Prediction of mortality and conception rates of beef breeding cattle in northern Australia

In current simulation packages for the management of extensive beef-cattle enterprises, the relationships for the key biological rates (namely conception and mortality) are quite rudimentary. To better estimate these relationships, cohort-level data covering 17 100 cow-years from six sites across northern Australia were collated and analysed. Further validation data, from 7200 cow-years, were then used to test these relationships. Analytical problems included incomplete and non-standardised data, considerable levels of correlation among the 'independent' variables, and the close similarity of alternate possible models. In addition to formal statistical analyses of these data, the theoretical equations for predicting mortality and conception rates in the current simulation models were reviewed, and then reparameterised and recalibrated where appropriate. The final models explained up to 80% of the variation in the data. These are now proposed as more accurate and useful models to be used in the prediction of biological rates in simulation studies for northern Australia. © The State of Queensland (through the Department of Agriculture, Fisheries and Forestry) 2012. © CSIRO.

智能交通仿真与车辆Agent决策策略的研究

文章介绍了Agent技术及特点,根据Agent的原理及其仿真的优势,着重叙述了Agent技术在交通仿真中的应用,详细探讨了基于Agent的智能仿真系统中车辆Agent的决策特点及模糊决策方法,同时,还分析了驾驶员因素对驾驶行为的影响。

Análise do desempenho de autoestradas através de microssimulação

Portugal é um dos países europeus com melhor cobertura espacial e populacional de rede de autoestradas (5º entre os 27 da UE). O acentuado crescimento desta rede nos últimos anos leva a que seja necessária a utilização de metodologias de análise e avaliação da qualidade do serviço que é prestado nestas infraestruturas, relativamente às condições de circulação. Usualmente, a avaliação da qualidade de serviço é efetuada por intermédio de metodologias internacionalmente aceites, das quais se destaca a preconizada no Highway Capacity Manual (HCM). É com esta última metodologia que são habitualmente determinados em Portugal, os níveis de serviço nas diversas componentes de uma autoestrada (secções correntes, ramos de ligação e segmentos de entrecruzamento). No entanto, a sua transposição direta para a realidade portuguesa levanta algumas reservas, uma vez que os elementos que compõem o ambiente rodoviário (infraestrutura, veículo e condutor) são distintos dos da realidade norte-americana para a qual foi desenvolvida. Assim, seria útil para os atores envolvidos no setor rodoviário dispor de metodologias desenvolvidas para as condições portuguesas, que possibilitassem uma caracterização mais realista da qualidade de serviço ao nível da operação em autoestradas. No entanto, importa referir que o desenvolvimento de metodologias deste género requer uma quantidade muito significativa de dados geométricos e de tráfego, o que acarreta uma enorme necessidade de meios, quer humanos, quer materiais. Esta abordagem é assim de difícil execução, sendo por isso necessário recorrer a metodologias alternativas para a persecução deste objetivo. Ultimamente tem-se verificado o uso cada vez mais generalizado de modelos de simulação microscópica de tráfego, que simulando o movimento individual dos veículos num ambiente virtual permitem realizar análises de tráfego. A presente dissertação apresenta os resultados obtidos no desenvolvimento de uma metodologia que procura recriar, através de simuladores microscópicos de tráfego, o comportamento das correntes de tráfego em secções correntes de autoestradas com o intuito de, posteriormente, se proceder à adaptação da metodologia preconizada no HCM (na sua edição de 2000) à realidade portuguesa. Para tal, com os simuladores microscópicos utilizados (AIMSUN e VISSIM) procurou-se reproduzir as condições de circulação numa autoestrada portuguesa, de modo a que fosse possível analisar as alterações sofridas no comportamento das correntes de tráfego após a modificação dos principais fatores geométricos e de tráfego envolvidos na metodologia do HCM 2000. Para o efeito, realizou-se uma análise de sensibilidade aos simuladores de forma a avaliar a sua capacidade para representar a influência desses fatores, com vista a, numa fase posterior, se quantificar o seu efeito para a realidade nacional e dessa forma se proceder à adequação da referida metodologia ao contexto português. Em resumo, o presente trabalho apresenta as principais vantagens e limitações dos microssimuladores AIMSUN e VISSIM na modelação do tráfego de uma autoestrada portuguesa, tendo-se concluído que estes simuladores não são capazes de representar de forma explícita alguns dos fatores considerados na metodologia do HCM 2000, o que impossibilita a sua utilização como ferramenta de quantificação dos seus efeitos e consequentemente inviabiliza a adaptação dessa metodologia à realidade nacional. São, no entanto, referidas algumas indicações de como essas limitações poderão vir a ser ultrapassadas, com vista à consecução futura dessa adequação.

Soluções de transporte ferroviário: simulação de marcha e de tráfego de veículos de tração diesel e elétrica

Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

Modelos de simulação em MATSim aplicados à análise de sistemas de transporte

Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes

A BDI-based approach for the assessment of driver's decision-making in commuter scenarios

The rapid growth of urban areas has a significant impact on traffic and transportation systems. New management policies and planning strategies are clearly necessary to cope with the more than ever limited capacity of existing road networks. The concept of Intelligent Transportation System (ITS) arises in this scenario; rather than attempting to increase road capacity by means of physical modifications to the infrastructure, the premise of ITS relies on the use of advanced communication and computer technologies to handle today’s traffic and transportation facilities. Influencing users’ behaviour patterns is a challenge that has stimulated much research in the ITS field, where human factors start gaining great importance to modelling, simulating, and assessing such an innovative approach. This work is aimed at using Multi-agent Systems (MAS) to represent the traffic and transportation systems in the light of the new performance measures brought about by ITS technologies. Agent features have good potentialities to represent those components of a system that are geographically and functionally distributed, such as most components in traffic and transportation. A BDI (beliefs, desires, and intentions) architecture is presented as an alternative to traditional models used to represent the driver behaviour within microscopic simulation allowing for an explicit representation of users’ mental states. Basic concepts of ITS and MAS are presented, as well as some application examples related to the subject. This has motivated the extension of an existing microscopic simulation framework to incorporate MAS features to enhance the representation of drivers. This way demand is generated from a population of agents as the result of their decisions on route and departure time, on a daily basis. The extended simulation model that now supports the interaction of BDI driver agents was effectively implemented, and different experiments were performed to test this approach in commuter scenarios. MAS provides a process-driven approach that fosters the easy construction of modular, robust, and scalable models, characteristics that lack in former result-driven approaches. Its abstraction premises allow for a closer association between the model and its practical implementation. Uncertainty and variability are addressed in a straightforward manner, as an easier representation of humanlike behaviours within the driver structure is provided by cognitive architectures, such as the BDI approach used in this work. This way MAS extends microscopic simulation of traffic to better address the complexity inherent in ITS technologies.

Interactive DC-DC converters tools for instant design and education

This paper deals with the usage of interactive simulations tools to serve as an oriented design tool for the lectures and laboratory experiments in the power electronics courses. A dynamic and interactive visualization of simulations for idealized converters in steady state are provided by the proposed educational tools, allowing students to acquire qualification in non-isolated DC-DC converters, without previous circuitry knowledge, either without the usage of sophisticated simulation packages. The interaction with proposed simulation tools can be accomplished by student using direct or graphic mode. In direct mode the parameters related with the design of converter can be inserted simply editing default values presented in textboxes, while in the graphic mode students interact indirectly with design information by manipulating visual widgets. In order to corroborate the proposed interactive simulation tools, comparisons of results from buck-boost and boost converters on proposed tools and a well-known simulator package with those on experimental evaluation from laboratory classes were presented. © 2009 IEEE.

Verkehrsmonitoring mit Hilfe von Radarfernerkundung

Für die Zukunft wird eine Zunahme an Verkehr prognostiziert, gleichzeitig herrscht ein Mangel an Raum und finanziellen Mitteln, um weitere Straßen zu bauen. Daher müssen die vorhandenen Kapazitäten durch eine bessere Verkehrssteuerung sinnvoller genutzt werden, z.B. durch Verkehrsleitsysteme. Dafür werden räumlich aufgelöste, d.h. den Verkehr in seiner flächenhaften Verteilung wiedergebende Daten benötigt, die jedoch fehlen. Bisher konnten Verkehrsdaten nur dort erhoben werden, wo sich örtlich feste Meßeinrichtungen befinden, jedoch können damit die fehlenden Daten nicht erhoben werden. Mit Fernerkundungssystemen ergibt sich die Möglichkeit, diese Daten flächendeckend mit einem Blick von oben zu erfassen. Nach jahrzehntelangen Erfahrungen mit Fernerkundungsmethoden zur Erfassung und Untersuchung der verschiedensten Phänomene auf der Erdoberfläche wird nun diese Methodik im Rahmen eines Pilotprojektes auf den Themenbereich Verkehr angewendet. Seit Ende der 1990er Jahre wurde mit flugzeuggetragenen optischen und Infrarot-Aufnahmesystemen Verkehr beobachtet. Doch bei schlechten Wetterbedingungen und insbesondere bei Bewölkung, sind keine brauchbaren Aufnahmen möglich. Mit einem abbildenden Radarverfahren werden Daten unabhängig von Wetter- und Tageslichtbedingungen oder Bewölkung erhoben. Im Rahmen dieser Arbeit wird untersucht, inwieweit mit Hilfe von flugzeuggetragenem synthetischem Apertur Radar (SAR) Verkehrsdaten aufgenommen, verarbeitet und sinnvoll angewendet werden können. Nicht nur wird die neue Technik der Along-Track Interferometrie (ATI) und die Prozessierung und Verarbeitung der aufgenommenen Verkehrsdaten ausführlich dargelegt, es wird darüberhinaus ein mit dieser Methodik erstellter Datensatz mit einer Verkehrssimulation verglichen und bewertet. Abschließend wird ein Ausblick auf zukünftige Entwicklungen der Radarfernerkundung zur Verkehrsdatenerfassung gegeben.

Infrastrutture per la mobilità, interventi di trasformazione territoriale e valorizzazione immobiliare: una proposta metodologica di approccio integrato

In una situazione caratterizzata dalla scarsità delle risorse finanziare a disposizione degli enti locali, che rende necessario il contributo dei privati alla realizzazione delle opere pubbliche, e dalla scarsità delle risorse ambientali, che impone di perseguire la sostenibilità degli interventi, la tesi si pone l’obiettivo di rendere le realizzazioni di nuove infrastrutture viarie “attive” rispetto al contesto in cui si collocano, garantendo l’impegno di tutte parti coinvolte. Si tratta di ottenere il contributo dei privati oltre che per le opere di urbanizzazione primaria, funzionali all’insediamento stesso, anche per la realizzazione di infrastrutture viarie non esclusivamente dedicate a questo, ma che sono necessarie per garantirne la sostenibilità. Tale principio, che viene anche denominato “contributo di sostenibilità”, comincia oggi a trovare un’applicazione nelle pratiche urbanistiche, sconta ancora alcune criticità, in quanto i casi sviluppati si basano spesso su considerazioni che si prestano a contenziosi tra operatori privati e pubblica amministrazione. Ponendosi come obiettivo la definizione di una metodologia di supporto alla negoziazione per la determinazione univoca e oggettiva del contributo da chiedere agli attuatori delle trasformazioni per la realizzazione di nuove infrastrutture viarie, ci si è concentrati sullo sviluppo di un metodo operativo basato sull’adozione dei modelli di simulazione del traffico a 4 stadi. La metodologia proposta è stata verificata attraverso l’applicazione ad un caso di studio, che riguarda la realizzazione di un nuovo asse viario al confine tra i comuni di Castel Maggiore ed Argelato. L’asse, indispensabile per garantire l’accessibilità alle nuove aree di trasformazione che interessano quel quadrante, permette anche di risolvere alcune criticità viabilistiche attualmente presenti. Il tema affrontato quindi è quello della determinazione del contributo che ciascuno degli utilizzatori del nuovo asse dovrà versare al fine di consentirne la realizzazione. In conclusione, si formulano alcune considerazioni sull’utilità della metodologia proposta e sulla sua applicabilità a casi analoghi.

Comparative evaluation of microscopic car-following behavior

Microscopic traffic-simulation tools are increasingly being applied to evaluate the impacts of a wide variety of intelligent transport, systems (ITS) applications and other dynamic problems that are difficult to solve using traditional analytical models. The accuracy of a traffic-simulation system depends highly on the quality of the traffic-flow model at its core, with the two main critical components being the car-following and lane-changing models. This paper presents findings from a comparative evaluation of car-following behavior in a number of traffic simulators [advanced interactive microscopic simulator for urban and nonurban networks (AIMSUN), parallel microscopic simulation (PARAMICS), and Verkehr in Statiten-simulation (VISSIM)]. The car-following algorithms used in these simulators have been developed from a variety of theoretical backgrounds and are reported to have been calibrated on a number of different data sets. Very few independent studies have attempted to evaluate the performance of the underlying algorithms based on the same data set. The results reported in this study are based on a car-following experiment that used instrumented vehicles to record the speed and relative distance between follower and leader vehicles on a one-lane road. The experiment was replicated in each tool and the simulated car-following behavior was compared to the field data using a number of error tests. The results showed lower error values for the Gipps-based models implemented in AIMSUN and similar error values for the psychophysical spacing models used in VISSIM and PARAMICS. A qualitative drift and goal-seeking behavior test, which essentially shows how the distance headway between leader and follower vehicles should oscillate around a stable distance, also confirmed the findings.

Bayesian precalibration of a large stochastic microsimulation model

Calibration of stochastic traffic microsimulation models is a challenging task. This paper proposes a fast iterative probabilistic precalibration framework and demonstrates how it can be successfully applied to a real-world traffic simulation model of a section of the M40 motorway and its surrounding area in the U.K. The efficiency of the method stems from the use of emulators of the stochastic microsimulator, which provides fast surrogates of the traffic model. The use of emulators minimizes the number of microsimulator runs required, and the emulators' probabilistic construction allows for the consideration of the extra uncertainty introduced by the approximation. It is shown that automatic precalibration of this real-world microsimulator, using turn-count observational data, is possible, considering all parameters at once, and that this precalibrated microsimulator improves on the fit to observations compared with the traditional expertly tuned microsimulation. © 2000-2011 IEEE.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

An Integrated approach to street canyon pollution modelling.

An integrated method for the prediction of the spatial pollution distribution within a street canyon directly from a microscopic traffic simulation model is outlined. The traffic simulation package Paramics is used to model the flow of vehicles in realistic traffic conditions on a real road network. This produces details of the amount of pollutant produced by each vehicle at any given time. The authors calculate the dispersion of the pollutant using a particle tracking diffusion method which is superimposed on a known velocity and turbulence field. This paper shows how these individual components may be integrated to provide a practical street canyon pollution model. The resulting street canyon pollution model provides isoconcentrations of pollutant within the road topography.

Dynamic Programming Approaches for Estimating and Applying Large-scale Discrete Choice Models

People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Evaluating effects of eco-driving at traffic intersections based on traffic micro-simulation

Eco-driving is an initiative driving behavior which aims to reduce fuel consumption and emissions from automobiles. Recently, it has attracted increasing interests and has been adopted by many drivers in Australia. Although many of the studies have revealed considerable benefits in terms of fuel consumption and emissions after utilising eco-driving, most of the literature investigated eco-driving effects on individual driver but not traffic flow. The driving behavior of eco-drivers will potentially affect other drivers and thereby affects the entire traffic flow. To comprehensively assess and understand how effectively eco-driving can perform, therefore, measurement on traffic flow is necessary. In this paper, we proposed and demonstrated an evaluation method based on a microscopic traffic simulator (Aimsun). We focus on one particular eco-driving style which involves moderate and smooth acceleration. We evaluated both traffic performance (travel time) and environmental performance (fuel consumption and CO2 emission) at traffic intersection level in a simple simulation model. The before-and-after comparisons indicated potentially negative impacts when using eco-driving, which highlighted the necessity to carefully evaluate and improve eco-driving before wide promotion and implementation.