E-Drone – Transforming the energy demand of supply chains through integrated UAV-to-land logistics for 2030
Aim: 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.
Research Contribution: Agent-based modelling and multi-objective optimization with particular focus on routing and scheduling problems, service network design and transportation.
Funder: EPSRC Engineering for a Prosperous Nation
Amount: £340,382 of £1,503,867
Duration: Jan 2021 – Dec 2023
Investigators: Prof. T. Cherrett (PI), Dr B. Anvari, Prof. J. Dickinson, Prof. J. Scanlan, Prof. G. Marsden, Prof. J. Chang, Prof. J.J. Zhang
In response to EIT UM’s COVID-19 Crisis’s call:
RAPID – RApid Prototyping In 3D
Aim: RAPID will use rapid prototyping in 3D (RAPID) to support city decision making and citizen engagement around changes and interventions to the built environment in response to COVID-19 restrictions such as social distancing. The result will be more informed decision making and more engaged citizens leading to greater acceptance of new ways of moving around the city through participatory redesign of public spaces. RAPID will use a library of 3D city assets with associated rules to allow investigation of different options and will include the ability to view citizen behaviours through the use of agents. Whilst the focus of RAPID is the response to the current COVID-19 crisis it will have value beyond as cities explore new urban designs in response to changing behaviours.
This is a project funded by EIT Urban Mobility to fulfil mobility needs. The RAPID consortium is composed of 6 institutions from 3 European countries (2 research and development institutions, 2 cities and 2 industrial partners) driving a knowledge-based society. In collaboration with Pixel Mill, Studio Profondo, Fraunhofer Society, Municipality Of Sabadell, and City of Copenhagen we help increase/restore economic activity and help distribute people more evenly around a city.
Funder: EIT Urban Mobility
Amount: €347,686 (€291,113 + €56,573 in-kind contribution)
Duration: July 2020 – December 2020
UCL Investigator: Dr B. Anvari (PI/Project Lead)
AI-TraWell (reads: ʌɪ ˈtrawɛl) – AI-powered, proactive TRAvel assistant to self-monitor user’s experience & craft personalised travel solutions for promoting WELLbeing
Aim: AI-TraWell combines information on users’ needs, preferences, physical/mental wellbeing with real-time and predictive information about all modes of transport to help users to manage the increasing complexity of mobility, to deliver better and more reliable mobility services, to improve efficiency and contributes to the overall wellbeing and health of people living in our cities.
This is a project funded by EIT Urban Mobility to fulfil mobility needs. The AI-TraWell consortium is composed of 6 institutions from 4 European countries (2 research and development institutions and 2 industrial partners) driving a knowledge-based society. In collaboration with Fraunhofer Society, Achmea, Cities of Munich and Lublin, we create an AI-powered, proactive chat-bot called AI-TraWell to recommend personalised travel alternatives that fit travellers’ needs/preferences and improves their travel experience.
Funder: EIT Urban Mobility
Amount: €401,463 (€281,000 + €120,463 in-kind contribution)
Duration: January 2020 – December 2020
UCL Investigators: Dr B. Anvari (PI/Project Lead), Prof. N. Tyler, Prof. P. Jones, Dr H. Wurdemann
The Dancing Brain
This project will combine hand gestures and rhythm with mind-controlled virtual robots to enable improved social interaction and coordination among young students and people with complex learning difficulties. By transposing/translating/transcribing a message from the mind of one participant to the peers through movement, The Dancing Brain will encourage young students that STEM is fun, and empower people with dementia to create a conversation and dialogue with their peers. This is a cross-disciplinary collaboration between Akademi and the Intelligent Mobility’s group/lab at UCL (IM @UCL).
Funder: EPSRC Impact Acceleration Account
Duration: January 2020 – May 2020
Investigators: Dr B. Anvari and Suba Subramaniam
Early Career Capital Equipment
Aim: This grant will be used to procure an integrated set of physiological monitoring technologies in a car simulator in order to explore human driver interaction inside and outside of future semi-/fully-autonomous vehicles.
Funder: EPSRC Capital Award
Amount: £120,320 (£100,320 + £20,000 in-kind industrial contribution)
Duration: July 2019 – March 2020
UCL Investigators: Dr B. Anvari (PI), Dr Helge Wurdemann, Dr Laura Toni, Dr Francesca Boem, Dr Jemima Unwin, Mr Kamal Achuthan, Mr Daniel Scott, Dr Mehdi Baghdadi, Dr Will Newton, Dr Ellie Cosgrave, Dr Aneesha Singh, Dr Will McDowall.
iSeat-Towards an Intelligent Driver Seat for Autonomous Cars
Aim: The iSeat system builds upon a complete re-think of the manner in which humans interact with autonomous cars. The smart combination of sensor systems, machine learning, affective computing, human factors, haptics and robotics will result in a bi-directional human-machine cooperation that is safe, intuitive, effective, & personalised.
Funder: EPSRC Engineering for a Prosperous Nation
Duration: January 2019 – October 2020
Principle-Investigator (PI) & project partners: Dr B. Anvari (PI), Dr Helge Wurdemann and Prof. N. Stanton
G-Active – Green Adaptive Control for Future Interconnected Vehicles
Aim: G-Active aims at reducing CO2 and NOx emissions in passenger and light duty road vehicles by implementing new energy management systems which are global, predictive, adaptive, and scalable.
Research Contribution: Travel time estimation and prediction models
Amount: £263,835 of £1,668,848
Duration: November 2016 – August 2019
Investigators: Prof. R. Lot (PI), Prof. N. Stanton, Dr S. Evangelou, Dr B. Anvari , Dr S. Box
Towards A New Traffic Prediction Technique For Improving Road Safety In Brazil
Aim: The aim of this visit is to develop a model to predict vehicle’s future location using real traffic traces and improve VANETs performance
Research Contribution: A travel time estimation and prediction model
Duration: May – June 2019
Investigators : Dr B. Anvari and Prof. W. Kraus Junior
University Partnership Programme (UPP)
Research Contribution: An open-source traffic control test-bed
Amount: £74,866 of £374,330
Duration: November 2016 – March 2018
Investigators: Prof. N. Hounsell (PI), Dr B. Anvari, Prof. J. Preston, Prof. N. Stanton
Collecting and Analysing Traffic Data Through Drone Vision
Aim: This project investigated the potential benefit of leveraging Unmanned Aerial Vehicles (UAVs) equipped with Computer Vision software in the development of future Intelligent Transport Systems (ITS).
Duration: June 2017 – December 2017
Investigators: Dr B. Gao (PI), Dr B. Anvari, Prof. J. Preston, Dr. S.D. Prior, Dr. J. Hare
NIHR Global Health Research on Road Safety (16/137/122): Socio-Technical systems Approach to Road Safety (STARS)
Aim: The overall goal of this project is to reduce the number and severity of road accidents in Low- and Middle-Income Countries (LMICs) through an underpinning philosophy of “local solutions for local problems”
Amount: £70,000 of £1,986,387
Duration: August 2017 – July 2020
Investigators: Prof. N. Stanton (PI), Prof. J. Preston, Prof. P. Roderick, Dr B. Anvari, Dr K. Plant, Dr G. Yao