Research team in Transport from University of Auckland.
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We are a research team based in the Faculty of Engineering, University of Auckland. We are passionate about developing sustainable transport infrastructure and policy solutions that benefit communities worldwide. Our focus is to use cutting-edge technologies like AI and data analytics to solve complex transport problems.
TARLab is at the forefront of research in autonomous and electric vehicles. Our expertise focuses on developing advanced technologies, such as dynamic wireless charging, to ensure that electric and autonomous vehicles operate efficiently and sustainably. We are also dedicated to optimising the infrastructure for and operation of electric vehicles, making it easier and more convenient for people to adopt cleaner, greener transport options. Through our innovative approaches, we aim to pave the way for a more efficient and eco-friendly transportation future.
In collaboration with our esteemed partners at QuakeCore and innovative industry leaders like Robinsights, we're harnessing the power of cutting-edge technologies and artificial intelligence to bolster the resilience of Aotearoa's transport systems. By leveraging advanced data analytics, predictive modeling, and intelligent infrastructure monitoring, we're developing robust solutions that ensure our transportation networks remain resilient in the face of seismic events and other challenges.
Project opportunities
We are open to consutancy projects on transport and urban data analytics. We are passionate about delivering practice-ready solutions for real-world challenges.
We are looking for motivated students to join TARLab on the following research topics:
- Project 1: Shared Autonomous Vehicle Systems: optimising the operational aspects of shared autonomous vehicles (SAVs), especially electric SAVs.
- Project 2: Assessing and improving transport resilience in New Zealand
- Project 3: Balance data utility and privacy-preservation in data anonymisation and synthetic data generation
Applications are also welcome from country-specific scholarship students (e.g. China's CSC, Indonesia's LDPD or Vietnam's Project 89)
TARLab Leader, also the Future and Intelligent Transport Systems Lead at the Transport Research Centre, and the Program Director of Postgraduate Study in Civil Engineering, Faculty of Engineering, University of Auckland.
Gayani is working towards her PhD in transport resilience, in particular, a data-driven method to develop agent-based modelling of evacuation systems, such as people exiting a train station
Yunlong is a PhD scholar who is working making shared autonomous vehicles a reality in near future, such as enabling them to operate continuously around-the-clock with dynamic wireless charging
Zhihao is developing a way for autonomous vehicles to help us human drivers to merge more safely and efficiently to motorways
Funded by QuakeCORE, Junran is working towards a digital-twin of transport systems in New Zealand, with the aim of enhancing our transport network resilience.
Enyang Hao primarily focuses on urban sustainable development, with particular emphasis on areas such as smart city construction, smart community development, resilient city building, and the renovation of aging communities. His work is especially concerned with residents' willingness to participate, as well as their happiness and satisfaction in these projects. By applying management methodologies, he quantifies these factors to evaluate project performance from a fresh perspective, offering new insights into the effectiveness of urban development initiatives.
Tao Wang's research focuses on enhancing the safety of vehicle-pedestrian interactions, especially within the rapidly evolving field of autonomous driving technology. Supported by the China Scholarship Council (CSC), his work primarily concentrates on analyzing and improving conflict situations between pedestrians and vehicles within the traffic system. This research direction is crucial for understanding the dynamics of traffic behavior and plays a significant role in enhancing the safety and sustainability of urban environments.
Chengmin primarily focuses on the reconstruction and application of trajectory data, particularly for intelligent transportation systems (ITS) using roadside Infrastructure. His work starts from the installation of sensors, data collection, to application, aiming to enhance the safety and reliability of ITS