People, environments and performance
This group supports research into the design of the interior and outdoor spaces for people, and how their perceptions and performance are affected by changes in environmental stimuli.
This group leads research in two interrelated themes: (i) the design of the interior and outdoor spaces for people, how people behave in these spaces and how their perceptions and performance are affected by changes in environmental stimuli, (ii) the simulation of resource flows at scales ranging from buildings, through neighbourhoods, to cities and nations; these simulation progressively incorporate models developed in theme i.
Key areas of research are lighting, environmental design, climate analysis and microclimate modelling, multiscale resource flow modelling, and construction materials. We use a range of research methods - field studies, laboratory experiments, big data analyses, statistical modelling and multi-agent simulation, and physical modelling.
A main focus of theme (i) is the interaction between people and their environments. For example, we investigate occupants’ activities, behaviours and the comfort consequences of these behaviours. We have particular expertise in the modelling of thermal comfort and overheating risk. We also examine the interaction between people and the outdoor built environment. For example, our lighting research focuses on outdoor lighting and how it influences behaviour after dark. This includes studying the effects of road lighting on walking and cycling behaviour, and the safety of pedestrians and cyclists.
In theme (ii) we develop physical, statistical and computational modelling and simulation techniques and workflows to improve peoples’ comfort and reduce their carbon impacts. In particular, we develop advanced modelling and simulation techniques to examine the interface between people, buildings and cities, particularly looking at how energy performance is influenced by occupant behaviour, spatial and functional structures of urban systems, and the evolution of regional and national building stocks over time. A major part of this involves developing predictive models that account for the presence of people, their activities, behaviours and comfort. In this we also develop computational workflows to improve the efficiency of these simulation endeavours, considering both data management and computational cost.
- Lighting and travel
Investigating how outdoor lighting affects transport safety and more sustainable modes of travel such as walking and cycling
- Behavioural modelling
Stochastic modelling of occupants’ energy-related behaviours and their comfort; integration of multi-agent stochastic simulations (MASS) of these models with dynamic building-scale, urban-scale and national-scale energy simulations.
- Comfort and overheating
The modelling and assessment of occupants’ comfort and the feedback to comfort from occupants’ behaviours; personalised comfort systems; under- and over- heating risk.
- Building performance evaluation
Development of IOT-based technologies to support low-cost longitudinal monitoring of building performance; machine learning techniques to analyse this data, feedback to building performance dashboards.
- Multi-scale energy simulation
Energy simulation and optimisation of rural off-grid micro-grids; urban energy microsimulation; national housing stock energy simulation and the dynamic evolution of these stocks; emulation of multiscale energy simulations; uncertainty quantification and decomposition; parametric modelling and optimisation of incremental housing; simulation building-microclimate interactions and implications of energy, comfort and health.
- Integrated assessment modelling
Downscaling global integrated assessment models through national to urban/regional scales; calibrating these models; deploying these models to support climate change policy.
- Low impact materials
We focus on the use of timber and bamboo during building construction
HAzards, ROad Lighting and Detection (EPSRC): 2019-2022. We investigate the impact of driver distraction on hazard detection with a focus on raising the conspicuity of pedestrians.
- Road lighting, fog and driver hazard detection (project for Highways England)
We investigated how fog and road lighting affect hazard detection.
- MERLIN and MERLIN-2
Road lighting for pedestrians [EPSRC]. 2011-2015, 2015-2018. A study of pedestrians needs (for safety and perceived safety) and how these are affected by changes in road lighting.
Light, Cognition, Attention, Perception (EU ITN). 2020-2023. The impact of non-image forming pathways of the visual system on hazard detection for drivers and at pedestrian crossings
- Unlocking the potential for model-predictive control (MPC) in building energy management (EPSRC)
2016-2020. We develop synthetic data from stochastic models of occupants’ behaviour coupled with building energy models, to train MPC algorithms.
- UKRI Innovation Fellowship on Housing Stock Decarbonisation (ESRC)
2017-2021. We develop and deploy a sophisticated housing stock energy modelling platform to support the formulation of national housing stock decarbonisation policy.
HAROLD: HAzards, ROad Lighting and Driving
Funding: EPSRC, £1.2M
The aim of this research is to improve drivers’ ability to detect hazards, with a focus on detecting pedestrians, using road lighting and active visibility aids. The project is led by Professor Steve Fotios in collaboration with Leeds University Institute of Transport Studies.
Unlocking the potential for model-predictive control in building energy management
Funding: EPSRC, £100K
Current methods for controlling building systems are poor at anticipating the demand for heating, ventilating and cooling to meet occupants’ needs. A team of researchers from the School of Architecture and Departments of Civil and Electrical Engineering will develop and test a new Model Predictive Control Algorithm to control heating, ventilating and cooling systems in buildings
UKRI Innovation Fellowship on Housing Stock Decarbonisation
Funding: ESRC, £260k
The aim of this research is to consolidate and deploy an advanced dynamic housing stock energy simulation platform EnHub, to support the formulation of national housing stock decarbonisation policy measures and to evaluate their effectiveness. In this, to complement the physical simulations of EnHub with new social simulations on household decarbonisation investment decisions, calibrated using dedicated (pilot) panel survey data.
- Wen-Shao Chang
- Chris Cheal
- Steve Fotios
- Chloe Robbins
- Chengzhi Peng
- Darren Robinson
- Sally Shahzad
- Jim Uttley
- Tsung-Hsien Wang
- Parag Wate
- Ben Purvis
- Gustavo Sousa
- Choo Yoon Yi
- Tha'er Abdalla
- Asma Rashid Abdullah Al Maqbali
- Jaihui Cheng
- Sergio Edgar Mauricio Poco Aguilar
- Reena J Sayani
- Al-Chokhdar Yussur
- Shen Chen
- Wenbin Lei
- Aleksandra Liachenko Monteiro
- Yichong Mao
- Choong Yew Chang
- Khalid Hamoodh
- Intisar Hussain
- Scott Fox
- Maan Balela
- Aysheh Alshdaifat
- Nima Hafezparast Moadab
- Mohammed H Aljammaz
- Omar SA Hamed
- Esti Nurdiah
- Yan Gao
- Yi Yang
- Na Tang
- Yiping Meng
- Olivia Trujilo
- Gioia Fusaro
- Ying Liu
- Meryem Gurel
- Boyan Zhang
- Ibrahim Halil Ozdemir
- Jiayu Guo