtained in the simulation environment, CONDUCTOR will boost the integration of CAVs in traffic management systems, leveraging its benefits, such as the direct communication between traffic managers and CAVs, individual route guidance (e.g., instructions of alternative routes depending on the type of event considered and its location), cooperative cruise control, among others.