Project description
New 5G design for driverless cars
Connected and autonomous vehicles (CAVs) represent a promising path towards road safety and efficiency. However, some barriers prevent the deployment of their entire potentiality, such as enhanced vehicle-to-vehicle (eV2V) services with millimetre wave (mmWave) communications and reliable cooperative perception with autonomous vehicles’ (AVs) sensors. The directional connectivity of mmWave shows new challenges for the whole protocol stack of V2V networks, and reliable cooperative perception requires a new design of deep learning models for object detection and fusion of sensor data from neighbour AVs. The EU-funded VESAFE project proposes an innovative cross-layer design to research the 5G eV2V schemes with mmWave and reliable cooperative perception for state-of-the-art CAV safety applications.
Fields of science
- engineering and technologymechanical engineeringvehicle engineeringautomotive engineeringautonomous vehicles
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationstelecommunications networksmobile network5G
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
Programme(s)
Funding Scheme
MSCA-IF-EF-ST - Standard EF
Coordinator
CO4 3SQ Colchester
United Kingdom
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