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Ultra-layered perception with brain-inspired information processing for vehicle collision avoidance

Objective

Autonomous vehicles, although in its early stage, have demonstrated huge potential in shaping future life styles to many of us. However, to be accepted by ordinary users, autonomous vehicles have a critical issue to solve – this is trustworthy collision detection. No one likes an autonomous car that is doomed to a collision accident once every few years or months. In the real world, collision does happen at every second - more than 1.3 million people are killed by road accidents every single year. The current approaches for vehicle collision detection such as vehicle to vehicle communication, radar, laser based Lidar and GPS are far from acceptable in terms of reliability, cost, energy consumption and size. For example, radar is too sensitive to metallic material, Lidar is too expensive and it does not work well on absorbing/reflective surfaces, GPS based methods are difficult in cities with high buildings, vehicle to vehicle communication cannot detect pedestrians or any objects unconnected, segmentation based vision methods are too computing power thirsty to be miniaturized, and normal vision sensors cannot cope with fog, rain and dim environment at night. To save people’s lives and to make autonomous vehicles safer to serve human society, a new type of trustworthy, robust, low cost, and low energy consumption vehicle collision detection and avoidance systems are badly needed.

This consortium proposes an innovative solution with brain-inspired multiple layered and multiple modalities information processing for trustworthy vehicle collision detection. It takes the advantages of low cost spatial-temporal and parallel computing capacity of bio-inspired visual neural systems and multiple modalities data inputs in extracting potential collision cues at complex weather and lighting conditions.

Fields of science (EuroSciVoc)

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

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Topic(s)

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.

MSCA-RISE - Marie Skłodowska-Curie Research and Innovation Staff Exchange (RISE)

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-RISE-2017

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Coordinator

UNIVERSITY OF LEICESTER
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.

€ 148 500,00
Address
UNIVERSITY ROAD
LE1 7RH Leicester
United Kingdom

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Region
East Midlands (England) Leicestershire, Rutland and Northamptonshire Leicester
Activity type
Higher or Secondary Education Establishments
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.

€ 148 500,00

Participants (7)

Partners (11)

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