Vehicles equipped with tracking technologies generate vast amounts of data, offering insights for transport operations, planning, and safety. Aston’s expertise in machine learning, AI, and transport engineering will unlock this data’s full value, optimising operations, enhancing safety, and driving sustainable mobility solutions. This will involve research challenges such as integrating and managing large-scale datasets, as well as ensuring privacy and security compliance.
This project aims to use vehicle tracking data for optimising transport operations, planning, and safety through analytical methods with the following specific objectives:
- Develop privacy-compliant methods for integrating and standardising data from multiple sources.
- Build accurate, scalable multi-agent models for predictive traffic analytics using multi-source data.
- Design real-time optimisation and autonomous co-ordination algorithms that incorporate external factors like weather and infrastructure conditions.
By unlocking the full potential of these datasets, the research will revolutionise traditional transport modelling, enabling more accurate decision-making and new applications in transport planning.
What Makes This Project Unique
This project combines industry data (Mobito), deployment opportunities (e.g., Coventry City Council trials), and Aston’s ACAIRA centre’s AI resources. Candidates will pioneer solutions with impact, supported by a globally recognised supervisory team.
Supervisory Team & Research Environment
The supervisory team brings complementary expertise in intelligent transport systems, machine learning, and agent-based modelling. Dr Tong has over 25 years of experiences in traffic engineering and transport modelling. He is a known expert in analysing vehicle tracking data to develop driving cycles that have been adopted by governments and academics. Dr Chli leads a research group with an international reputation in AI for smart cities, including deep reinforcement learning for traffic optimisation and agent-based modelling for policy and infrastructure simulation. Her recent work deployed in Coventry City Council—has received national and international attention (BBC News, Deutsche Welle, Radio NZ).
The successful candidate will benefit from the dynamic environment of Aston’s Centre for Artificial Intelligence Research and Application, and the transport research group. Interaction with active Knowledge Transfer Partnerships in related topics, real-world datasets, and cutting-edge AI technologies will support impactful, publishable research with strong translational value.
Industry Partnership with Mobito:
Mobito, a leading European data mobility platform, will provide exclusive access to high-quality, real-world datasets and valuable industry insights. This collaboration enhances the real-world impact of the research and strengthens the link with commercial deployment.
Data Sources and Technologies:
The project will utilise diverse, high-resolution datasets from vehicles, sensors, and open-source transport feeds. Core technologies include Python, PyTorch for machine learning, geospatial data platforms, and cloud-based processing frameworks such as AWS or Azure. Access to Mobito’s mobility data marketplace may provide rare and commercially valuable datasets.
Industry Exposure and Opportunities:
There will be opportunities to engage directly with Mobito’s data science and business teams through collaborative sessions, internship opportunities, and visits to Mobito’s offices.
Candidate Development Opportunities:
- Experience developing and deploying AI algorithms in real-world traffic systems.
- Exposure to cutting-edge AI methods, including transfer learning, agent-based modelling, and simulation synthesis.
- Opportunity to co-author with a team recognised for top-tier publications (e.g., AAMAS, ITSC, JAIR, TRA, TRC).
- Support for attending high-profile conferences and AI policy forums (e.g., Turing Institute’s AI UK, IEEE ITSC, TRB Annual conference, HKSTS).
- Mentorship within a globally connected AI research team with a strong industrial and civic partnership network, boosting employability and innovation skills