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BEhavioural ReplicaTion of Human drivers for CCAM

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 (EuroSciVoc)

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-RIA - HORIZON Research and Innovation Actions

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Call for proposal

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(opens in new window) HORIZON-CL5-2022-D6-01

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Coordinator

INSTITUTO DE BIOMECANICA DE VALENCIA
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 778 437,50
Address
CAMINO DE VERA EDIFICIO 9C UNIVERSIDAD POLITECNICA DE VALENCIA
46022 Valencia
Spain

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SME

The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Yes
Region
Este Comunitat Valenciana Valencia/València
Activity type
Research Organisations
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 778 437,50

Participants (15)

Partners (1)

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