Projects
Projects: Projects for Investigator |
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| Reference Number | EP/X038866/1 | |
| Title | ASCENT: Autonomous Vehicular Edge Computing and Networking for Intelligent Transportation | |
| Status | Started | |
| Energy Categories | Energy Efficiency(Transport) 10%; Not Energy Related 90%; |
|
| Research Types | Basic and strategic applied research 100% | |
| Science and Technology Fields | PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 75%; ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 25%; |
|
| UKERC Cross Cutting Characterisation | Not Cross-cutting 100% | |
| Principal Investigator |
Professor G Min No email address given Computer Scienc University of Exeter |
|
| Award Type | Standard | |
| Funding Source | EPSRC | |
| Start Date | 01 March 2023 | |
| End Date | 28 February 2027 | |
| Duration | 48 months | |
| Total Grant Value | £237,858 | |
| Industrial Sectors | ||
| Region | South West | |
| Programme | UKRI MSCA | |
| Investigators | Principal Investigator | Professor G Min , Computer Scienc, University of Exeter (100.000%) |
| Web Site | ||
| Objectives | ||
| Abstract | 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 | |
| Publications | (none) |
|
| Final Report | (none) |
|
| Added to Database | 19/04/23 | |
