Research and expertise
Artificial intelligence is steering smart cities and transforming urban mobility. This offers opportunities to better meet and shape the growing and ever-changing demand for mobility, while reducing its carbon footprint to meet net-zero goals. To this end, I lead the Transport AI Innovation Centre at º¬Ðß²ÝÊÓƵ to develop deep digital technologies that drive forward disruptive dimensions of future mobility: automation, electrification, connectivity, shared mobility, and active travel.
My research expertise lies in simulation, machine learning, and digital twinning approaches for scenario testing and optimisation that captures the complex interactions between people, traffic, transport infrastructure and services, and the wider built environment. Specifically, I develop fundamental methodologies in traffic flow theory, activity and agent-based modelling, simulation-based optimisation, deep learning, statistical learning, active learning, large language models, etc. My research delivers critical data and digital tools to improve traffic management, reduce emissions, enhance transport services, boost evidence-based policies and data-driven interventions.
I welcome enquiries from postgraduates who wish to study for a PhD or pursue postdoctoral research in my areas of research interest.
Current research activity
- Multimodal urban transport: integrated modelling and simulation towards net-zero, inclusive mobility (UKRI Future Leaders Fellowship)
- TraffEase: Predictive traffic analytics with natural language queries (Manchester Prize)
- Foot traffic analytics (The Town Observatory º¬Ðß²ÝÊÓƵ)
Recently completed research projects
- BusMONITOR: A sophisticated data monitoring, aggregation and analysis solution for bus operation (KTP with Vectare)
- AI and Smart Mobility (Institute of Advanced Studies, º¬Ðß²ÝÊÓƵ)
- SignBus: Smart signals and infrastructures to provide bus priority (Swiss National Science Foundation)
- WEAVE: Highway weaving sections design and capacity (Research Commission for Road Transport in Switzerland)
Recent publications
- Schumann, H., Haitao, H., & Quddus, M. (2023). Passively generated big data for micro-mobility: State-of-the art and future research directions, Transportation Research Part D: Transport and Environment, 121, 103795.
- Mangold, M., Zhao, P., Haitao, H., & Mansourian, A. (2022). Geo-fence planning for dockless bike-sharing systems: a GIS-based multi-criteria decision analysis framework. Urban Informatics, 1(1), 1-15.
- Reck, DJ., Haitao, H, S. Guidon and KW. Axhausen (2021), Explaining shared micromobility usage, competition and mode choice by modelling empirical data from Zurich, Switzerland, Transportation Research Part C: Emerging Technologies, 124, 102947.
- Zhao, P., Haitao, H., Li, A., & Mansourian, A. (2021). Impact of data processing on deriving micro-mobility patterns from vehicle availability data. Transportation Research Part D: Transport and Environment, 97, 102913.
- Li, A., Zhao, P., Haitao, H., Mansourian, A., & Axhausen, K. W. (2021). How did micro-mobility change in response to COVID-19 pandemic? A case study based on spatial-temporal-semantic analytics. Computers, Environment and Urban Systems, 90, 101703.
- Haitao, H., K. Yang, H. Liang, M. Menendez and I. Guler (2019), Providing public transport priority in the perimeter of urban networks: a bimodal strategy, Transportation Research Part C: Emerging Technologies, 107, 171-192.
- Haitao, H., M. Menendez and I. Guler (2018) Analytical evaluation of flexible-sharing strategies on multimodal arterials, Transportation Research Part A: Policy and Practice, 114, 364-379.
Teaching
Since joining º¬Ðß²ÝÊÓƵ, I have contributed to the following learning and teaching activities across the Urban Planning programme and the Civil Engineering programme:
Undergraduate
- CVA130 Design Skills and Urban Data Analytics
- CVB120 Research Methods and Digital Skills
- CVC110 Transport Infrastructure Engineering
- CVC115 Future Cities
- CVC072/CVP363 Smart Cities and Mobility
Enterprise
Current projects
- TraffEase: Predictive traffic analytics with natural language queries (Manchester Prize)
Recently completed projects
- BusMONITOR: A sophisticated data monitoring, aggregation and analysis solution for bus operation (KTP with Vectare)
- Roll2Go AG: A data-centric platform for mobility data fusion and predictive analytics (ETH Spin-off company)
Consultancies
- City-scale urban simulation and analytics (Beijing Academy of Urban Planning and Design)
Key industry collaborators
- Nottingham City Council
- Transport for Greater Manchester
- Transport for London
- Department for Transport
- Arup
- Atkins
- WSP
- Siemens (Yunex)
- PTV
- Aimsun
- O2 (Telefonica)
- Lime
- Beam
- Vectare
Profile
With a background in mathematics and extensive experience in modelling across physics, transportation, and AI, I have pursued an educational journey across five countries and held professional roles in both academia and industry. Witnessing urban sprawl in China and the US, contrasted with sustainable development in Singapore and Switzerland, has shaped my vision for creating a sustainable future society through technological advancements.
Therefore, after graduating from the National University of Singapore with a first-class honours degree in physics and mathematics, I pursued an MPhil in sustainable engineering at the University of Cambridge. Recognising the profound impact of transportation on the economy, sustainability, and resilience of cities, I then completed a PhD at ETH Zurich, focusing my dissertation on the modeling of multimodal transport systems across different infrastructure levels.
To drive research impact in the real world, after obtaining my PhD, I co-founded Roll2Go, an ETH spin-off providing digital tools for shared micromobility. Under my leadership, the spin-off company has won prestigious competitions, awards, and grants from VentureKick, IMD, Innosuisse, European Institute of Innovation and Technology, and Horizon 2020, leading to its successful acquisition by Bond Mobility within two years.
I then joined º¬Ðß²ÝÊÓƵ in 2019. Returning to academia has allowed me to lead the development of fundamental AI research underpinning transformative tools for sustainable, resilient, and equitable mobility solutions that enhance the quality of life for all. Developing AI in the transport field intrigues me because it encapsulates the complexities of human behaviour and societal values, which are crucial for advancing towards AGI, while delivering immediate benefits for the public good. In 2023, my research excellence was recognised with a prestigious UKRI Future Leaders Fellowship.
Understanding the complex, multifaceted challenges in transport that call for interdisciplinary collaboration to amplify the impact of our research, I have led the establishment of the Transport AI Innovation Centre at º¬Ðß²ÝÊÓƵ in 2024 as the inaugural director. With over 70 academic staff from all nine Schools at º¬Ðß²ÝÊÓƵ, we will together develop deep digital technologies that drive forward disruptive dimensions of future mobility: automation, electrification, connectivity, shared mobility, and active travel.
Awards
- Manchester Prize top-10 finalist (2024)
- UKRI Future Leaders Fellowship (2023)
- Best paper award, Journal of Urban Informatics (2023)
- School mentoring award (2023)
- Traffic4Cast competition finalist (2022)
- Winner of Transport Innovation Challenge by the European Commission's Directorate-General for Mobility and Transport (2019)
- Student Fellowship for International Symposium on Transportation and Traffic Theory (2017)
External activities
- Deputy Director, European Association for Activity-Based Modelling (EAABM), 2024-
- Chair, UK Task Force for Activity and Agent-based Modelling, 2024-
- Chair, IEEE COINS conference Mobility Track, 2024
Key academic collaborators
- MIT
- ETH
- University of Cambridge
- Imperial College London
- UCL
- National University of Singapore