Grants

Current:

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 BMW Group, 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.
Amount: €281,000 (+ €120k in-kind contribution) – UCL portion is €120,463
Duration: January 2020 – December 2020
Investigators: Dr B. Anvari (PI), Prof. N. Tyler, Prof. P. Jones, Dr H. Wurdemann

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.
Amount: £99,330 (+ £20,000 in-kind industrial contribution)
Duration: July 2019 – March 2020
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.
Amount: £251,453
Duration: January 2019 – June 2020
Principle-Investigator (PI): Dr B. Anvari

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
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: Travel Time Estimation and Prediction
Amount: £3,078
Duration: May – June 2019
Investigators : Dr B. Anvari and Prof. W. Kraus Junior


Past:

University Partnership Programme (UPP)
Research Contribution: 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).
Amount: £6,319
Duration: June 2017 – December 2017
Investigators: Dr B. Gao (PI), Dr B. Anvari, Prof. J. PrestonDr. S.D. PriorDr. 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. RoderickDr B. Anvari, Dr K. Plant, Dr G. Yao