Project description
Filling the gap in driver behaviour understanding
In the rapidly advancing landscape of connected, cooperative and automated mobility, Europe faces a pressing challenge. The absence of a scientifically validated driver behavioural model (DBM) leaves a significant void in understanding human driving performance, a crucial aspect for safe and efficient development. This gap hampers the creation of connected systems that can interact predictably with a human perspective. The EU-funded BERTHA project will address this issue by developing a scalable and probabilistic DBM. This project seeks to bridge the gap, ensuring a harmonious integration of automated driving functions into mixed traffic scenarios. By bringing together 14 entities across six countries, BERTHA paves the way for more human-like connected autonomous vehicles and societal acceptance.
Objective
Europe must seize the opportunities presented by connected, cooperative, and automated mobility (CCAM). For its deployment, powerful tools enabling the design and analysis of CCAM components, digitally and with a common language between TIERs an OEMs are needed.
The lack of a validated - and scientifically based - Driver Behavioural Model (DBM) to cover the aspects of human driving performance is one of the main shortcomings of CCAM development. It allows to understand and test the interaction of CCAM with other cars in a safer and predictable way from a human perspective. DBM is the cornerstone for the development of CCAM components. It will guarantee its digital validation and, if incorporated in the ECUs software, will generate a more human-like response of autonomous vehicles (at any level) and increase its acceptance.
The main objective of BERTHA is to develop a scalable and probabilistic DBM based mostly on Bayesian Belief Network (BBN). The DBM will be implemented on an open-source, HUB (repository) to validate technological and practical feasibility of the solution with industry and become a unique approach for the model worldwide scalability. The resulting DBM will be translated into a simulating platform, CARLA, using diverse demos which allows building new driving models in the platform.
BERTHA will also include a methodology which, due to the HUB, will share the model to the scientific community to ease its growth.
The project includes a set of interrelated demonstrators to show this DBM approach as a reference to design human-like, easily predictable and acceptable behaviour of automated driving functions in mixed traffic scenarios.
BERTHA is expected to go from a TRL 2 a TRL 4. The requested EU contribution is €7,981,801. The consortium, 14 entities from 6 countries, including South Korea, deem this Project as vitally relevant to the CCAM industry due to its impact for safer and more human-like CAVs and its market and societal adoption.
Fields of science
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Programme(s)
Funding Scheme
HORIZON-RIA - HORIZON Research and Innovation ActionsCoordinator
46022 Valencia
Spain
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.