Sustainable mobility and connected transportation
About the program
Innovative Planet Research Institute’s sustainable mobility and connected transportation research program is led by Associate Professor Hailing Zhou in the Department of Mechanical and Product Design Engineering.
Associate Professor Zhou heads a team of experts who are exploring and evaluating new approaches to mobility and transport – aiming to develop sustainable policies and practices that improve quality of life, access to services and locations, reduced energy use and congestion, lower costs and impact on the environment, and potential access to new economic opportunities.
Sustainable mobility and connected transportation combines disciplines such as robotics, autonomous vehicles, material and manufacturing engineering, infrastructure, networking, communications, transportation management and road safety to develop safe, resilient urban transport and mobility solutions that connect the social, physical, economic and information infrastructures of our daily lives.
Our research
The program’s key objectives are to encourage sustainable practices, enhance transport-related safety, and improve urban and rural mobility and connectivity through four main areas of research.
Autonomous vehicles
Autonomous (or uncrewed) vehicles use technology to fully or partially replace a human driver, while navigating road hazards and changing traffic conditions, and currently includes developments such as cruise control and automated steering.
Continued exploration of sustainable energy and materials and technologies, advanced control, navigation and perception technologies, energy-efficient algorithms, AI and autonomy have potential applications in agriculture, delivery and defence.
Electric vehicles
The shift from non-renewable fuel sources to electric vehicles (EVs) is benefiting from developments in EV charging infrastructure, the creation of battery management systems to monitor and optimise performance, longevity and safety, and developing consistent EV standards and compliance regulations.
Road infrastructure
Ensuring road safety is a key issue in transport. Researchers are designing technological solutions to reducing road hazards, including sustainable roller barriers, ways of predicting and interpreting crash severity, and the development of intelligent surveillance and monitoring for traffic optimisation and in-time response to accidents.
In-car and car-to-car systems
As individual car systems become more automated, close attention is being paid to how systems communicate within a vehicle, and how a vehicle’s systems connect to other vehicles or operational bases, particularly with uses in dangerous procedures relating to industry and defence.
Our research focuses on vehicle-to-everything communications, cybersecurity measures to secure connected transportation systems, and the creation of advanced driver assistance systems (ADAS).
Our currect projects
This road safety project is optimising the design of roadside safety roller barriers (SRBs) to enhance road infrastructure safety. These innovative SRBs use foam rollers to absorb and convert shock energy from vehicle collisions into rotational energy.
This unique mechanism mitigates the impact force during accidents – significantly reducing the risk and severity of injuries. The project aims to refine the SRBs’ structural design and material composition to maximise their effectiveness, durability and adaptability to diverse road conditions.
This work has secured funding from the National Road Safety Action Grants Program (via the Department of Infrastructure, Transport, Regional Development, Communications and the Arts) – supporting our ability to advance research, implement pilot installations and evaluate performance in real-world scenarios.
The spatial mapping project aims to develop cutting-edge cross-view image geo-localisation technology capable of spatially matching target regions captured from diverse perspectives, including ground-level cameras, uncrewed aerial vehicles (UAVs) and satellite imagery.
By using advanced image analysis and extraction techniques to identify and align different viewpoints of a particular geographical location, operators will be able to locate a target precisely within the matching image.
The integration of spatial data from multiple perspectives allows improved situational awareness, operational efficiency and decision-making in scenarios where traditional GPS solutions are unavailable or unreliable. Applications for the technology include urban planning, disaster management, autonomous navigation and environmental monitoring.
In collaboration with the University of New South Wales, this project seeks to advance the real-time prediction of the State of Health (SOH) of lithium-ion batteries, which are the preferred energy source for electric vehicles (EVs) due to their high energy density, low self-discharge rate and broad operating temperature range.
Accurate SOH estimation is essential for the effective health monitoring and cost-efficient operation of EVs and energy storage systems. However, existing methods, such as ohmic resistance and capacity comparison techniques, are constrained by their sensitivity to operating conditions – including temperature variations – and substantial computational demands.
To address these limitations, the project aims to develop a novel approach for classifying battery health features and estimating SOH with improved accuracy and reliability under real-time conditions. By overcoming the challenges of current methodologies, this research has the potential to enhance battery performance management, extend operational lifespan and support the broader adoption of sustainable energy solutions.
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Have a question?
For more information, please contact our research program leader Associate Professor Hailing Zhou at hailingzhou@swinburne.edu.au.