Data requirements and graph data structures for a multi-modal, multi-objective trip planner

Traffic congestion has a significant impact on the economy and environment. Encouraging the use of multimodal transport (public transport, bicycle, park’n’ride, etc.) has been identified by traffic operators as a good strategy to tackle congestion issues and its detrimental environmental impacts. A multi-modal and multi-objective trip planner provides users with various multi-modal options optimised on objectives that they prefer (cheapest, fastest, safest, etc) and has a potential to reduce congestion on both a temporal and spatial scale. The computation of multi-modal and multi-objective trips is a complicated mathematical problem, as it must integrate and utilize a diverse range of large data sets, including both road network information and public transport schedules, as well as optimising for a number of competing objectives, where fully optimising for one objective, such as travel time, can adversely affect other objectives, such as cost. The relationship between these objectives can also be quite subjective, as their priorities will vary from user to user. This paper will first outline the various data requirements and formats that are needed for the multi-modal multi-objective trip planner to operate, including static information about the physical infrastructure within Brisbane as well as real-time and historical data to predict traffic flow on the road network and the status of public transport. It will then present information on the graph data structures representing the road and public transport networks within Brisbane that are used in the trip planner to calculate optimal routes. This will allow for an investigation into the various shortest path algorithms that have been researched over the last few decades, and provide a foundation for the construction of the Multi-modal Multi-objective Trip Planner by the development of innovative new algorithms that can operate the large diverse data sets and competing objectives.

Investigation into the noise map based on traffic flow prediction in the citywide road network

As one of the measures for decreasing road traffic noise in a city, the control of the traffic flow and the physical distribution is considered. To conduct the measure effectively, the model for predicting the traffic flow in the citywide road network is necessary. In this study, the existing model named AVENUE was used as a traffic flow prediction model. The traffic flow model was integrated with the road vehicles' sound power model and the sound propagation model, and the new road traffic noise prediction model was established. As a case study, the prediction model was applied to the road network of Tsukuba city in Japan and the noise map of the city was made. To examine the calculation accuracy of the noise map, the calculated values of the noise at the main roads were compared with the measured values. As a result, it was found that there was a possibility that the high accuracy noise map of the city could be made by using the noise prediction model developed in this study.

Information provision and network performance represented by Macroscopic Fundamental Diagram

The existence of the Macroscopic Fundamental Diagram (MFD), which relates network space-mean density and flow, has been shown in urban networks under homogeneous traffic conditions. Since the MFD represents the area-wide network traffic performances, studies on perimeter control strategies and an area traffic state estimation utilizing the MFD concept has been reported. The key requirements for the well-defined MFD is the homogeneity of the area wide traffic condition, which is not universally expected in real world. For the practical application of the MFD concept, several researchers have identified the influencing factors for network homogeneity. However, they did not explicitly take drivers’ behaviour under real time information provision into account, which has a significant impact on the shape of the MFD. This research aims to demonstrate the impact of drivers’ route choice behaviour on network performance by employing the MFD as a measurement. A microscopic simulation is chosen as an experimental platform. By changing the ratio of en-route informed drivers and pre-trip informed drivers as well as by taking different route choice parameters, various scenarios are simulated in order to investigate how drivers’ adaptation to the traffic congestion influences the network performance and the MFD shape. This study confirmed and addressed the impact of information provision on the MFD shape and highlighted the significance of the route choice parameter setting as an influencing factor in the MFD analysis.

New Perspectives On Firm Growth

This insightful volume presents a collection of innovative works by two of the leading researchers of firm growth: Per Davidsson, Director, Australian Centre for Entrepreneurship Research and Professor of Entrepreneurship, Queensland University of Technology, Australia and Jönköping International Business School, Sweden and Johan Wiklund, Professor of Entrepreneurship, Syracuse University, US and Jönköping International Business School, Sweden. The studies extend previous research by providing stronger theoretical underpinnings and using longitudinal databases that can separate in time the firms’ growth from its presumed causes. They also break new ground by examining different modes of growth, such as sales growth vs. employment growth, and organic growth vs. acquisition-based expansion. Further, the studies investigate the drivers of firm growth and take a critical look at the effects, such as under what circumstances high growth is associated with high profitability. The issue of how firm growth is achieved and managed, and what consequences it has for different stakeholders is both theoretically interesting and practically important. The book will strongly appeal to academics of entrepreneurship, small business management and strategy.

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.

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.

Using variable speed limits for motorway off-ramp queue protection

Motorway off-ramps are a significant source of traffic congestion and collisions. Heavy diverging traffic to off-ramps slows down the mainline traffic speed. When the off-ramp queue spillbacks onto the mainline, it leads to a major breakdown of the motorway capacity and a significant threat to the traffic safety. This paper proposes using Variable Speed Limits (VSL) for protection of the motorway off-ramp queue and thus to promote safety in congested diverging areas. To support timely activation of VSL in advance of queue spillover, a proactive control strategy is proposed based on a real-time off-ramp queue estimation and prediction. This process determines the estimated queue size in the near-term future, on which the decision to change speed limits is made. VSL can effectively slow down traffic as it is mandatory that drivers follow the changed speed limits. A collateral benefit of VSL is its potential effect on drivers making them more attentive to the surrounding traffic conditions, and prepared for a sudden braking of the leading car. This paper analyses and quantifies these impacts and potential benefits of VSL on traffic safety and efficiency using the microsimulation approach.

Handbook on the Knowledge Economy : Volume Two

The second volume of the Handbook on the Knowledge Economy is a worthy companion to the highly successful original volume published in 2005, extending its theoretical depth and developing its coverage. Together the two volumes provide the single best work and reference point for knowledge economy studies. The second volume with fifteen original essays by renowned scholars in the field, provides insightful and robust analyses of the development potential of the knowledge economy in all its aspects, forms and manifestations.

Who's asking for what? Fundraising and leadership in Australian nonprofits

The nonprofit funding landscape is in flux. Many organisations are having to think differently and develop fresh skills either to enter the fundraising market or to cope better with rising competition for community and corporate support. This new reality affects boards, CEOs and fundraisers alike. Against this backdrop, our exploratory study aimed to build an evidence base and spark more discussion about: - the role Australian nonprofit CEOs and boards play in supporting fundraising/development; - current engagement levels; and - perceptions of leadership in fundraising from two possibly contrasting perspectives: NP leaders (board members and CEOs); and fundraisers. This research has been supported by the Perpetual Foundation, the EF and SL Gluyas Trust and the Edward Corbould Charitable Trust under the management of Perpetual Trustee Company Ltd.

Triple Helix: Film Noir, Neo Noir and Los Angeles – imagining history and remembering the future in the most contemporary city

Modern and Postmodern Los Angeles is examined through the lens of film noir and neo noir. The unique relationship between the city of Los Angeles and cinema is discussed in terms of a historiography emphasizing the role played by these defining film styles and genres. The research draws and extends on the work conducted by Edward Dimendberg, Paula Rabinowitz and Mike Davis, and urban theory approaches associated with the Los Angeles School of Urbanism.

Brave new green world : consequences of a carbon economy for the conservation of Australian biodiversity

Pricing greenhouse gas emissions is a burgeoning and possibly lucrative financial means for climate change mitigation. Emissions pricing is being used to fund emissions-abatement technologies and to modify land management to improve carbon sequestration and retention. Here we discuss the principal land-management options under existing and realistic future emissions-price legislation in Australia, and examine them with respect to their anticipated direct and indirect effects on biodiversity. The main ways in which emissions price-driven changes to land management can affect biodiversity are through policies and practices for (1) environmental plantings for carbon sequestration, (2) native regrowth, (3) fire management, (4) forestry, (5) agricultural practices (including cropping and grazing), and (6) feral animal control. While most land-management options available to reduce net greenhouse gas emissions offer clear advantages to increase the viability of native biodiversity, we describe several caveats regarding potentially negative outcomes, and outline components that need to be considered if biodiversity is also to benefit from the new carbon economy. Carbon plantings will only have real biodiversity value if they comprise appropriate native tree species and provide suitable habitats and resources for valued fauna. Such plantings also risk severely altering local hydrology and reducing water availability. Management of regrowth post-agricultural abandonment requires setting appropriate baselines and allowing for thinning in certain circumstances, and improvements to forestry rotation lengths would likely increase carbon-retention capacity and biodiversity value. Prescribed burning to reduce the frequency of high-intensity wildfires in northern Australia is being used as a tool to increase carbon retention. Fire management in southern Australia is not readily amenable for maximising carbon storage potential, but will become increasingly important for biodiversity conservation as the climate warms. Carbon price-based modifications to agriculture that would benefit biodiversity include reductions in tillage frequency and livestock densities, reductions in fertiliser use, and retention and regeneration of native shrubs; however, anticipated shifts to exotic perennial grass species such as buffel grass and kikuyu could have net negative implications for native biodiversity. Finally, it is unlikely that major reductions in greenhouse gas emissions arising from feral animal control are possible, even though reduced densities of feral herbivores will benefit Australian biodiversity greatly.

Algebraic analysis of Trivium-like ciphers

Trivium is a bit-based stream cipher in the final portfolio of the eSTREAM project. In this paper, we apply the approach of Berbain et al. to Trivium-like ciphers and perform new algebraic analyses on them, namely Trivium and its reduced versions: Trivium-N, Bivium-A and Bivium-B. In doing so, we answer an open question in the literature. We demonstrate a new algebraic attack on Bivium-A. This attack requires less time and memory than previous techniques which use the F4 algorithm to recover Bivium-A's initial state. Though our attacks on Bivium-B, Trivium and Trivium-N are worse than exhaustive keysearch, the systems of equations which are constructed are smaller and less complex compared to previous algebraic analysis. Factors which can affect the complexity of our attack on Trivium-like ciphers are discussed in detail.

Introduction

The issue of firm growth - how it is achieved and managed, and what consequences it has for different stakeholders - is both theoretically interesting and practically important. It is also an area of scholarly enquiry that has expanded very significantly since we started doing research on it in the 1980s and 1990s. In this volume we present and comment upon the most recent contributions we have made to this field of inquiry - separately, jointly and with various colleagues (who are included in the 'we/us article authors' used in the remainder of this introduction). While the chapters have been published before in various places, we think it valuable to gather them in one easily accessible place, which also allows space for our reflective commentary across the individual chapters. We hope readers will find the work a useful and worthwhile addition to the extant body of knowledge about firm growth. We also hope they will find that it- as its title suggests- brings new•/ perspectives on firm growth and its study, and that it can inspire future contributions by other researchers. This is important, because despite the growing volume of research on firm growth, many important questions still lack satisfactory answers. The current volume may be regarded as a follow-up of a previous collection where we- and Frederic Delmar- presented and commented on eight articles on (mostly small) firm growth that we had jointly or separately published up until that time (Davidsson et al., 2006). In that volume we organised the works under three broad themes: the conceptual and empirical complexity of the firm growth phenomenon; growth aspirations and motivations; and patterns and determinants of actual growth The current volume builds on and extends these themes. Only one of the chapters in the previous volume directly addressed the issue of drivers of actual growth. We add three more in this book, two of which expand on the (aspirations and motivations' theme by relating growth aspirations and motivations (or lack thereof) of the owner-manager to the actual growth achieved in the subsequent period.

Asset specificity and behavioral uncertainty as moderators of the sales growth-employment growth relationship in emerging ventures

New venture growth is a central topic in entrepreneurship research. Although sales growth is emerging as the most commonly used measure of growth for emerging ventures, employment growth has also been used frequently. However, empirical research demonstrates that there are only very low to moderately sized correlations between the two (Delmar et aL, 2003; Weinzimmer, et al., 1998). In addition) sales growth and employment growth respond differently to a wide variety of criteria (Baum et al., 2001; Delmar et al., 2003). In this study we use transaction cost economics (Williamson, 1996) as a theoretical base to examine transaction cost influences on the addition of new employees as emerging ventures experience sales growth. \\le theorize that transaction cost economics variables will moderate the relationship between sales growth and employment growth. W'e develop and test hypotheses related to asset specificity, behavioral uncertainty, and the influence of resource munificence on the strength of the sales growth/ employment growth relationship. Asset specificity is theorized to be a positive moderator of the relationship between sales growth and employment growth. When the behavioral uncertainty associated with adding new employees is greater than that of outsourcing or subcontracting, it is hypothesized to be a negative moderator of the sales growth/employment growth relationship. We also hypothesize that resource scarcity will strengthen those relationships.