Vision & Mission
To improve urban transport systems through innovative research and technology, creating safer, more efficient, and sustainable cities.
Our mission is to develop intelligent transportation technologies, Connected and Automated Vehicles (CAVs), and smart infrastructure solutions. We work with global partners to solve mobility challenges, enhance road safety, and make transport systems more effective.
Projects
Our team is involved in several key research and development projects:
Data Analytics for Autonomous Vehicle Testing (iMOVE – TfNSW)
Collecting and analysing environmental and traffic data from various sensors (LiDAR, cameras, GPS) to improve Autonomous Vehicle performance. This data includes detailed semantic labels to help refine models and improve their real-world adaptability.
Data Analytics for Autonomous Vehicle Testing (iMOVE – TfNSW)
Collecting and analysing environmental and traffic data from various sensors (LiDAR, cameras, GPS) to improve Autonomous Vehicle performance. This data includes detailed semantic labels to help refine models and improve their real-world adaptability.
Large Animal Activated Roadside Monitoring System (LAARMA – iMOVE – TMR)
A system designed to detect large animals near roads and alert drivers, reducing the risk of collisions. It focuses on detecting animals from a distance of 200-300 meters in various weather and lighting conditions.
Cooperative Intelligent Transport Systems (C-ITS) on NSW Roads
Testing CAV technologies on NSW roads to study their impact on traffic safety and management. This project helps inform future transport policies by exploring data from connected vehicles and smart infrastructure.
TfNSW Australian Driving Dataset
A collaborative project to build a dataset for 3D object detection in autonomous vehicles. The dataset includes synchronised sensor data from vehicles, enhancing research in AV technology.
ADAS Quality Assessment
A project to evaluate the real-world performance of Advanced Driver Assistance Systems (ADAS) like lane-departure warnings. It helps improve insurance models and overall road safety by assessing how drivers interact with ADAS technologies.
Collaborators
- International Partners:
- Renault (France)
- Cornell University (USA)
- École Centrale de Nantes (France)
- Australian Partners:
- Transport for New South Wales (TfNSW)
- Insurance Australia Group (IAG)
- Department of Transport and Main Roads (TMR)
- National Transport Research Organisation (NTRO)
- Cohda Wireless
We would like to acknowledge the support of HxGN SmartNet for providing RTK GPS corrections. This contribution has been valuable in providing ground truth positioning for our research.
Fundamental Research
Our research covers several key areas within intelligent transportation systems:
- V2X Communication: Developing systems that allow vehicles to communicate with each other and with infrastructure, improving connectivity and road safety.
- Cooperative Perception: Enhancing how vehicles and infrastructure perceive their environment using LiDAR and camera systems for more accurate detection and decision-making.
- Scene Understanding & Localisation: Improving vehicle localisation and mapping to ensure accurate positioning and safer autonomous driving.
- Data Analytics: Using machine learning to analyse large datasets and generate insights that improve the performance of autonomous vehicles and traffic systems.
Hardware
We use advanced technology to support our research projects:
- Intelligent Roadside Units (RSUs): Devices that monitor and communicate real-time traffic data, improving the management of road networks.
- Advanced Sensor Systems: Vehicles equipped with LiDAR, cameras, GPS, and Inertial Measurement Units (IMUs) for high-quality data collection.
- ADAS Testing Platforms: Vehicles with built-in sensors that collect data on driver behavior and interaction with advanced driver assistance systems.
Datasets
We maintain several valuable datasets for use in transportation research and development:
- Autonomous Vehicle Driving Data: Data collected from vehicles equipped with advanced sensors, including detailed labels for refining vehicle models.
- Large Animal Detection Dataset: Data from roadside monitoring systems designed to detect animals and improve road safety.
- Cooperative Vehicle and Infrastructure Data: Real-world data from connected vehicles and infrastructure on NSW roads to support cooperative transport systems.
- TfNSW Australian Driving Dataset: A dataset for 3D object detection in autonomous vehicles, collected using synchronised sensor platforms.