Objective
The number of road traffic accident fatalities world wide has recently reached 1.3 million each year, with between 20 and 50 million injuries being caused by road accidents. In theory, all accidents can be avoided. Studies showed that more than 90% road accidents are caused by or related to human error. Developing an efficient system that can detect hazardous situations robustly is the key to reduce road accidents.
This HAZCEPT consortium will focus on automatic hazard scene recognition for safe driving. The primary objective of this project is to build international capacity and cooperation in the fields of nature inspired visual computation, pattern recognition and human behaviour analysis, to explore effective methodologies for hazard perception.
Vision plays a critical role in hazard perception and escape behaviour for most animal species in a dynamic world. Many animal species, such as dung beetles and locusts, have also developed efficient night vision systems that work well in low light conditions. At a higher level, human vision combines cognitive cues such as road markings and signposts to judge hazard situations robustly. The naturally evolved biological vision systems provide ideal models to develop tireless artificial vision systems for hazard perception. On the other hand, a driver plays a key role in the safe driving loop, the status and behaviour of a driver should be constantly monitored and automatically analysed.
Taking the inspiration from biological vision systems, the consortium will bring together neurobiologists, neural system modellers, pattern recognition experts, an autonomous system integrator and a human/robot movement analyst to develop a hazard perception system, whilst also building strong connections between the European institutions and partner institutions in the East of Asia via staff secondments, and jointly organised seminars and workshops.
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.
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.
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.
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.
FP7-PEOPLE-2012-IRSES
See other projects for this call
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.
MC-IRSES - International research staff exchange scheme (IRSES)
Coordinator
LN6 7TS Lincoln
United Kingdom
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.