School of Civil Engineering

Projects in Traffic and Transport engineering

Supervisor:             Dr Jiwon Kim

Undergraduate/postgraduate research projects are available in Traffic and Transport Engineering, in the areas of traffic flow analysis, data mining and machine learning applications in transport research, Big Data and predictive analytics for intelligent transport systems (ITS). 

The overall goal of the current research is to leverage new sources of data such as GPS trajectories and public transport Smart-Card data to gain better insights into urban traffic dynamics and enable better design and operation of urgan transport systems

Potential research topics include:

  • Network traffic analysis using spatiotemporal data mining: traffic anomaly (traffic incident, flow breakdown/traffic jam) detection, congestion propagation pattern analysis, incident impact analysis, event correlation and root cause analysis, etc.
  • Analysis of urban commuting patterns using bus passenger trajectories
  • Examining public transport travel time variability using GoCard data
  • Validating traffic simulation models using vehicle trajectory data
  • Analysis of pedestrian crowd dynamics using pedestrian trajectories
  • Agent-based modelling and simulation of pedestrian/passenger facilities (e.g., bus/rail station platforms)

Through the project activities, students will understand how to transform data into useful information to support decision making in traffic management and transport planning and will learn practical skills in data mining, statistical analysis, and data visualization.

Prerequisite:            Basic programming skills in MATLAB or similar (e.g., R, Python, C/C++)