Arterial travel time estimation & prediction : a literature review

This report is the fourth deliverable of the Real Time and Predictive Traveller Information project and the first deliverable of the Arterial Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Arterial Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for arterial traffic. The objective of this report is to review the literature pertaining to travel time estimation and prediction models for arterial traffic.

Fundamental understanding on the use of Bluetooth MAC scanner for arterial travel time estimation

This report is the eight deliverable of the Real Time and Predictive Traveller Information project and the third deliverable of the Arterial Travel Time Information sub-project in the Integrated Traveller Information research Domain of the Smart Transport Research Centre. The primary objective of the Arterial Travel Time Information sub-project is to develop algorithms for real-time travel time estimation and prediction models for arterial traffic. Brisbane arterial network is highly equipped with Bluetooth MAC Scanners, which can provide travel time information. Literature is limited with the knowledge on the Bluetooth protocol based data acquisition process and accuracy and reliability of the analysis performed using the data. This report expands the body of knowledge surrounding the use of data from Bluetooth MAC Scanner (BMS) as a complementary traffic data source. A multi layer simulation model named Traffic and Communication Simulation (TCS) is developed. TCS is utilised to model the theoretical properties of the BMS data and analyse the accuracy and reliability of travel time estimation using the BMS data.

Evaluation of strain energy based damage indices for flexural crack detection of RC beams

Vibration Based Damage Identification Techniques which use modal data or their functions, have received significant research interest in recent years due to their ability to detect damage in structures and hence contribute towards the safety of the structures. In this context, Strain Energy Based Damage Indices (SEDIs), based on modal strain energy, have been successful in localising damage in structuers made of homogeneous materials such as steel. However, their application to reinforced concrete (RC) structures needs further investigation due to the significant difference in the prominent damage type, the flexural crack. The work reported in this paper is an integral part of a comprehensive research program to develop and apply effective strain energy based damage indices to assess damage in reinforced concrete flexural members. This research program established (i) a suitable flexural crack simulation technique, (ii) four improved SEDI's and (iii) programmable sequentional steps to minimise effects of noise. This paper evaluates and ranks the four newly developed SEDIs and existing seven SEDIs for their ability to detect and localise flexural cracks in RC beams. Based on the results of the evaluations, it recommends the SEDIs for use with single and multiple vibration modes.

Application of multi-criteria decision making methods to compression ignition engine efficiency and gaseous, particulate and greenhouse gas emissions

Compression ignition (CI) engine design is subject to many constraints which presents a multi-criteria optimisation problem that the engine researcher must solve. In particular, the modern CI engine must not only be efficient, but must also deliver low gaseous, particulate and life cycle greenhouse gas emissions so that its impact on urban air quality, human health, and global warming are minimised. Consequently, this study undertakes a multi-criteria analysis which seeks to identify alternative fuels, injection technologies and combustion strategies that could potentially satisfy these CI engine design constraints. Three datasets are analysed with the Preference Ranking Organization Method for Enrichment Evaluations and Geometrical Analysis for Interactive Aid (PROMETHEE-GAIA) algorithm to explore the impact of 1): an ethanol fumigation system, 2): alternative fuels (20 % biodiesel and synthetic diesel) and alternative injection technologies (mechanical direct injection and common rail injection), and 3): various biodiesel fuels made from 3 feedstocks (i.e. soy, tallow, and canola) tested at several blend percentages (20-100 %) on the resulting emissions and efficiency profile of the various test engines. The results show that moderate ethanol substitutions (~20 % by energy) at moderate load, high percentage soy blends (60-100 %), and alternative fuels (biodiesel and synthetic diesel) provide an efficiency and emissions profile that yields the most “preferred” solutions to this multi-criteria engine design problem. Further research is, however, required to reduce Reactive Oxygen Species (ROS) emissions with alternative fuels, and to deliver technologies that do not significantly reduce the median diameter of particle emissions.

Work integrated research higher degree studies : experiences, benefits, barriers and coping strategies

Attributed to the changing social, political and economic landscape of the ‘knowledge economy’, Australian universities are under pressure to produce researchers that have a variety of skills which meet the demands of an increasingly diverse job market. As a consequence, the Australian PhD now includes a range of doctoral degrees. This paper reports on the experiences of two PhD students engaged in an informally managed research higher degree program described in this paper as a Work Integrated Research Higher Degree (WIRHD). Their learning process shares the attributes from both the traditional PhD program and professional doctorates. However, because of the blended nature of the learning contexts, what students need to manage within the WIRHD is much more complicated than the established RHD programs. An exploratory case study approach exploring experiences, benefits, barriers and coping strategies was conducted with the view to develop a preliminary integrative framework that attempts to explain the various contexts that influence the learning experience of WIRHD candidates. The paper concludes with some recommended strategies for helping WIRHD candidates to manage the challenges associated with their learning process.

Stress distribution of CFRP strengthened steel hollow sections under tension

Carbon fibre reinforced polymer (CFRP) sheets have many outstanding properties such as high strength, high elastic modulus, light weight and good durability which are made them a suitable alternative for steel in strengthening work. This paper describe the ultimate load carrying capacity of steel hollow sections at effective bond length in terms of its cross sectional area and the stress distribution within bond region for different layers CFRP. It was found that depending on their size and orientation of uni- directional CFRP layers, the ultimate tensile load was different. Along with these tests, non linear finite element analysis was also performed to validate the ultimate load carrying capacity depending on their cross sections. The predicted ultimate loads from FE analysis are found very close to the laboratory test results. The validated model has been used to determine the stress distribution at bond joint for different orientation of CFRP. This research shows the effect of stress distribution and suitable wrapping layer to be used for the strengthening of steel hollow sections in tension.

Assessment of the application of contingent valuation theory to bio-sequestered carbon

The issue of carbon sequestration rights has become topical following the United Nations Convention on Climate Change (United Nations 1992 at page 1414) and the subsequent Kyoto Protocol (United Nations Climate Change Secretariat 1998) which identified emissions trading as one of the mechanisms to reduce greenhouse gas emissions. Australian states have responded by creating a legal framework for the recognition of rights to bio-sequestered carbon. There is a lack of uniformity in the approach of each state to the recognition of these rights, which vary from the creation of new and novel interests in land to the adoption of more traditional rights such as a profit a prendre. Rights to bio-sequestered carbon are likely to have an impact on the utility, marketability, value and financing of rural land holdings. Despite the creation of the legal framework for recognition of rights to sequestrated carbon, there has been a delay in the introduction of a formalised carbon trading scheme in Australia. In the absence of an established carbon market, this paper addresses the applicability of contingent valuation theory to assess the value of bio-sequestered carbon rights to a rural land holder. Limitations and potential controversies associated with this application of contingent valuation theory are also addressed in this paper.

Empirical approach to understand the knowledge management process

Knowledge Management (KM) is a process that focuses on knowledge-related activities to facilitate knowledge creation, capture, transformation and use, with the ultimate aim of leveraging organisations’ intellectual capital to achieve organisational objectives. The KM process receives input from its context (e.g. internal business environment), and produces output (i.e. knowledge). It is argued that the validity of such knowledge should be justified by business performance. The study, this paper reports on, provides enhanced empirical understanding of such an input-process-output relationship through investigating the interactions among different KM activities in the context of how construction organisations in Hong Kong manage knowledge. To this end, a theoretical framework along with a number of hypotheses are proposed and empirically tested through correlation, regression and path analyses. A questionnaire survey was administered to a sample of construction contractors operating in Hong Kong to facilitate testing the proposed relationships. More than 140 respondents from 99 organisations responded to the survey. The study findings demonstrate that both organisational and technical environments have the potential to predict the intensity of KM activities. Furthermore, different categories of KM activities interact with each other, and collectively they could be used to predict business performance.

Impact of organisational cultural factors on knowledge management in construction

Knowledge Management (KM) is a process that focuses on knowledge-related activities to facilitate knowledge creation, capture, transformation and use, with the ultimate aim of leveraging organisations’ intellectual capital to achieve organisational objectives. Organisational culture and climate have been identified as major catalysts to knowledge creation and sharing, and hence are considered important dimensions of KM research. The fragmented and hierarchical nature of the construction industry illustrates its difficulties to operate in a co-ordinated and homogeneous way when dealing with knowledge-related issues such as research and development, training and innovation. The culture and climate of organisations operating within the construction industry are profoundly shaped by the long-established characteristics of the industry, whilst also being influenced by the changes within the sector. Meanwhile, the special project-based structure of construction organisations constitutes additional challenges in facing knowledge production. The study this paper reports on addresses the impact of organisational culture and climate on the intensity of KM activities within construction organisations, with specific focus on the managerial activities that help to manage these challenges and to facilitate KM. A series of semi-structured interviews were undertaken to investigate the KM activities of the contractors operating in Hong Kong. The analysis on the qualitative data revealed that leadership on KM, innovation management, communication management and IT development were key factors that impact positively on the KM activities within the organisations under investigation.

China's foreign economic cooperation development : exporting Chinese construction services

Since the movement for economic reform started in China 20 years ago, the nation's GDP had grown on average from seven to nine per cent a year, making China's construction industry one of the largest in the world. This paper presents an overview of China's foreign economic cooperation development (FECD) in the context of exporting three major construction services namely; contracting, labour and design. The paper outlines the export market profile of Chinese contractors and discusses their current position in the international market. It then addresses challenges; they are facing in view of meeting the ambitious strategic targets set out by the Government for the FECD, which cover the export of construction services. Finally, the paper sheds some light on key exporting strategies currently adopted by Chinese contractors.

Adaptive metering algorithm for electronic commercial vehicle preclearance systems

This paper presents an adaptive metering algorithm for enhancing the electronic screening (e-screening) operation at truck weight stations. This algorithm uses a feedback control mechanism to control the level of truck vehicles entering the weight station. The basic operation of the algorithm allows more trucks to be inspected when the weight station is underutilized by adjusting the weight threshold lower. Alternatively, the algorithm restricts the number of trucks to inspect when the station is overutilized to prevent queue spillover. The proposed control concept is demonstrated and evaluated in a simulation environment. The simulation results demonstrate the considerable benefits of the proposed algorithm in improving overweight enforcement with minimal negative impacts on nonoverweighed trucks. The test results also reveal that the effectiveness of the algorithm improves with higher truck participation rates in the e-screening program.

Algorithm for queue estimation with loop detector of time occupancy in off-ramps on signalized motorways

Long traffic queues on off-ramps significantly compromise the safety and throughput of motorways. Obtaining accurate queue information is crucial for countermeasure strategies. However, it is challenging to estimate traffic queues with locally installed inductive loop detectors. This paper deals with the problem of queue estimation with the interpretation of queuing dynamics and the corresponding time-occupancy distribution over motorway off-ramps. A novel algorithm for real-time queue estimation with two detectors is presented and discussed. Results derived from microscopic traffic simulation validated the effectiveness of the algorithm and revealed some of its useful features: (a) long and intermediate traffic queues could be accurately measured, (b) relatively simple detector input (i.e., time occupancy) was required, and (c) the estimation philosophy was independent with signal timing changes and provided the potential to cooperate with advanced strategies for signal control. Some issues concerning field implementation are also discussed.

Traffic queue estimation for metered motorway on-ramps through use of loop detector time occupancies

The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is a vital input for dynamic queue management on metered on-ramps. Accurate and reliable queue information enables the management of on-ramp queue in an adaptive manner to the actual traffic queue size and thus minimises the adverse impacts of queue flush while increasing the benefit of ramp metering. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.

Optimized strategy for integrated traffic and transit signal control

This paper proposes a unique and innovative approach to integrate transit signal priority control into a traffic adaptive signal control strategy. The proposed strategy was named OSTRAC (Optimized Strategy for integrated TRAffic and TRAnsit signal Control). The cornerstones of OSTRAC include an online microscopic traffic f low prediction model and a Genetic Algorithm (GA) based traffic signal timing module. A sensitivity analysis was conducted to determine the critical GA parameters. The developed traffic f low model demonstrated reliable prediction results through a test. OSTRAC was evaluated by comparing its performance to three other signal control strategies. The evaluation results revealed that OSTRAC efficiently and effectively reduced delay time of general traffic and also transit vehicles.

A Kalman filter based queue estimation algorithm using time occupancies for motorway on-ramps

The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is the most vital input for a dynamic queue management that can treat long queues on metered on-ramps more sophistically. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in the congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.