Use case 1 (UC1) focusses on integrated traffic management with intermodality. It explores CCAM solutions designed to offer recommendations for balancing demand and supply, optimising the overall performance of the transport network and supporting network recovery after accidents and planned or unplanned events. The envisioned solutions consider real-time and predicted traffic conditions to respond to specific traffic network scenarios and fit into the broader framework of CCAM applications in multimodal traffic management ecosystems and traffic orchestrators.


The Almelo use case focuses on improving traffic flow along an important logistics corridor and reducing the number of vehicles stopping at traffic lights.

This will bring significant benefits to the sector because every time a truck stops at a traffic light, it generates considerable costs, both financially and in terms of emissions. A total of 27 intelligent traffic control systems (iTLCs) will be implemented to communicate with vehicles and road users in an effective, safe and platform-independent manner. This will bring information from traffic controllers to road users and vice versa. A particular focus will be on freight traffic, where truck drivers will receive information to adjust their speed and form convoys to get the green light at signalised intersections.

Network-wide prioritisation of vehicles at signalised intersections will be introduced to ensure a seamless trip and support authorities in their transition to net-zero emissions in transport and improved public well-being.


The UC1 Athens solution optimises the synchronisation of buses and on-demand services with the metro and tram by adapting their schedules to reduce door-to-door travel times for passengers. The solutions offered by CONDUCTOR utilise 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, and rescheduling and rebalancing strategies.

These strategies take into account the needs and oblectives of different stakeholders and users in the CAM ecosystem and enable optimised mobility for people by redirecting/shifting to shared mobility fleets (including on-demand services), urban rail and the use of park and ride hubs, as well as promoting a shift to public transport.


The Madrid use case focuses on the management of events/incidents to restore the transport network operations, taking into account connected and autonomous vehicles (CAVs).

Planned events (e.g. road works) and unplanned events (e.g. accidents) are taken into account. The section of the M-30 ring road in Madrid was selected as the network for the use case. The vehicles in the simulated environment will be equipped with an on-board unit or a smart device that enables communication with the surroundings. Various scenarios will be tested, including routes/lanes for evacuation, prioritisation of emergency vehicles, control of access on the ring road, lane management and alternative routes to avoid certain road sections on the M-30. With the results obtained in the simulation environment, CONDUCTOR will boost the integration of CAVs into traffic management systems and take advantage of their benefits, such as direct communication between traffic managers and CAVs, customised routing (e.g. instruction of alternative routes depending on the type and location of the incident), cooperative cruise control and much more.