Queensland University of Technology (QUT) is a university recognised for its excellence in teaching, real-world research and international scholarship. The PhD student experience is not limited to the classroom. Students undertaking research in the Transport focus area have the opportunity to be involved in real-world projects with industry practitioners, many of whom are members of the Smart Transport Research Centre.
 

Current PhD Students

Shuai Yang
A second stop line for better traffic management in Australia

Previous research has shown the start-up loss problem but more exploration is required into a potential solution. This research aims to demonstrate the hypothesis that using 'Second Stop Line' (SSL) to enlarge stopping distance could shorten the start-up loss time, and as a result, it could help improve the efficiency of queuing vehicles' departure at signalised intersection.

Rui Jiang
Strategies for rapid congestion recovery using ramp metering

Ramp metering is usually designed to delay the onset of motorway congestion. However, increasing traffic demand and field constraints, such as ramp queue limitation, makes congestion unavoidable. This research examines ramp metering from a different angle, using it to quickly recover a free flow state on the motorway as the demand decreases.

Kevah Bevrani
The development of a naturalistic car following model for assessing managed motorway systems

This research targets microscopic behavioural sub-models and it compares existing car following models against precise traffic measures such as headways and time to collision. It is anticipated that the major outcome of this research will be a more realistic car following model that will be effective in evaluation of managed motorway systems and particularly in traffic safety studies. Traffic safety indicators are going to be used for the final proposed model assessment.

Gongbin Qian
The harmonisation of eco-driving and intersection signals for enviromental-friendliness

Eco-driving is an innovative method of driving which has benefits in road safety, environmental impact, driver comfort and fuel savings. However, gentle driving behaviour may negatively affect non-eco drivers, which has the potential to worsen congestion and increase fuel consumption. This research investigates the payoff between mobility and sustainability at urban signalised intersections via analytical and simulation study. The expected contribution of this research is to answer the following questions: "How does eco-driving affect traffic flow" and "how to efficiently eco-drive" in an urban area.

Takahiro Tsubota
Traffic State Map based on Spatial-Temporal Relationship of Traffic Characteristics

This research aims to develop a traffic state map, which describes the traffic state for the entire urban network, including freeways and arterials. Instead of a conventional link-based analysis, an area-wide traffic state is investigated based on macroscopic traffic modelling techniques such as Macroscopic Fundamental Diagram (MFD) in order to explore the spatial-temporal traffic characteristics. The findings will provide a comprehensive understanding of congestion propagation, and is a novel method of monitoring the condition of network-wide traffic.

Ovitigalage Prasad Nalaka Perera
Environmental Adaptive and Cooperative Routing Protocol for Vehicular Ad-hoc Networks

This research aims to develop a cooperative and environmental adaptive routing protocol for vehicular ad-hoc networks. A cooperation method will be combined with a vehicular ad-hoc network routing protocol to enable more efficent and reliable routing. An environmental adaptive technique will be embedded into the same routing protocol using node cooperation as a metric. The protocol will be simulated using a realistic vehicle mobility model and a propagation model to obtain accurate results. It is expected that this routing protocol will support high service levels in infotainment and safety related applications for vehicular ad-hoc networks.

Le Minh Kieu
Short-term Bus Travel Time Prediction for Urban Networks

Bus travel time estimation could facilitate transit operators in offline management by optimising the transit schedule and understanding the reliablity of their systems. Bus travel time prediction, on the other hand, could be an important component of a real time traveller information system, and could also reduce anxiety and stress for travellers by helping them to select bus lines with minimum waiting time. This study is an effort to utilise the data of Brisbane's transit and traffic network in a bus travel time prediction model which considers the relationship between bus travel time and car travel time. The research goals are the comprehensive understandings on the bus operations and the relationship between bus and car travel time.

Rakkitha Widana Pathiranage
Comparison of Bus Rapid Transit (BRT) Operations between Local Route joins Corridor versus Local Route Interchange with Line Haul

The primary objective of this research is to study a line haul superbus system proposed for the study corridor, which uses 25m superbuses of nominal 200 passenger carrying capacity. This operational strategy would be intended to increase service capacity and reliablity. The approach includes investigating the feasibility of converting the existing busway operation to a line haul superbus system. The research will contribute to a better understanding of the impact of different operating strategies on BRT systems through performance measures including capacity and reliablity. This in turn will ultimately save time and expense for both passengers and transit agencies.

Jianyue Zhang
Communication Based Assistant System for Cooperative Merging on Urban Freeway

The aim of this research is to develop an available merging assistant to solve the problem of congestion caused by merging behaviour on an urban freeway. Merging management and a communication solution such as IEEE 802.11p AND IEEE 1609.3 are two parts that are included in this proposed system. Additionally, the research refers to a number of simulation tools, such as NS2, Matlab and Simulink. The results will provide a smooth merging process and a friendly driving environment during peak time on short-gap highway conditions.

Asso Hamzehei
Real-time Traffic Crash Propensity Analysis in Urban Motorways Using Data Mining Techniques

Much research has been conducted on traffic safety focusing on non-real-time crash prediction in the last decade. These studies applied aggregated data to analyse traffic risk indicators. However, due to the recent progress in IT and ITS, online traffic data is available and has made it possible to perform real-time proactive road safety studies. Although some research has been done in the scope of real-time traffic safety, it is still a fresh area of research. This study deals with crashes that have been caused mainly by hazardous traffic conditions. The study considers the variables between crash and traffic flow in developing the real-time crash estimation models. The research concentrates primarily on real-time crash propensity analysis in motorways using both descriptive and predictive techniques of data mining to maximise road safety.

Gabriel Michau
Dyanmic OD matrices estimation from Bluetooth data

Origin-destination matrices are a major input for describing the demand in a transport networks. Being the corner stone of traffic planning and management, their precise knowledge is a major challenge. The aim of this research is to give a comprehensive overview of the main issues that need to be accounted for, prior to estimating Origin-Destination matrices in urban road networks.

Furthermore, we will propose a methodology that can be followed, in order to cleanse, correct and aggregate Bluetooth data, thus facilitating the OD pattern analysis.

Ali Malekzadeh
Developing a Model for Estimating Qualitative and Quantitative Aspects of Elderly's Accessibility

Current Master Students

Amir Khoei
Exploiting Bluetooth to estimate urban travel time

This research focuses on the capturing of MAC address from Bluetooth devices as an accurate and cost effective monitoring system for traffic data collection, especially in travel time estimation. Furthermore, new methods will be investigated to improve the amount of accurate travel time data and decrease the error in collected data when compared to other sources of travel time data.

Syeed Anta Kashfi
Development of Enhanced VSL Deactivation Strategy

This research will develop a VSL deactivation scheme to improve the current practice of VSL operation. Essentially, the current VSL system induces an increase in travel time while providing safety benefits on the motorway. These operations decrease the network productivity and increase the travel time, mainly due to the delay in restoring the default speed limit in the traffic recovery phase. Therefore, this research will identify the possible solutions for reducing the negative impact of the current VSL system while maintaining its safety application.

Adama Lucky
Variable Speed Limit Speed Compliance and Flow Capacity Impact

Variable Speed Limit (VSL) is traditionally designed to improve safety, but recent research aims to employ VSL to increase throughput by optimising the use of available capacity. Such VSL implementations require high level of driver compliance to ensure VSL's optimum benefit is achieved. Recognising that high level of compliance is difficult to achieve in a real-life situation, this research focuses on analysing driver's reaction to VSL in order to improve VSL control strategy for future implementation.

Naeim Abedi
Improving the Performance of Wireless Device Scanning Systems for Traffic and Crowd Data Acquisition Purposes

Wireless Scanners such as Bluetooth and Wi-Fi detectors have become popular in the area of traffic data acquisition, particularly for the travel time estimation purposes. This research aims to improve the performance of wireless scanning devices in terms of detection rate and sensitivity. The effective strategies and parameters impacting on the performance of wireless scanning systems will be investigated and studied along this project. The outcomes will be helpful to increase the efficiency of the wireless data collection process.

Visiting Scholars

Jennifer Amourette

Visiting April 2013 - August 2013

Jennifer Amourette is a student from ENTPE (école Nationale des Travaux Publics de l'Etat), French Civil Engineering school. She completed her second year at ENTPE, equivalent to the first year of master. Her internship is to analyse travel time variability from Bluetooth sensor. She compares travel time from Bluetooth sensor with taxis GPS. The aim is to improve the accuracy of travel time prediction.

Nicolai Christian Idel

Visiting February 2013 - June 2013

Nicolai Christian Idel is a Danish student from the Department of Transport at DTU (Technical University of Denmark). He is currently in his 6th semester of his Bachelor Degree in Traffic and Transport Engineering. He is at QUT as an exchange student, taking three course-work units while also completing a project that is investigating rail freight in Australia. It has a particular focus on the supply chain and why rail freight is not as highly used in Australia relative to the European standard, and the service and human factor.

Hasti Tajtehranifard

Visited April 2012 - November 2012

Hasti received her B.S. in “Industrial Engineering with the specialization on Systems Analysis” from the ‘University of Tehran-Tehran, Iran’ and then attended a master program of “Transport Systems” at KTH (Royal Institute of Technology- Stockholm, Sweden). She is currently undertaking her master dissertation at STRC-QUT concentrating on ‘Intersections Performance Assessment Using the Bluetooth Data’.

Dr Yangbeibei Ji

Visited August 2012 - November 2012

Ji Yangbeibei did her PhD on “Traffic Incident Duration Time Prediction Method Research” at Tongji University in Shanghai. After receiving her PhD, JI Yangbeibei went to the University of Tokyo as a visiting scholar and later worked as post doctor at Delft University of Technology in the Netherlands. Now she is working at Shanghai Institute of Technology as associate professor. Her research interest includes:

(i) Investigation of Macroscopic Fundamental Diagram properties
(ii) Traffic incident duration time prediction and traffic incident management
(iii) Network evaluation and control
(iv) Traffic Information Management system
(v) Pedestrian flow research

Pierre-Antoine Laharotte

Visited April 2012 - August 2012

Pierre-Antoine is a french student from ENTPE (Ecole Nationale des Travaux Publics de l’Etat), french civil engineering school. He completed his second year within ENTPE, equivalent to the first year of master. Currently, he practices his background in transportation system within STRC assisting traffic engineer and focus on the evaluation of the travel time from BCC data and particularly on the link between probability of selecting a route and the evolution of the travel time.

Dr Qinghua Liu

Visited November 2011 - April 2012

Qinghua Liu is an Associate professor at Jiangsu University of Science and Technology, Zhenjiang, China, where he works as a teacher in the Computer Engineering Department, and previously as a teacher in the Automotive Engineering Department. He recently visited the centre as a research scholar in Intelligent Transportation, with a specialisation in traffic incident detection research fields. During his study here, he was instructed by Professor Edward Chung, and performed research on automatic incident detection methodology. He studied traffic flow from Tokyo Motorway loop data, and utilized a number of methodologies for data mining, including different denoise and prepocess methods as well as different wavelet decomposition methods.

Kugamoorthy Gajananan

Visited Febuary - March 2012

Kugamoorthy Gajananan (Gajan) is a PhD student at the National Institute of Informatics, Japan, where he works in the Global Lab, directed by Assoc.Prof. Helmut Prendinger. He carries out research in the areas of online multi-user 3D virtual worlds, human computer interaction. Currently,  he focus on building 3D virtual world based solutions to empower traffic engineers so that they can study human factor that influence driving behavior, against various transport scenarios. Specifically, he develops a novel framework for the automatic generation of complex traffic scenarios for the purpose of conducting driver behavioural studies in simulated environments such as an online multi-user 3D virtual world. For his research work, he has been closely collaborating with the traffic engineering experts from the Smart Transport Research Centre. He recently visited the centre to demonstrate his research work and assist traffic engineers to conduct a behavioural driver study to investigate a particular traffic phenomenon.

Please refer to QUT's website for more information regarding scholarships and prizes on offer.