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Relationship between speed, traffic volumes and road geometry on heavy vehicle crash rates

The overall objective of this research, in conjunction with previous research undertaken by the Department of Transport and Main Roads (TMR), is to determine how the type, mass and length of heavy vehicles affects the type, severity and rate of crashes.The objective of this specific piece of research is to determine how parameters such as speed limits, traffic volumes and road infrastructure affects the type, severity and numbers of heavy vehicles crashes.

Study level
PhD, Master of Philosophy
Faculty
Science and Engineering Faculty
Lead unit
School of Civil Engineering and Built Environment

Development of generalized crash prediction models

This project will develop both Safety Performance Functions (SPFs) and generalized crash estimation and severity models for Queensland.The development will be guided by Queensland Department of Transport and Main Roads (TMR)’s need for innovation and the exploration or emerging technologies and techniques.This project is expected to provide the foundation for future research that over time will provide a complete and comprehensive approach for traffic safety management using state-of-the-art modelling and analysis techniques. …

Study level
PhD, Master of Philosophy
Faculty
Science and Engineering Faculty
Lead unit
School of Civil Engineering and Built Environment

Enhancing discrete choice models using insights from behavioural economics and psychology

Behavioural economics studies the impact of psychological factors on economic decisions and how these decisions deviate from those implied by classical economic theory. It merges the fields of economics and psychology to provide a better understanding of choice behaviour.When it comes to transportation individuals face long-term choices, such as car ownership and residential/work locations, and short-term choices, such as destination and departure time.Insights from behavioural economics can be applied to these choices to gain a better understanding of the conditions …

Study level
PhD, Master of Philosophy
Faculty
Science and Engineering Faculty
Lead unit
School of Civil Engineering and Built Environment

Use of depth sensing technology in radiotherapy and medical imaging

Consumer-grade depth sensing technology has in recent years become widely available. A number of vendors have developed similar technologies.Some examples of these technologies include:Microsoft Kinect™ (now discontinued)Intel’s RealSense™Asus Xtion depth sensorQualcomm Spectra ISP platform, now in its second generation.The systems make use of camera technology that measures the distance to a surface. Rapid image acquisition can then enable real time motion detection of location of the surface. The infra-red transmitter and sensor use a time-of-flight method to construct a depth …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Chemistry, Physics and Mechanical Engineering

Opportunities and challenges faced in intelligent transport systems

With the advancement in technology, new sources of transportation data, including traffic and transit data, have emerged which can potentially facilitate and even revolutionise transport modelling and simulation.My research team focuses on various aspects of the exploitation of emerging data for network planning, operations, management and control. This includes:new insights in travel behaviour modelling, traffic state estimation and predictiontransit network monitoring, modelling or controlapplying data from connected and autonomous vehicledata-driven operation of transportation systems with artificial intelligence and machine learning …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Civil Engineering and Built Environment

Robotic Process Automation: Research Opportunities

Recently, there has been a strong interest in industry in a specific area of automation Robotic Process Automation (RPA). This term can include robotics, software agents acting as human beings in system interactions, and process automation, workflow management systems or systems that are process-aware.RPA is a relatively new technology comprising of software agents called `bots' that mimic the manual path taken by a human through a range of computer applications when performing certain tasks in a business process. The tasks …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Information Systems

Responsible Analytics of Process Data

Technological advances in the field of data science empowers organisations to become ‘data-driven’ by applying new techniques to analyse large amounts of data. The potential benefits include a better understanding of business performance and more-informed decision making for business growth. However, a key roadblock to this vision is the lack of transparency surrounding the quality of data.Process mining is a specialised form of data-driven process analytics where process data, collated from the different IT systems typically available in organisations, is …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Information Systems

Privacy-Preserving Process Analytics

Modern organisations consider data to be their lifeblood. While the importance of data science and the potential benefits of data analytics are widely acknowledged, many people have grave concerns about irresponsible use of their data.Negative publicity surrounding large collections of personal data (incl. location, videos, pictures, emails, etc.) by corporations such as Google and Facebook and subsequent breaches have resulted in people losing trust in, and becoming more suspicious about, how their personal data is being used by such organisations.Process …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Information Systems

How to choose the right NoSQL database for your application?

Relational databases have consistently been the default choice for serious data storage. Relational databases provide many advantages, but are by no means perfect. They face issues with scalability, responsiveness and storage of different data types.On the contrary, with the rise of big data, the need to handle voluminous and heterogeneous data is becoming increasingly significant. NoSQL databases provide a platform to store and transact such data. They are open-source, schema-less, built for the 21st century data and run well on …

Study level
Vacation research experience scheme
Faculty
Science and Engineering Faculty
Lead unit
School of Information Systems

Data centre management and optimization for improved energy efficiency

Cloud data centres have been increasingly built to provide a wide range of data, network and cloud services. The increasing demand in various services requires more data centre resources and consequently more energy is consumed in data centres.It is estimated that about 30% of the running cost of a data centre is the energy consumption. Therefore, it is significant to manage and optimize data centre resources and energy consumption in data centres.

Study level
PhD
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Machine learning from big data for root cause analysis of power system faults

Power systems are fundamental infrastructure world-wide and their safe and reliable operations are critical. However, faults and failures are inevitable in power systems. Nevertheless, these should be avoided as much as possible.When a fault or failure occurs, the real-time supervisory control and data acquisition system (SCADA) usually presents this information as alarms or indications at the control centre. Quite often, the resulting alarm data are reviewed manually with the help of some automated system components to identify the contributing factors …

Study level
PhD
Faculty
Science and Engineering Faculty
Lead unit
School of Electrical Engineering and Computer Science

Improving process discovery

Nowadays, commercial and governmental organisations store lots of data related to their business processes. From such recorded data, process mining aims to gain insights in order for the process to be improved.A first step in typical process mining projects is to discover a process model automatically from the recorded event log. Leading process discovery techniques currently provide several guarantees, such as soundness of the model and a good trade-off between including and excluding behaviour of the log in/from the model.In …

Study level
Master of Philosophy, Honours
Faculty
Science and Engineering Faculty
Lead unit
School of Information Systems

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