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Real-Time Vehicle Tracking for Smarter Transport Decisions

Aston University College of Engineering and Physical Sciences
✓ Fully Funded ⏰ Closing Soon 🎓 Artificial Intelligence 🎓 Data Analytics 🎓 Engineering 🎓 Intelligent Transport Systems 🎓 Machine Learning 🎓 Transport Engineering phd AI fully funded UK machine learning Aston University Birmingham real-time analytics transport vehicle tracking

A fully funded PhD at Aston University leveraging vehicle tracking data to optimise transport operations, planning, and safety using AI and machine learning

Project Description

The project focuses on real-time analysis of vehicle tracking data to improve transport systems. Key activities include: Developing privacy-compliant methods for integrating and standardising multi-source vehicle data. Building multi-agent predictive traffic models. Designing real-time optimisation and autonomous coordination algorithms, incorporating external factors such as weather and infrastructure conditions. Using industry datasets provided by Mobito and engaging with Coventry City Council deployment trials. Applying Python, PyTorch, geospatial platforms, and cloud-based frameworks (AWS/Azure) for data processing and modelling.

Entry Requirements

Bachelor’s (First Class/2.1) or Master’s degree (Merit or higher) in AI, Machine Learning, Control, Transport Engineering, or a closely related field.
Strong programming skills.
Interest in AI applications in transport systems and intelligent transport.
Desirable: Experience with deep reinforcement learning, traffic engineering, ROS, or smart mobility frameworks.

How to Apply

Submit CV, transcripts, research statement, personal statement, and references via Aston University application system.
Contact Dr Hing Yan Tong for informal enquiries: h.tong1@aston.ac.uk

Eligibility

UK/Home
EU
International

Supervisor Profile

DH
Dr Hing Yan Tong
Aston University, College of Engineering and Physical Sciences

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