Urban traffic state estimation: Fusing point and zone based data

Loop detectors are the oldest and widely used traffic data source. On urban arterials, they are mainly installed for signal control. Recently state of the art Bluetooth MAC Scanners (BMS) has significantly captured the interest of stakeholders for exploiting it for area wide traffic monitoring. Loop detectors provide flow- a fundamental traffic parameter; whereas BMS provides individual vehicle travel time between BMS stations. Hence, these two data sources complement each other, and if integrated should increase the accuracy and reliability of the traffic state estimation. This paper proposed a model that integrates loops and BMS data for seamless travel time and density estimation for urban signalised network. The proposed model is validated using both real and simulated data and the results indicate that the accuracy of the proposed model is over 90%.

Optimising offsets and bandwidths in vehicle traffic networks

Bandwidths and offsets are important components in vehicle traffic control strategies. This article proposes new methods for quantifying and selecting them. Bandwidth is the amount of green time available for vehicles to travel through adjacent intersections without the requirement to stop at the second traffic light. The offset is the difference between the starting-time of ``green'' periods at two adjacent intersections, along a given route. The core ideas in this article were developed during the 2013 Maths and Industry Study Group in Brisbane, Australia. Analytical expressions for computing bandwidth, as a function of offset, are developed. An optimisation model, for selecting offsets across an arterial, is proposed. Arterial roads were focussed upon, as bandwidth and offset have a greater impact on these types of road as opposed to a full traffic network. A generic optimisation-simulation approach is also proposed to refine an initial starting solution, according to a specified metric. A metric that reflects the number of stops, and the distance between stops, is proposed to explicitly reduce the dissatisfaction of road users, and to implicitly reduce fuel consumption and emissions. Conceptually the optimisation-simulation approach is superior as it handles real-life complexities and is a global optimisation approach. The models and equations in this article can be used in road planning and traffic control.

Residential balconies with road traffic noise : a combined source image and radiosity model

Several significant studies have been made in recent decades toward understanding road traffic noise and its effects on residential balconies. These previous studies have used a variety of techniques such as theoretical models, scale models and measurements on real balconies. The studies have considered either road traffic noise levels within the balcony space or inside an adjacent habitable room or both. Previous theoretical models have used, for example, simplified specular reflection calculations, boundary element methods (BEM), adaptations of CoRTN or the use of Sabine Theory. This paper presents an alternative theoretical model to predict the effects of road traffic noise spatially within the balcony space. The model includes a specular reflection component by calculating up to 10 orders of source images. To account for diffusion effects, a two compartment radiosity component is utilised. The first radiosity compartment is the urban street, represented as a street with building facades on either side. The second radiosity compartment is the balcony space. The model is designed to calculate the predicted road traffic noise levels within the balcony space and is capable of establishing the effect of changing street and balcony geometries. Screening attenuation algorithms are included to determine the effects of solid balcony parapets and balcony ceiling shields.

The Arab Spring and its social media audiences : English and Arabic Twitter users and their networks

2011 ‘Arab Spring’ are likely to overstate the impact of Facebook and Twitter on these uprisings, it is nonetheless true that protests and unrest in countries from Tunisia to Syria generated a substantial amount of social media activity. On Twitter alone, several millions of tweets containing the hashtags #libya or #egypt were generated during 2011, both by directly affected citizens of these countries, and by onlookers from further afield. What remains unclear, though, is the extent to which there was any direct interaction between these two groups (especially considering potential language barriers between them). Building on hashtag datasets gathered between January and November 2011, this paper compares patterns of Twitter usage during the popular revolution in Egypt and the civil war in Libya. Using custom-made tools for processing ‘big data’, we examine the volume of tweets sent by English-, Arabic-, and mixed-language Twitter users over time, and examine the networks of interaction (variously through @replying, retweeting, or both) between these groups as they developed and shifted over the course of these uprisings. Examining @reply and retweet traffic, we identify general patterns of information flow between the English- and Arabic-speaking sides of the Twittersphere, and highlight the roles played by users bridging both language spheres.

Traffic incident clearance time and arrival time prediction based on hazard models

Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an ffective input for travel time prediction. In this paper, the hazard based prediction odels are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS) for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

Enabling safe autonomous driving in real-world city traffic using multiple criteria decision making

This paper addresses the topic of real-time decision making for autonomous city vehicles, i.e., the autonomous vehicles' ability to make appropriate driving decisions in city road traffic situations. The paper explains the overall controls system architecture, the decision making task decomposition, and focuses on how Multiple Criteria Decision Making (MCDM) is used in the process of selecting the most appropriate driving maneuver from the set of feasible ones. Experimental tests show that MCDM is suitable for this new application area.

Methodology for developing real-time motorway traffic risk identification models using individual-vehicle data

Most of existing motorway traffic safety studies using disaggregate traffic flow data aim at developing models for identifying real-time traffic risks by comparing pre-crash and non-crash conditions. One of serious shortcomings in those studies is that non-crash conditions are arbitrarily selected and hence, not representative, i.e. selected non-crash data might not be the right data comparable with pre-crash data; the non-crash/pre-crash ratio is arbitrarily decided and neglects the abundance of non-crash over pre-crash conditions; etc. Here, we present a methodology for developing a real-time MotorwaY Traffic Risk Identification Model (MyTRIM) using individual vehicle data, meteorological data, and crash data. Non-crash data are clustered into groups called traffic regimes. Thereafter, pre-crash data are classified into regimes to match with relevant non-crash data. Among totally eight traffic regimes obtained, four highly risky regimes were identified; three regime-based Risk Identification Models (RIM) with sufficient pre-crash data were developed. MyTRIM memorizes the latest risk evolution identified by RIM to predict near future risks. Traffic practitioners can decide MyTRIM’s memory size based on the trade-off between detection and false alarm rates. Decreasing the memory size from 5 to 1 precipitates the increase of detection rate from 65.0% to 100.0% and of false alarm rate from 0.21% to 3.68%. Moreover, critical factors in differentiating pre-crash and non-crash conditions are recognized and usable for developing preventive measures. MyTRIM can be used by practitioners in real-time as an independent tool to make online decision or integrated with existing traffic management systems.

Spontaneous large volume adipose tissue generation from a vascularized pedicled fat flap inside a chamber space

A novel method of spontaneous generation of new adipose tissue from an existing fat flap is described. A defined volume of fat flap based on the superficial inferior epigastric vascular pedicle in the rat was elevated and inset into a hollow plastic chamber implanted subcutaneously in the groin of the rat. The chamber walls were either perforated or solid and the chambers either contained poly(D,L-lactic-co-glycolic acid) (PLGA) sponge matrix or not. The contents were analyzed after being in situ for 6 weeks. The total volume of the flap tissue in all groups except the control groups, where the flap was not inserted into the chambers, increased significantly, especially in the perforated chambers (0.08 ± 0.007 mL baseline compared to 1.2 ± 0.08 mL in the intact ones). Volume analysis of individual component tissues within the flaps revealed that the adipocyte volume increased and was at a maximum in the chambers without PLGA, where it expanded from 0.04 ± 0.003 mL at insertion to 0.5 ± 0.08 mL (1250% increase) in the perforated chambers and to 0.16 ± 0.03 mL (400% increase) in the intact chambers. Addition of PLGA scaffolds resulted in less fat growth. Histomorphometric analysis rather than simple hypertrophy documented an increased number of adipocytes. The new tissue was highly vascularized and no fat necrosis or atypical changes were observed.

Noisy Bluetooth traffic data?

Traffic state estimation in an urban road network remains a challenge for traffic models and the question of how such a network performs remains a difficult one to answer for traffic operators. Lack of detailed traffic information has long restricted research in this area. The introduction of Bluetooth into the automotive world presented an alternative that has now developed to a stage where large-scale test-beds are becoming available, for traffic monitoring and model validation purposes. But how much confidence should we have in such data? This paper aims to give an overview of the usage of Bluetooth, primarily for the city-scale management of urban transport networks, and to encourage researchers and practitioners to take a more cautious look at what is currently understood as a mature technology for monitoring travellers in urban environments. We argue that the full value of this technology is yet to be realised, for the analytical accuracies peculiar to the data have still to be adequately resolved.

A finite volume scheme with preconditioned Lanczos method for two-dimensional space-fractional reaction–diffusion equations

Fractional differential equations have been increasingly used as a powerful tool to model the non-locality and spatial heterogeneity inherent in many real-world problems. However, a constant challenge faced by researchers in this area is the high computational expense of obtaining numerical solutions of these fractional models, owing to the non-local nature of fractional derivatives. In this paper, we introduce a finite volume scheme with preconditioned Lanczos method as an attractive and high-efficiency approach for solving two-dimensional space-fractional reaction–diffusion equations. The computational heart of this approach is the efficient computation of a matrix-function-vector product f(A)bf(A)b, where A A is the matrix representation of the Laplacian obtained from the finite volume method and is non-symmetric. A key aspect of our proposed approach is that the popular Lanczos method for symmetric matrices is applied to this non-symmetric problem, after a suitable transformation. Furthermore, the convergence of the Lanczos method is greatly improved by incorporating a preconditioner. Our approach is show-cased by solving the fractional Fisher equation including a validation of the solution and an analysis of the behaviour of the model.

Crime, Justice and Social Democracy: Proceedings of the Second International Conference, 2013, volume 2

The refereed papers contained in this volume of conference proceedings were among those presented at the 2nd International Conference on Crime, Justice and Social Democracy, hosted by the Crime and Justice Research Centre, Faculty of Law, QUT, from 8 – 11 July 2013. The conference attracted an impressive list of speakers from Australasia, Europe, North America and Latin America. These seven papers can be viewed at the Crime and Justice Research Centre’s website at http://crimejusticeconference.com/publications/ as can Volume 1 representing another 26 selected papers from the conference. As with the papers contained in the first volume, this set of papers raises important questions about the links between crime, justice and social democracy, and continues the contribution that the Crime and Justice Research Centre makes towards engaging with these topics. We thank all those who submitted papers for review for this second volume of proceedings, as well as the peer reviewers for taking the time to review the papers, often within very tight timelines.

Relating urban airborne particle concentrations to shipping using carbon based elemental emission ratios

This study demonstrates a novel method for testing the hypothesis that variations in primary and secondary particle number concentration (PNC) in urban air are related to residual fuel oil combustion at a coastal port lying 30 km upwind, by examining the correlation between PNC and airborne particle composition signatures chosen for their sensitivity to the elemental contaminants present in residual fuel oil. Residual fuel oil combustion indicators were chosen by comparing the sensitivity of a range of concentration ratios to airborne emissions originating from the port. The most responsive were combinations of vanadium and sulfur concentration ([S], [V]) expressed as ratios with respect to black carbon concentration ([BC]). These correlated significantly with ship activity at the port and with the fraction of time during which the wind blew from the port. The average [V] when the wind was predominantly from the port was 0.52 ng.m-3 (87%) higher than the average for all wind directions and 0.83 ng.m-3 (280%) higher than that for the lowest vanadium yielding wind direction considered to approximate the natural background. Shipping was found to be the main source of V impacting urban air quality in Brisbane. However, contrary to the stated hypothesis, increases in PNC related measures did not correlate with ship emission indicators or ship traffic. Hence at this site ship emissions were not found to be a major contributor to PNC compared to other fossil fuel combustion sources such as road traffic, airport and refinery emissions.

Origins of Australian Football: Victoria's Early History. Volume 2 : A golden era begins : Football in 'Marvellous Melbourne', 1877 to 1885

This is the second volume of a five volume series that describes, assesses, and analyses football in Victoria during the nineteenth century. This volume looks at the cultural contexts of the sport in the late 1870s and early 1880s, describes the important matches played, and provides a full statistical account of this time period. This book is the first comprehensive discussion of the early period in Australian football's development.

Modelling total duration of traffic incidents including incident detection and recovery time

Traffic incidents are key contributors to non-recurrent congestion, potentially generating significant delay. Factors that influence the duration of incidents are important to understand so that effective mitigation strategies can be implemented. To identify and quantify the effects of influential factors, a methodology for studying total incident duration based on historical data from an ‘integrated database’ is proposed. Incident duration models are developed using a selected freeway segment in the Southeast Queensland, Australia network. The models include incident detection and recovery time as components of incident duration. A hazard-based duration modelling approach is applied to model incident duration as a function of a variety of factors that influence traffic incident duration. Parametric accelerated failure time survival models are developed to capture heterogeneity as a function of explanatory variables, with both fixed and random parameters specifications. The analysis reveals that factors affecting incident duration include incident characteristics (severity, type, injury, medical requirements, etc.), infrastructure characteristics (roadway shoulder availability), time of day, and traffic characteristics. The results indicate that event type durations are uniquely different, thus requiring different responses to effectively clear them. Furthermore, the results highlight the presence of unobserved incident duration heterogeneity as captured by the random parameter models, suggesting that additional factors need to be considered in future modelling efforts.