As Europe prepares for large-scale deployment of Connected, Cooperative and Automated Mobility (CCAM) services, understanding how automated vehicles will interact with human road users in real traffic environments become increasingly important for both technology development and certification processes.

However, automated driving systems still struggle to represent the diversity, uncertainty and complexity of human behaviour. Drivers continuously adapt their actions according to traffic conditions, perceived risks, personal preferences, cultural influences and interactions with other road users. Capturing these behavioural aspects is important for the development, testing and validation of trustworthy automated mobility solutions.

To address this challenge, the Horizon Europe CCAM project BERTHA has developed new Driver Behavioural Models representing realistically the diversity of human driving behaviour. Accessible to researchers, developers and industry stakeholders through a centralised open source repository, these can be incorporated into testing activities, virtual validation processes and automated driving development workflows.

Beyond technical validation, behavioural modelling also plays a role in addressing public acceptance challenges associated with automated mobility. Indeed, systems that fail to interpret human behaviour or react unexpectedly may undermine confidence in automation, regardless of their technical performance. As automated mobility moves closer to large-scale deployment, these solutions become as important as advances in sensing, connectivity and artificial intelligence to support safe interactions between automated vehicles, conventional vehicles and vulnerable road users in real-world operations.

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Source: The original article was published here.