Shortest path and vehicle trajectory aided map-matching for low frequency GPS data

Map-matching algorithms that utilise road segment connectivity along with other data (i.e.position, speed and heading) in the process of map-matching are normally suitable for high frequency (1 Hz or higher) positioning data from GPS. While applying such map-matching algorithms to low frequency data (such as data from a fleet of private cars, buses or light duty vehicles or smartphones), the performance of these algorithms reduces to in the region of 70% in terms of correct link identification, especially in urban and sub-urban road networks. This level of performance may be insufficient for some real-time Intelligent Transport System (ITS) applications and services such as estimating link travel time and speed from low frequency GPS data. Therefore, this paper develops a new weight-based shortest path and vehicle trajectory aided map-matching (stMM) algorithm that enhances the map-matching of low frequency positioning data on a road map. The well-known A* search algorithm is employed to derive the shortest path between two points while taking into account both link connectivity and turn restrictions at junctions. In the developed stMM algorithm, two additional weights related to the shortest path and vehicle trajectory are considered: one shortest path-based weight is related to the distance along the shortest path and the distance along the vehicle trajectory, while the other is associated with the heading difference of the vehicle trajectory. The developed stMM algorithm is tested using a series of real-world datasets of varying frequencies (i.e. 1 s, 5 s, 30 s, 60 s sampling intervals). A high-accuracy integrated navigation system (a high-grade inertial navigation system and a carrier-phase GPS receiver) is used to measure the accuracy of the developed algorithm. The results suggest that the algorithm identifies 98.9% of the links correctly for every 30 s GPS data. Omitting the information from the shortest path and vehicle trajectory, the accuracy of the algorithm reduces to about 73% in terms of correct link identification. The algorithm can process on average 50 positioning fixes per second making it suitable for real-time ITS applications and services.

Evaluating the level of stakeholder involvement during the project planning processes of building projects

The purpose of this study is to examine the current level of stakeholder involvement during the project's planning process. Stakeholders often provide the needed resources and have the ability to control the interaction and resource flows in the network. They also ultimately have strong impact on an organisation's survival, and therefore appropriate management and involvement of key stakeholders should be an important part of any project management plan. A series of literature reviews was conducted to identify and categorise significant phases involved in the planning. For data collection, a questionnaire survey was designed and distributed amongst nearly 200 companies who were involved in the residential building sector in Australia. Results of the analysis demonstrate the engagement levels of the four stakeholder groups involved in the planning process and establish a basis for further stakeholder involvement improvement.

The paradox of creative uncertainty in learning and teaching

In an ever-changing and globalised world there is a need for higher education to adapt and evolve its models of learning and teaching. The old industrial model has lost traction, and new patterns of creative engagement are required. These new models potentially increase relevancy and better equip students for the future. Although creativity is recognised as an attribute that can contribute much to the development of these pedagogies, and creativity is valued by universities as a graduate capability, some educators understandably struggle to translate this vision into practice. This paper reports on selected survey findings from a mixed methods research project which aimed to shed light on how creativity can be designed for in higher education learning and teaching settings. A social constructivist epistemology underpinned the research and data was gathered using survey and case study methods. Descriptive statistical methods and informed grounded theory were employed for the analysis reported here. The findings confirm that creativity is valued for its contribution to the development of students’ academic work, employment opportunities and life in general; however, tensions arise between individual educator’s creative pedagogical goals and the provision of institutional support for implementation of those objectives. Designing for creativity becomes, paradoxically, a matter of navigating and limiting complexity and uncertainty, while simultaneously designing for those same states or qualities.

A decision-analysis-based framework for analysing stakeholder behaviour in scenario planning

Scenario planning is a method widely used by strategic planners to address uncertainty about the future. However, current methods either fail to address the future behaviour and impact of stakeholders or they treat the role of stakeholders informally. We present a practical decision-analysis-based methodology for analysing stakeholder objectives and likely behaviour within contested unfolding futures. We address issues of power, interest, and commitment to achieve desired outcomes across a broad stakeholder constituency. Drawing on frameworks for corporate social responsibility (CSR), we provide an illustrative example of our approach to analyse a complex contested issue that crosses geographic, organisational and cultural boundaries. Whilst strategies can be developed by individual organisations that consider the interests of others – for example in consideration of an organisation's CSR agenda – we show that our augmentation of scenario method provides a further, nuanced, analysis of the power and objectives of all concerned stakeholders across a variety of unfolding futures. The resulting modelling framework is intended to yield insights and hence more informed decision making by individual stakeholders or regulators.

Preliminary work on the detection of partial discharges in SF6 under impulse voltages

This paper presents preliminary results of an investigation into the detection of partial discharges on the rise of impulse voltages from a point-to-plane gap in SF6. A parallel RC detection impedance is placed in the earth path of a point. Computer simulations are done to determine the values of R and C that will result in the smallest impulse voltage signal and the largest discharge signal across the detection impedance. These simulations and the experimental work show that the impulse voltage signal can not be sufficiently attenuated during the rise time of the applied voltage impulse using the RC detection impedance alone. An alternative discharge detection method is proposed in which a resonant partial discharge coupler is used. Elimination of noise and the impulse voltage signal can be achieved by shorting the coupler plate to the ground plane in the middle of the disk. However, due to the bandwidth of the measuring equipment and noise from the impulse generator it was not possible to detect discharges on the rising edge of a 1.5s voltage impulse using a coupler shorted in the middle. It was found that for this particular coupler, with no shorting points, and if the rising edge of the voltage impulse is longer than 5us, (10us) PD activity can be detected on the rising edge.

A 4D automatic simulation tool for construction resource planning: A case study

Purpose Traditional construction planning relies upon the critical path method (CPM) and bar charts. Both of these methods suffer from visualization and timing issues that could be addressed by 4D technology specifically geared to meet the needs of the construction industry. This paper proposed a new construction planning approach based on simulation by using a game engine. Design/methodology/approach A 4D automatic simulation tool was developed and a case study was carried out. The proposed tool was used to simulate and optimize the plans for the installation of a temporary platform for piling in a civil construction project in Hong Kong. The tool simulated the result of the construction process with three variables: 1) equipment, 2) site layout and 3) schedule. Through this, the construction team was able to repeatedly simulate a range of options. Findings The results indicate that the proposed approach can provide a user-friendly 4D simulation platform for the construction industry. The simulation can also identify the solution being sought by the construction team. The paper also identifies directions for further development of the 4D technology as an aid in construction planning and decision-making. Research limitations/implications The tests on the tool are limited to a single case study and further research is needed to test the use of game engines for construction planning in different construction projects to verify its effectiveness. Future research could also explore the use of alternative game engines and compare their performance and results. Originality/value The authors proposed the use of game engine to simulate the construction process based on resources, working space and construction schedule. The developed tool can be used by end-users without simulation experience.

The path towards greening the Malaysian construction industry

Construction industry contributes significantly to environmental degradation, and governments in many countries which are endeavouring to address the situation. Malaysia is no exception. This paper examines the path towards green construction project delivery in Malaysia, focusing on current green policies and initiatives by governments. The historical waves in Malaysian approaches to tackling environmental issues are described, starting from the early 20th century, through the 1990s to the present, and the influence of these approaches on construction practices is analysed. Based on the findings of policy review, essential green construction practices aimed at mitigating the adverse effects of construction activities on the environment in Malaysia were identified. This paper paves the way for future studies in construction and sustainability in Malaysia, especially for the Southeast Asian region where sustainability practices are urgently needed.

Methods for constructing uncertainty intervals for queries of Bayesian nets

In this paper the issue of finding uncertainty intervals for queries in a Bayesian Network is reconsidered. The investigation focuses on Bayesian Nets with discrete nodes and finite populations. An earlier asymptotic approach is compared with a simulation-based approach, together with further alternatives, one based on a single sample of the Bayesian Net of a particular finite population size, and another which uses expected population sizes together with exact probabilities. We conclude that a query of a Bayesian Net should be expressed as a probability embedded in an uncertainty interval. Based on an investigation of two Bayesian Net structures, the preferred method is the simulation method. However, both the single sample method and the expected sample size methods may be useful and are simpler to compute. Any method at all is more useful than none, when assessing a Bayesian Net under development, or when drawing conclusions from an ‘expert’ system.

Path algebra for mobile robots

In this paper, we introduce a path algebra well suited for navigation in environments that can be abstracted as topological graphs. From this path algebra, we derive algorithms to reduce routes in such environments. The routes are reduced in the sense that they are shorter (contain fewer edges), but still connect the endpoints of the initial routes. Contrary to planning methods descended from Disjktra’s Shortest Path Algorithm like D , the navigation methods derived from our path algebra do not require any graph representation. We prove that the reduced routes are optimal when the graphs are without cycles. In the case of graphs with cycles, we prove that whatever the length of the initial route, the length of the reduced route is bounded by a constant that only depends on the structure of the environment.

An automated emergency landing system for fixed-wing aircraft: Planning and control

A number of hurdles must be overcome in order to integrate unmanned aircraft into civilian airspace for routine operations. The ability of the aircraft to land safely in an emergency is essential to reduce the risk to people, infrastructure and aircraft. To date, few field-demonstrated systems have been presented that show online re-planning and repeatability from failure to touchdown. This paper presents the development of the Guidance, Navigation and Control (GNC) component of an Automated Emergency Landing System (AELS) intended to address this gap, suited to a variety of fixed-wing aircraft. Field-tested on both a fixed-wing UAV and Cessna 172R during repeated emergency landing experiments, a trochoid-based path planner computes feasible trajectories and a simplified control system executes the required manoeuvres to guide the aircraft towards touchdown on a predefined landing site. This is achieved in zero-thrust conditions with engine forced to idle to simulate failure. During an autonomous landing, the controller uses airspeed, inertial and GPS data to track motion and maintains essential flight parameters to guarantee flyability, while the planner monitors glide ratio and re-plans to ensure approach at correct altitude. Simulations show reliability of the system in a variety of wind conditions and its repeated ability to land within the boundary of a predefined landing site. Results from field-tests for the two aircraft demonstrate the effectiveness of the proposed GNC system in live operation. Results show that the system is capable of guiding the aircraft to close proximity of a predefined keyhole in nearly 100% of cases.

Governance and regional planning outcomes: Using governance indicators to support a policy implementation approach

Regional planning faces numerous decision making uncertainties related to the complex interdependencies between urban and regional centres. Questions about how to achieve sustainable planning solutions across regions are a key uncertainty and relate to a lack of information about the actual achievement of outcomes as proposed by the objectives of a plan. Regional plan implementation and its impact on environmental, social and economic outcomes have been little explored within Australian urban and regional planning research. Despite a desire to improve the conditions across Australian regions, ambiguity persists regarding the results of regional planning efforts. Of the variables affecting regional planning, scholars argue that governance has a significant impact on achieving outcomes (see Pahl-Wostl 2009). In order to better analyse the impact of governance, we propose a set of governance indicators to examine decisions across regional planning institutions and apply this to governance models across Queensland’s regions. We contend that these governance indicators can support a more rigorous assessment of the impacts of governance models on plan implementation and outcomes. We propose that this is a way to better understand the relationship between planning and outcomes across urban and regional areas.

Acute myocardial infarction: The spouse's experience

Given the marked changes in length of hospital stay and the number of CAB procedures being performed, it is essential that health professionals are aware of the potential impact these changes could have on the spouses of patients who have undergone CAB surgery. Results from numerous quantitative studies suggest that spouses of patients undergoing CAB surgery experience both physical and emotional stress before and after their partners surgery. While such studies have contributed to our understanding, they fail to capture the qualitative experience of what it is like to be a spouse of a partner who has undergone CAB surgery, specifically in the context of changes in the length of hospital stay. The objective of this study was to describe the experience of spouses of patients who had recently undergone CAB surgery. This study utilised a qualitative methodology and was guided by Husserl's phenomenological approach. Data was obtained from four participants by in depth open ended interviews. This study has implications for all health professionals involved in the care of patients and their families undergoing CAB surgery. If health professionals are to provide holistic care, they need to understand more fully the qualitative experience of spouses of critically ill patients. The purpose of this study was to describe the experience of spouses whose partner's had suffered an acute myocardial infarction (MI). The study was guided by a phenomenological approach. This qualitative type of study is new to nursing inquiry, therefore this investigation creates links with understanding the notion of psychosocial nursing processes with the leading cause of death in Australia. Literature concerning the spouses of myocardial infarction patients has predominantly employed quantitative methods, as such results have centred on structured data collection, and categorised outcomes. Such methods have failed to capture the insight of what it is like to be a spouse of a patient who has had an MI. In-depth interviews were conducted with three participants (2 females and 1 male) about their experiences. The major findings of the study were categorised under the headings of uncertainty, emotional turmoil, support information and lifestyle change. Conclusions suggest that spouses are neglected by health professionals and they require as much psychosocial support as their partner in terms of cardiac discharge planning. Spouses need to be granted special consideration, as they progress through a grieving and readjustment process in coming to terms with: (1) the need to support and care for their partner, (2) changes in their roles and (3) adjustments to their current lifestyles.

A Jacobian-Based Algorithm for Planning Attitude Maneuvers Using Forward and Reverse Rotations

Algorithms for planning quasistatic attitude maneuvers based on the Jacobian of the forward kinematic mapping of fully-reversed (FR) sequences of rotations are proposed in this paper. An FR sequence of rotations is a series of finite rotations that consists of initial rotations about the axes of a body-fixed coordinate frame and subsequent rotations that undo these initial rotations. Unlike the Jacobian of conventional systems such as a robot manipulator, the Jacobian of the system manipulated through FR rotations is a null matrix at the identity, which leads to a total breakdown of the traditional Jacobian formulation. Therefore, the Jacobian algorithm is reformulated and implemented so as to synthesize an FR sequence for a desired rotational displacement. The Jacobian-based algorithm presented in this paper identifies particular six-rotation FR sequences that synthesize desired orientations. We developed the single-step and the multiple-step Jacobian methods to accomplish a given task using six-rotation FR sequences. The single-step Jacobian method identifies a specific FR sequence for a given desired orientation and the multiple-step Jacobian algorithm synthesizes physically feasible FR rotations on an optimal path. A comparison with existing algorithms verifies the fast convergence ability of the Jacobian-based algorithm. Unlike closed-form solutions to the inverse kinematics problem, the Jacobian-based algorithm determines the most efficient FR sequence that yields a desired rotational displacement through a simple and inexpensive numerical calculation. The procedure presented here is useful for those motion planning problems wherein the Jacobian is singular or null.

A hierarchical system of learning automata that can learn die globally optimal path

Systems of learning automata have been studied by various researchers to evolve useful strategies for decision making under uncertainity. Considered in this paper are a class of hierarchical systems of learning automata where the system gets responses from its environment at each level of the hierarchy. A classification of such sequential learning tasks based on the complexity of the learning problem is presented. It is shown that none of the existing algorithms can perform in the most general type of hierarchical problem. An algorithm for learning the globally optimal path in this general setting is presented, and its convergence is established. This algorithm needs information transfer from the lower levels to the higher levels. Using the methodology of estimator algorithms, this model can be generalized to accommodate other kinds of hierarchical learning tasks.

A lesson from cyclone Larry: An untold story of the success of good coastal planning

When tropical cyclone Larry crossed the Queensland coast on 20 March 2006, commercial, recreational and naval vessels in the port of Cairns, 60 km north of the eye of the cyclone and others closer to the eye, were protected from the destructive winds by sheltering in deep mangrove creeks in Trinity Inlet and off other coastal rivers. The Trinity Inlet mangroves are protected under the comprehensive multi-use Trinity Inlet Management Plan, agreed by the local and state government agencies (Cairns City Council, the Cairns Port Authority and the Queensland Government). Using this Australian example and one from the town of Palompon in Leyte province, central Philippines, we show how long-term mangrove habitat protection resulting from well-conceived coastal planning can deliver important economic and infrastructure benefits.