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CORDIS

Autonomous Vehicular Edge Computing and Networking for Intelligent Transportation

Project description

AI-empowered autonomous vehicular system for smart transportation

Intelligent Transportation Systems (ITS) are essential in transport systems. However, ITS cannot meet emerging mission-critical applications concerning ultra-high reliability and low latency due to their complex and dynamic operating environments. The EU-funded ASCENT project will create a novel AI-powered Autonomous Vehicular Edge Computing and Networking system for reliable and efficient ITS. The project will conduct pioneering research and innovations (R&I) on a novel and scalable system architecture. This will allow agile and reliable ITS service provisioning and an original distributed AI framework fuelled by deep learning methods. ASCENT will develop innovative analytics tools to accurately predict dynamic network status and autonomous and smart resource management schemes to support mission-critical services.

Objective

Intelligent Transportation Systems (ITS) are vital for enhancing road safety, alleviating traffic congestion, and saving energy in transport. However, due to the complex and dynamic operating environments of ITS including fast-moving vehicles, fluctuating vehicular communications, and scarce computing resources, ITS face unprecedented challenges in meeting the stringent service requirements in terms of ultra-high reliability and low-latency, demanded by the emerging mission-critical applications (e.g. autonomous driving and real-time intelligent traffic control).
To address these challenges, ASCENT aims to form an international, multidisciplinary, and inter-sectoral consortium with world-leading experts to create a novel Autonomous Vehicular Edge Computing and Networking system empowered by advanced Artificial Intelligence (AI) technologies towards achieving reliable and efficient ITS. Specifically, ASCENT will pioneer research and innovations (R&I) on ground-breaking technologies including: 1) a novel and scalable system architecture that enables agile and reliable ITS service provisioning; 2) an original distributed AI framework fuelled by bespoke federated deep learning methods to offer pervasive intelligence; 3) innovative analytics tools to accurately predict dynamic network status including network traffic and channel quality; 4) autonomous and smart resource management schemes to support mission-critical ITS services.
ASCENT will boost the R&I capability of partners in multiple disciplines and create a long-term cross-discipline and cross-sector knowledge-sharing platform with complementary expertise. The researchers involved will be trained through extensive R&I actions and well-planned networking activities to enrich their skill sets as well as enhance their career perspectives. The outcomes of ASCENT will significantly contribute to enhance the EU’s competitiveness and transforming our transportation systems into safer, smarter, and greener future ITS.

Coordinator

KUNGLIGA TEKNISKA HOEGSKOLAN
Net EU contribution
€ 105 800,00
Address
BRINELLVAGEN 8
100 44 Stockholm
Sweden

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Region
Östra Sverige Stockholm Stockholms län
Activity type
Higher or Secondary Education Establishments
Links
Total cost
No data

Participants (3)

Partners (4)