Project description
Intelligent vehicles
Intelligent transportation systems (ITS) have the potential to transform road transportation and personal mobility. Advances in information and communication technologies are leading to the emergence of intelligent vehicles (IVs), which are typically equipped with GPS and advanced driver assistance systems (ADAS). IVs also feature various autonomous functions such as the sensing of vehicles, the environment and driver state. Using a combination of engineering and statistics, scientists of the EU-funded BITS project will work on a novel methodology for uncertainty identification and efficient estimation of various unknown parameters of ITS. They will conduct physical tests to validate the proposed methodologies and, using computer science tools, they will evaluate and minimise risks in the dynamic environment of IVs. This work will provide an accurate representation of a network of IVs and will contribute towards the deployment of IVs in real traffic networks.
Objective
The study of intelligent vehicles (IVs) is an area developing very fast and has the potential to transform road transportation and personal mobility in the years to come. In order to evaluate and minimize risks in the dynamic environment of IVs, it is necessary to have an accurate representation of the system and the uncertainty; the system describing IVs will never be a perfect representation of the true physical process and relying on its accuracy may lead to unreliable estimations and predictions and hence lead to wrong decisions. We will take into account this discrepancy of the mathematical representation and the physical system and utilize a fully Bayesian approach to develop a novel Bayesian learning methodology enabling efficient decision-making such avoiding collisions, as well as robust fault diagnosis. By first analyzing and understanding the uncertainty of an individual IV, the aim is to move to the collective behavior of IVs. This methodology will be validated on a physical test-bed at the University of Cyprus. The proposed project is highly interdisciplinary and combines methods from Engineering (expertise of the supervisor) and Statistics (extensive experience of the ER whose research background blends with parallel developments in Computer Science such as Machine Learning). This fellowship will contribute to the boost and advancement of the ER's career and ensure a two-way transfer of knowledge by (1) enriching the ER’s research skills through a career development plan and (2) the ER will transfer to the host her expertise. The potential impact of the proposed Bayesian uncertainty quantification of IVs can be high and important for the society as a whole, as we are making a step to the right direction to make IVs part of our everyday lives. The project has been designed around a coherent plan with experiments that will examine specific research directions but will also provide valuable insights and draw conclusions on Bayesian learning for IVs.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.4. - SPREADING EXCELLENCE AND WIDENING PARTICIPATION
MAIN PROGRAMME
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Topic(s)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-WF-2018-2020
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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.
1678 Nicosia
Cyprus
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.