Projects: Projects for Investigator |
||
Reference Number | EP/V002619/1 | |
Title | E-Drone: Transforming the energy demand of supply chains through integrated UAV-to-land logistics for 2030 | |
Status | Completed | |
Energy Categories | Energy Efficiency(Transport) 20%; Not Energy Related 80%; |
|
Research Types | Basic and strategic applied research 100% | |
Science and Technology Fields | SOCIAL SCIENCES (Business and Management Studies) 35%; SOCIAL SCIENCES (Politics and International Studies) 15%; PHYSICAL SCIENCES AND MATHEMATICS (Statistics and Operational Research) 25%; PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 25%; |
|
UKERC Cross Cutting Characterisation | Systems Analysis related to energy R&D (Other Systems Analysis) 30%; Sociological economical and environmental impact of energy (Policy and regulation) 30%; Sociological economical and environmental impact of energy (Consumer attitudes and behaviour) 10%; Sociological economical and environmental impact of energy (Other sociological economical and environmental impact of energy) 30%; |
|
Principal Investigator |
Dr TJ Cherrett No email address given Faculty of Engineering and the Environment University of Southampton |
|
Award Type | Standard | |
Funding Source | EPSRC | |
Start Date | 01 January 2021 | |
End Date | 30 June 2024 | |
Duration | 42 months | |
Total Grant Value | £1,503,703 | |
Industrial Sectors | Energy | |
Region | South East | |
Programme | Energy : Energy | |
Investigators | Principal Investigator | Dr TJ Cherrett , Faculty of Engineering and the Environment, University of Southampton (99.994%) |
Other Investigator | Dr B Anvari , School of Engineering Sciences, University of Southampton (0.001%) Dr GR Marsden , Institute for Transport Studies, University of Leeds (0.001%) Dr JE Dickinson , Sch of Tourism, Bournemouth University (0.001%) Professor J Scanlan , Sch of Engineering, University of Southampton (0.001%) Professor J Chang , Faculty of Media and Communication, Bournemouth University (0.001%) Professor J Zhang , Faculty of Media and Communication, Bournemouth University (0.001%) |
|
Web Site | ||
Objectives | ||
Abstract | CONTEXT OF THE RESEARCH:Vans are the fastest-growing category of licensed road vehicle in the UK, significantly impacting on CO2 emissions. Vans performing service functions make up the large proportion of activity and, given the increasing access constraints imposed on freight vehicles by city authorities, alternative operating practices are being seriously investigated by logistics providers. Our proposed research into how Unmanned Aerial Vehicles (UAVs) and land logistics systems can be combined and managed to create new services will provide fundamental new understanding into the impacts of regulation and operating criteria on the energy efficiency of mixed logistics fleets. UAVs are increasingly seen as a new mode to assist in last-mile logistics with pathology being seen as a realistic domain that could utilise UAVs on a commercial scale, to significantly reduce service times and emissions. With the NHS spending an estimated 2.5 billion annually on pathology logistics and with patient numbers rising, there is a need to re-think how logistics costs could be reduced along with energy demand whilst improving the bleed-to-diagnosis times for patients. The UAV global market is estimated to grow from $2 billion in 2016, to nearly $127 billion by 2020 and will have a significant impact on both controlled and uncontrolled airspace. The greatest barrier to UAV adoption into logistics fleets is the current lack of integration of UAVs within civil airspace which requires development of suitable air traffic rules. The true energy savings and overall viability of UAVs in this domain will only be realised when the regulations governing their use and the operational implications have been quantified through simulation.AIM AND OBJECTIVES: Our research vision is to examine the energy reduction potential of logistics solutions involving UAVs operating alongside traditional and sustainable last-mile delivery solutions (vans, cargo cycles and walking porters via micro-consolidation points). This involves generating fundamental new understanding of how UAV operations will function in shared airspace alongside manned aircraft under various regulations. The project uses a case study based around NHS pathology sample transportation involving simulated and live trials across the Solent region to investigate this.Our key research objectives are to:Measurable objectives:1) Investigate the collective transport and energy impacts of current 'business-as-usual' NHS pathology logistics across the Solent region.2) Develop new simulation tools to quantify the energy consumption of UAVs and land logistics systems resulting from: i) potential new types of traffic regulation for shared airspace; ii) UAV collision and dynamic automated path re-planning stipulations; iii) conflict-resolution rules; iv) types of permitted coordination; v) the availability and positioning of ground logistics systems and infrastructure to effectively interact with and service UAVs.3) Evaluate using the simulation tools and live trials the impact on air space and energy use of a large scale take-up of UAVs for medical logistics across the Solent region.4) Develop fundamental new understandings of stakeholder concerns and the regulatory and governance needs associated with UAV interventions that realise energy benefits in logistics. POTENTIAL APPLICATIONS AND BENEFITS: Our research outcomes will be trialled by Meachers Global Logistics and Steve Porter Transport as part of the project and will provide evidence of the tangible benefits to carriers from adopting UAVs into their logistics fleets. The project will provide evidence for UAV regulation and management policies for shared airspace, highlighted as a key requirement by the Department for Transport, the Civil Aviation Authority and NATS. It will also provide the first concrete evidence of the energy demand benefits of integrating UAVs with land logistics under real operating and regulatory conditions | |
Data | No related datasets |
|
Projects | No related projects |
|
Publications | No related publications |
|
Added to Database | 21/09/21 |