Hybrid drone/truck last mile delivery planning for e-groceries
In this PhD project multiple trucks, each of which is equipped with drones, will via simulation deliver grocery purchases in parallel to customers.
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.
Smart bridge health monitoring and maintenance prediction
This project investigates the use of an integrated package of IoT, computer vision and machine learning to support smart bridge health monitoring and prediction.
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.
Scenario developments for forecasting urban freight shifts
This project will develop a framework/tool for forecasting future scenarios of urban freight in informing planning and regulation (transport and land use).
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.
Advanced data analytics: Real-time demand calibration/prediction
This project aims to improve travel demand calibration and accuracy of 24 hour/ 7 days network simulation models for any hour of any day.
Role of heterogeneity in active travellers’ injury severity analysis
This PhD research will develop and apply advanced econometric models in estimating injury severity models for active travellers.
CAVs: Barriers and opportunities for people with disability
The iMOVE project Australia’s Public Transport Disability Standards and CAVs project has been completed, and final reports are available for download.
Empirical modelling of traffic states and route choice behaviour
In this PhD project data analytics on Bluetooth trajectories and traffic states will be applied to empirically estimate the assignment matrix for the network.
Government initiatives to support women in the transport sector
This project will identify the barriers to women entering & progressing within the transport sector workforce, & audit/evaluate government initiatives in this area.
Advanced driver state monitoring system
This PhD project aims to develop a system with a data-driven human driver behaviour model that can help detect the attention level of drivers.
MaaS and PT integration: Focus on vulnerable travellers
This PhD project will focus on smart adoption of MaaS with the purpose of providing vulnerable travellers with equitable mobility services.