Projet ASCENT (Horizon Europe, appel à projets 2021)
Action : Staff Exchanges
Panel : Information Science and Engineering
Statut du projet : SIGNED

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.

Mots clés : internet of vehicles, edge computing, machine learning, intelligent transportation systems

Participants :
- Greensphere unipessoal lda (Portugal) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 115000.0 €
- Université des sciences et technologies électroniques de Chine (Chine) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- Ranplan wireless network design ltd (Royaume-Uni) — Partner, associated partner, Organismes privés (hors enseignement), subvention : 0.0 €
- Université d'Exeter (Royaume-Uni) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €
- KTH Institut royal de technologie (Suède) — Coordinator, beneficiary, Enseignement supérieur ou secondaire, subvention : 105800.0 €
- Université de Jyväskylä (Finlande) — Partner, beneficiary, Enseignement supérieur ou secondaire, subvention : 119600.0 €
- Cumucore oy (Finlande) — Partner, beneficiary, Organismes privés (hors enseignement), subvention : 110400.0 €
- Université Tongji (Chine) — Partner, associated partner, Enseignement supérieur ou secondaire, subvention : 0.0 €