Shihan Xu – iMOVE PhD student
A profile of iMOVE PhD student Shihan Xu and her project, ‘Estimating freight origin-destination activity using video and data’.
Samson Ting – iMOVE PhD student
A profile of iMOVE PhD student Samson Ting and his project, ‘Using a data-driven approach to improve intersection modelling’.
Amir Hosein Jabbari Sabegh – iMOVE PhD student
Amir Hosein’s iMOVE PhD project is ‘Decentralised data sharing platform for supply chains’. This profile backgrounds his work, lessons learnt, and more.
Chintan Advani – iMOVE PhD student
Chintan Advani’s PhD topic is ‘Empirical modelling of traffic states and route choice behaviour’. This profile outlines his work, lessons learnt, and more.
The relationship between vehicle telemetry and sustainability
The objective of this PhD project is to analyse the relationship between telemetry and its impact on commercially sustainable transportation solutions/networks.
Emergency facilities location and transportation routing
This PhD project will develop traffic management strategies and infrastructure allocation algorithms needed to improve emergency vehicle logistics.
Real-time crash risk estimation using machine learning
Using state-of-the-art machine learning algorithms, this study will use a novel modelling approach to accurately predict traffic crashes in real-time.
Building trust and collaboration among MaaS stakeholders
This PhD project will, at its conclusion, demonstrate how the roles and responsibilities of different stakeholders impact building a collaborative MaaS environment.
Implementation of sustainable transport policies
This PhD project explores cycle lane implementation from both a policymaker’s and user’s perspective, and flexible transport solutions for rural users.
Bus performance assessment using GTFS data
This PhD project will analyse archived GTFS data to identify significant inefficient road designs and exemplary designs for optimising performance
Optimising multimodal transport networks: Sharing road space
This research will focus on enhanced depiction of pedestrian and active mode interactions with vehicular traffic across a variety of road infrastructure scenarios.
Innovative road network pricing models
This PhD research aims to investigate new methods for managing urban congestion and reducing emissions through innovative transport pricing policies.
Co-operative eco-driving system for mixed traffic on urban roads
The objective of this PhD study is to develop an eco-driving system for a mixed traffic consisting of CAVs and human-driven vehicles (HVs) on urban roads.
Transformative commercial urban delivery solutions
This research aims to identify and evaluate new solutions for commercial urban deliveries to meet the demand of last-mile and surging e-commerce markets.
Macroscopic Fundamental Diagram: Measuring flow and density
Research into a network-wide approach to identify critical links and estimate the Macroscopic Fundamental Diagram using flow and density measurements.
Demand management/estimation in large-scale traffic networks
Development of demand management & estimation tools for large-scale traffic networks, incorporating macroscopic fundamental diagram-based traffic dynamics.