(195)
Road traffic should be understood as surface roads41 excluding water ways. According to the approach presented in Section 3.2.1.ii above, ‘an AI system intended to be used in the management and operation of road traffic ’ refers to an AI system intended to be used in an asset, a facility, equipment, a network, or a system or a part of an asset, a facility, equipment, a network or a system which is necessary for the provision of the essential services established in Article 2(2) point (d) of the CER Delegated Regulation. This includes:
- Traffic management control, including aspects related to road network planning, control and management services, excluding traffic management or the operation of intelligent transport systems where they are not an essential part of the general activity of p ublic entities (road authorities);
- Intelligent Transport Systems services (operators of Intelligent Transport Systems);
(196)
An AI system intended to be used in the management and operation of road traffic shouldtherefore be considered high-risk only if it is intended to be used by a road traffic entity (i.e. a road authority or an operator of Intelligent Transport Systems) that has been identified as a critical entity by a Member State under the CER Directive.
a) Practical examples of AI systems falling within the high-risk use case of road traffic
- An AI system intended to be used as a real-time translation tool. Such a system is necessary for transport service employees to overcome language barriers between the control centre and drivers or between passengers and drivers , which ensures linguistic communication and contributes to the safety of public transport operations.
- An AI system intended to be used to monitor road traffic and to adjust traffic lights accordingly. Such a system controls or limits possible physical harm to people or physical damage to vehicles, road users and surroundings by directly protecting the physical integrity of road traffic management system. It should therefore be considered to have a direct impact on road traffic safety.
- An AI system intended to be used in the recognition of heavy objects on vulnerable bridges and quaysides. Such a system helps prevent the collapse of bridges and quay walls. It prevents physical harm to natural persons and physical damage to objects under a bridge or a quaysideby directly protecting the physical integrity of road infrastructure dependent on the road traffic management system. The failure of the AI system could result in potential collapse not being detected on time and natural persons on the bridges and quay walls being at risk when they collapse. The AI system is not needed for managing bridges and quays and is an additional safety component, comparable to an emergency button.
- An AI system intended to be used to link real-time water level data to lock management for road traffic (e.g. in flood-risk scenarios). Sucha system monitors and detects situations thatmay directly lead to physical harm to natural persons or physical damage to property by directly protecting the physical integrity of the road infrastructure dependent on the road traffic management system.
- An AI system intended to be used as a control system capable of communicating with road users via telecommunication networks (Intelligent Traffic Control System-iTCS). Such a system can recognize traffic, perform analyses on received data, and make decisions based on these analyses. This enables the prioritisation of certain road users over others; a key advantage being improved traffic flow on busy roads. Through data exchange with iTCS , road users can also be informed about how long a traffic light will remain red or green. Such an AI system prevents accidents (e.g., head-on collisions if two traffic flows cross paths, chain-reaction accidents in congestion ), i ts malfunction c ould cause gridlock, the obstruction of emergency services, (e.g., ambulances) or an increased likelihood of accidents at busy junctions , and such failures create direct and immediate risks to both infrastructure integrity (damage to signals, road surfaces, vehicles, etc.) and health and safety of natural persons (fatalities and injuries).
b) Practical examples of AI systems falling outside the high-risk use case of the road traffic
- An AI-enabled traffic flow optimisation system based on real-time data collection. Such a system is a traffic data analytics platform enabling intelligent analysis for flow optimisation functions, but does not directly trigger changes in the traffic management that may impact the safety; it does not directly protect safetyor physical integrity. These systems provide insights but do not directly protect physical integrity. Traffic systems can function without it.
- An AI system used for predictive maintenance which allows for more accurate predictions regarding infrastructure maintenanceas part of a range of safety measures. Such an AI system merely helps prevent failures; it is not a safety component and malfunctioning of the system would not endanger the safety as the system can function without it as it is only one measure that is precautionary in nature among other safety safeguards and not essential for the safe operation of the system.
- With regards to emotion recognition AI systems that do not fall under the scope of the prohibition under Article 5(1)(f), please see the analysis of Annex III(1)(c) within these Guidelines.