Cities are testing driverless trains thanks to two key technologies: Remote Train Control (RTC) and Automatic Train Operation (ATO). In a recent study of a European tram network, researchers interviewed 44 experts β operators, suppliers and safety managers β to see what really changes. The findings highlight three major benefits: first, productivity rises because trams can run closer together safely. Second, safety improves as systems constantly monitor speed, brakes and signals, cutting human errors. Finally, the environmental impact drops as energy is used more efficiently. But itβs not all smooth sailing. Challenges are equally strong: current regulations often donβt cover driverless trains, so new laws are needed. Technically, a stable data connection and protection against cyberβattacks are essential. Moreover, staff must acquire new skills or shift roles, which can cause tension. The authors recommend a stepβbyβstep approach, testing solutions in controlled settings and involving all stakeholders from the start. Only then can cities fully harness automation, making transport faster, safer and greener.
Automatic Train Operation (ATO) relies on predictive control algorithms that compute the optimal vehicle trajectory in real time, considering variables such as gradient, load weight and weather conditions. The system uses positioning sensors (GNSS), magnetic balises and V2I (VehicleβtoβInfrastructure) communications to constantly update the digital map of the route. Remote Train Control (RTC), on the other hand, requires a lowβlatency communication network (typically 5G or LTEβAdvanced) linking the vehicle to an operations centre. This architecture enables emergency command transmission, driving parameter updates, and realβtime diagnostic data collection. Cybersecurity is a critical aspect: communications must be encrypted with TLS 1.3 protocols and include publicβkey authentication mechanisms to prevent intrusions. From a regulatory standpoint, EU Directive 2016/797 mandates functional safety certification at SIL 4 level for railway control systems, implying faultβtolerance testing and hardware redundancy. Moreover, organizational transition demands upβskilling programs for operators, with certified courses on ATO/RTC management and faultβscenario simulations. A gradual rollout, starting with lowβtraffic lines, allows the collection of operational data, refinement of AI algorithms, and demonstration of regulatory compliance while reducing implementation costs.
