Use Case 4
AI based Traffic management
UC-4 AI based Traffic management
Objectives
Objectives
Define a benchmark/reference for desired/acceptable behaviour and/or minimal driving performance expectations.
Analyse the response of AI-models to traffic management data, at strategic, tactical, and operational levels.
Rationale
Rationale
Demonstrator
Demonstrator
AI Models and Traffic Management
Aim: the capabilities of the AI models will be tested and evaluated in use cases particularly relevant for traffic management and road authorities. The decisions of AI models in response to the data are of special interest. To assess this, the behaviour of the vehicle will be benchmarked against what is considered good behaviour as defined by the rules of the road.
Approach towards trustworthy AI:
- Prepare data sets with real traffic management data
- Real-world data will serve as a starting point, for example from deployed traffic systems, data from national access points, weather data and databases of road operators
- Define good behaviour patterns according to road rules
- Create causality, transparency and predictability indicators
Traffic
– AI based traffic management
AI models are analysed in macroscopic scenarios with interaction with other AI and non-AI systems. Trustworthiness is gained by benchmarking “good behaviour” of AI models in transport level contexts.