Models based on micro-simulation of traffic flows have proven to be useful tools in the study of various traffic systems. Today, there is a wealth of traffic microsimulation models developed for freeway and urban street networks. The road mileage is however in many countries dominated by rural highways. Hence, there is a need for rural road traffic simulation models capable of assessing the performance of such road environments. This thesis introduces a versatile traffic micro-simulation model for the rural roads of today and of the future. The developed model system considers all common types of rural roads including effects of intersections and roundabouts on the main road traffic. The model is calibrated and validated through a simulation study comparing a two-lane highway to rural road designs with separated oncoming traffic lanes. A good general agreement between the simulation results and the field data is established. The interest in road safety and the environmental impact of traffic is growing. Recent research has indicated that traffic simulation can be of use in these areas as well as in traditional capacity and level-of-service studies. In the road safety area more attention is turning towards active safety improving countermeasures designed to improve road safety by reducing the number of driver errors and the accident risks. One important example is Advanced Driver Assistance Systems (ADAS). The potential to use traffic simulation to evaluate the road safety effects of ADAS is investigated in the last part of this thesis. A car-following model for simulation of traffic including ADAS-equipped vehicles is proposed and the developed simulation framework is used to study important properties of a traffic simulation model to be used for safety evaluation of ADAS. Driver behavior for ADAS-equipped vehicles has usually not been considered in simulation studies including ADAS-equipped vehicles. The work in this thesis does however indicate that modeling of the behavior of drivers in ADAS-equipped vehicles is essential for reliable conclusions on the road safety effects of ADAS. / <p>Report code: LiU-Tek-Lic-2005:60.</p>

The demand for road freight transport continues to grow with the growing economy, resulting in increased fossil fuel consumption and emissions. At the same time, the fossil fuel use needs to decrease substantially to counteract the ongoing global warming. One way to reduce fuel consumption is to utilize emerging intelligent transport system (ITS) technologies and introduce heavy-duty vehicle (HDV) platooning, i.e. HDVs driving with small inter-vehicle gaps enabled by the use of sensors and controllers. It is of importance for transport authorities and industries to investigate the effects of introducing HDV platooning. Previous studies have investigated the potential benefits, but the effects in real traffic, both for the platoons and for the surrounding vehicles, have barely been explored. To further utilize ITS and optimize the platoons, information about the traffic situation ahead can be used to optimize the vehicle trajectories for the platoons. Paper I presents a dynamic programming-based optimal speed control including information of the traffic situation ahead. The optimal control is applied to HDV platoons in a deceleration case and the potential fuel consumption reduction is evaluated by a microscopic traffic simulation study with HDV platoons driving in real traffic conditions. The effects for the surrounding traffic are also analysed. Paper II and Paper III present a simulation platform to assess the effects of HDV platooning in real traffic conditions. Through simulation studies, the potential fuel consumption reduction by adopting HDV platooning on a real highway stretch is evaluated, and the effects for the other vehicles in the network are investigated. / Efterfrågan på godstransporter på väg fortsätter att öka i takt med den växande ekonomin, vilket resulterar i ökad förbrukning av fossila bränslen och ökade utsläpp. Samtidigt behöver användandet av fossila bränslen minska för att motverka den pågående globala uppvärmningen. Ett sätt för att minska bränsleförbrukningen är att utnyttja den teknik kring intelligenta transportsystem som är under utveckling och introducera lastbilskonvojer, det vill säga lastbilar som använder sensorer och regulatorer för att kunna köra med korta avstånd mellan sig. För transportföretag och -myndigheter är det viktigt att undersöka effekterna av att införa lastbilskonvojkörning. Tidigare studier har undersökt de möjliga fördelarna, men effekterna vid körning i trafik, både för konvojerna och för omgivande fordon, är outforskade. För att ytterligare utnyttja intelligenta transportsystem och optimera konvojerna kan information om trafiksituationen längre fram på vägen användas för att optimera konvojernas körning. Artikel I presenterar en optimal hastighetsregulator baserad på dynamisk programmering och som inkluderar information om trafiksituationen längre fram. Den optimala regulatorn appliceras på lastbilskonvojer under ett inbromsningsscenario och den potentiella minskningen i bränsleförbrukning utvärderas genom en mikroskopisk trafiksimuleringsstudie där lastbilskonvojerna kör i verkliga trafikförhållanden. Effekterna för omgivande fordon är också analyserade.Artikel II och artikel III presenterar en simuleringsplattform för att utvärdera effekterna av lastbilskonvojkörning i verkliga trafikförhållanden. Genom simuleringsstudier analyseras den potentiella bränsleförbrukningsminskningen då lastbilskonvojer körs på en verklig motorvägssträcka och effekterna för de övriga fordonen på vägen undersöks. / <p>QC 20180516</p>

Currently, the road cargo system with low or zero CO2 emission is under rapid development. Heavy-duty trucks with electrified driveline systems will be the workhorse of future freight. But developing such a brand new and very complex system and adapting it to various application scenarios, such as long-haul freight, city distribution or construction loading, is still a big problem, because there is no previous experience to refer to. There is no standard development procedure or constraint framework for uncertainty either. Simulation on a massive scale with thousands of truck agents will be of great use for developing such a road-cargo system. System engineering will be the guiding methodology for this thesis project about developing a high-performance and multi-adaptive electrified driveline system. Referring to the classical V-shape development methodology, the complex concept will be divided into different levels of subsystems, from the large application scenarios to traffic simulation, driveline system simulation, electric motor and controller blocks development, and the system integration, performance verification and output of the results. The massive scale of traffic simulation will be implemented in AnyLogic, which does not contain any accurate agent model with vehicle dynamic motion during simulation. Thus, a precise vehicle agent model needs to be developed and embedded into AnyLogic’s simulation scenario, so as to make the simulation very close to reality, and to be able to evaluate vehicle concepts as well. The driveline system will be developed in Matlab/Simulink while the information communication between them will be realised in the form of computational calculation functions through the C language program. The development of the driveline model is also progressive. First, an equation-based full glider model was constructed. It simulates the scenario of a heavy-loaded truck driving on a steep slope (30% grade), decelerating from the initial 70 km/h to 0 km/h and then remaining stationary. The second model added the functionality of velocity input and output, enabling information exchange with AnyLogic. It will judge the real-time speed and the desired speed to decide whether to accelerate or decelerate and it uses the “Bang-Bang” control method of the electric motor. But this control mode results in a massive and frequent change in the electric motor output power, leading to extremely high energy consumption and in real life significantly shortened motor lifetime. So a powerful PI controller was introduced to the third Simulink model. The PI controller is embedded in the electric motor and it will replace the “Bang-Bang” control method. The “PID” control method provides a more stable power output so that the truck’s real-time speed can approach the target speed more smoothly. This control system can adapt to a variety of speed inputs and it can decide whether to output full power or partial power, depending on the speed difference. The third version of the Simulink model with PI controller has been verified as an acceptable model through various inputs of different speeds, and it will be converted into a C language program to be embedded in AnyLogic for massive traffic simulation. / Utveckling av godstrafiksystem på väg med låga eller noll CO2-utsläpp är under snabb utveckling. Tunga lastbilar med elektrifierade drivlinesystem kommer förmodligen att vara dominerande i framtiden för vägfrakt. Att utveckla ett helt nytt system med hög teknisk komplexitet och anpassning till olika tillämpningsscenarier, som fjärrtransport, distribution eller bygg och anläggning, är en stor utmaning på grund av kritiska begränsningar i exempelvis erfarenhet. Det finns heller ingen etablerad utvecklingsmetodik baserad på tidigare erfarenhet eller ramverk för att hantera osäkerheter. Simuleringar med tusentals lastbilsagenter kan vara till stor nytta och stöd för att utveckla lastbilssystem. Systemteknik kommer att vara den vägledande metodiken för detta examensarbete för att utveckla ett avancerat och multiadaptivt elektrifierat drivlinesystem. Med hjälp av den klassiska "V"-utvecklingsmetodiken kommer drivlinemodellen delas in i olika nivåer av delsystem utifrån de tidigare nämnda olika tillämpnings-scenarierna för trafiksimulering för att sedan utföra simulering av komplett drivlinesystem, utveckling av elmotor och reglersystem till systemintegration, prestandaverifiering och analys av resultat. Trafiksimulering är tänkt att implementeras i AnyLogic, som inte innehåller någon modell baserad på fordonsdynamik där drivlineegenskaper beaktas. Därför måste en specifk fordonsdynamikmodell utvecklas för fordonsagenten och bäddas in i AnyLogics simuleringsscenario för att göra simuleringen närmre verkligheten. Drivlinesystemet har utvecklats i Matlab/Simulink för att sedan realiseras i form av beräkningsfunktioner i C. Utvecklingen av drivlinemodellen görs iterativt. Först konstruerades en ekvationsbaserad full s.k. glidermodell. Den simulerar scenariot för en tung lastad lastbil som kör i en brant sluttning (30\% lutning), bromsar in från de ursprungliga 70 km/h till 0 km/h och förblir stillastående. I den andra modellen lades till gränssnitt för agentens begynnelsevärden och tillstånd vid tidsstegets slut, vilket möjliggjorde informationsutbyte med AnyLogic. Modellen analyserar realtidshastigheten och den önskade hastigheten för att sedan avgöra om agenten ska accelerera eller bromsa. Den använder "Bang-Bang"-reglermetoden för elmotorn. Men denna reglermetod resulterar i en frekvent och stor förändring av elmotorns uteffekt, vilket leder till hög energiförbrukning och i verkligheten avsevärt förkortad motorlivslängd. Därför introducerades en PI-regulator i den tredje Simulink-modellen. PI-regulatorn är inbäddad i elmotorn och ersätter "Bang-Bang"-reglermetoden. "PID"-regulatorn ger mer stabil effekt, så att lastbilens realtidshastighet mjukare kan närma sig målhastigheten. Detta reglersystem kan anpassas till en mängd olika begynnelsehastigheter och kan bestämma om full eller deleffekt ska matas ut beroende på skillnaden mellan realtidshastighet och målhastighet. Den tredje versionen av Simulink-modellen med PI-regulator har verifierats som en acceptabel modell genom olika begynnelsehastigheter och konverterats till ett C-program för att bäddas in i AnyLogic för trafiksimulering.

La simulation constitue une approche majeure pour la conception, le développement, l’analyse et l’évolution des systèmes urbains. Dans le contexte de cette thèse, nous nous intéressons à la modélisation et à la simulation des déplacements de flux (piéton, véhicule, cycle) au sein d’environnements urbains. Le contexte industriel dans lequel s’inscrit également cette thèse impose de considérer les déplacements de chaque entité dans un univers modélisé en trois dimensions. Nous proposons d’aborder les nombreux défis scientifiques et technologiques en modélisant les flux sous la forme d’entités autonomes appelées agents. La simulation orientée-agent nécessite de définir trois mécanismes principaux : le comportement des agents, leurs interactions avec les autres agents et leurs interactions avec l’environnement dans lequel ils évoluent. Ce dernier modélise la structure du monde ainsi que sa dynamique endogène. Malheureusement, il reste difficile de trouver des modèles d’environnement répondant aux différentes problématiques scientifiques et technologiques abordées dans cette thèse. Par conséquent, nous proposons un modèle d'environnement, nommé HEDGE (HEterogenous Dual Graph Environment). Il est basé sur une décomposition de l’environnement en zones reliées par des liens de navigation et de perception. Cette structure de graphe est au centre de notre modèle. Elle a été conçue pour permettre une modélisation naturelle de l’environnement et une simulation efficace du système constitué par cet environnement et les agents. Les missions et les processus dynamiques de l’environnement sont modélisés à l’aide de mécanismes inspirés des lois de la Physique. Les actions fournies par les agents et par les algorithmes calculant la dynamique endogène de l’environnement sont des forces à appliquer aux objets du monde. Un modèle de détection et de résolution de conflits entre ces forces est utilisé afin de garantir un état cohérent du modèle de l’environnement. Dans la dernière partie de cette thèse, nous illustrons l’utilisation du modèle HEDGE dans le cadre de deux projets d’aménagement de la ville de Belfort et de sa communauté d’agglomérations Le produit de l’application de ce modèle est utilisé à des fins d’études techniques (études préliminaires, avant-projet), de communication (concertations et débats publics) et de promotion (expositions, valorisation) sous la forme de logiciels interactifs en 3D. / Simulation constitutes a major approach for the conception, development, analysis and evolution of urban systems. This thesis focusses on the modeling and simulation of movements (pedestrian, vehicle, cycle) within urban environments. The industrial context associated with this thesis requires to consider the movements of each entity in a three dimensional universe. In this thesis, we propose to address the scientific and technological challenges by using autonomous entities, called agents, to model the individuals. In agent-based simulation three elements must be defined: the agent behaviors, their interactions with other agents, and with the environment. The environment models the structure of the world and its endogenous dynamics. Unfortunately, it is still difficult to find an environment model that answers all the different scientific and technological problems addressed in this thesis. Consequently, an environment model named HEterogenous Dual Graph Environment (or HEDGE) is proposed. The HEDGE model is based on a decomposition of the environment using zones that are linked with navigation and perception links. This graph structure is at the center of our model. It is designed to “naturally” model the environment, and it allows an efficient simulation of the system composed of the environment and the agents. The environment’s missions and dynamic processes are modeled using mechanisms, which are inspired by the laws of Physics. The actions provided by the agents and the endogenous dynamics algorithms correspond to physical forces to apply to objects in the world. A model of conflict detection and resolution between those forces is used to ensure the coherence of the environment model state. In the last part of this thesis, the HEDGE model is used in the context of two urban planning projects in the city of Belfort, and its metropolitan area. The product of this model’s application is used in the context of technical studies (preliminary studies, pre-project), communication (consultation and public debates) and promotion (exposition, valorization) in the form of interactive 3D software.

The collection and interpretation of data is a critical component of traffic and transportation engineering used to establish baseline performance measures and to forecast future conditions. One important source of traffic data is commercial motor vehicle (CMV) weight and classification data used as input to critical tasks in transportation design, operations, and planning. The evolution of Intelligent Transportation System (ITS) technologies has been providing transportation engineers and planners with an increased availability of CMV data. The primary sources of these data are automatic vehicle classification (AVC) and weigh-in-motion (WIM). Microscopic traffic simulation models have been used extensively to model the dynamic and stochastic nature of transportation systems including vehicle composition. One aspect of effective microscopic traffic simulation models that has received increased attention in recent years is the calibration of these models, which has traditionally been concerned with identifying the "best" parameter set from a range of acceptable values. Recent research has begun the process of automating the calibration process in an effort to accurately reflect the components of the transportation system being analyzed. The objective of this research is to develop a methodology in which the effects of CMVs can be included in the calibration of microscopic traffic simulation models. The research examines the ITS data available on weight and operating characteristics of CMVs and incorporates this data in the calibration of microscopic traffic simulation models. The research develops a methodology to model CMVs using microscopic traffic simulation models and then utilizes the output of these models to generate the data necessary to quantify the impacts of CMVs on infrastructure, travel time, and emissions. The research uses advanced statistical tools including principal component analysis (PCA) and recursive partitioning to identify relationships between data collection sites (i.e., WIM, AVC) such that the data collected at WIM sites can be utilized to estimate weight and length distributions at AVC sites. The research also examines methodologies to include the distribution or measures of central tendency and dispersion (i.e., mean, variance) into the calibration process. The approach is applied using the CORSIM model and calibrated utilizing an automated genetic algorithm methodology.

The collection and interpretation of data is a critical component of traffic and transportation engineering used to establish baseline performance measures and to forecast future conditions. One important source of traffic data is commercial motor vehicle (CMV) weight and classification data used as input to critical tasks in transportation design, operations, and planning. The evolution of Intelligent Transportation System (ITS) technologies has been providing transportation engineers and planners with an increased availability of CMV data. The primary sources of these data are automatic vehicle classification (AVC) and weigh-in-motion (WIM). Microscopic traffic simulation models have been used extensively to model the dynamic and stochastic nature of transportation systems including vehicle composition. One aspect of effective microscopic traffic simulation models that has received increased attention in recent years is the calibration of these models, which has traditionally been concerned with identifying the "best" parameter set from a range of acceptable values. Recent research has begun the process of automating the calibration process in an effort to accurately reflect the components of the transportation system being analyzed. The objective of this research is to develop a methodology in which the effects of CMVs can be included in the calibration of microscopic traffic simulation models. The research examines the ITS data available on weight and operating characteristics of CMVs and incorporates this data in the calibration of microscopic traffic simulation models. The research develops a methodology to model CMVs using microscopic traffic simulation models and then utilizes the output of these models to generate the data necessary to quantify the impacts of CMVs on infrastructure, travel time, and emissions. The research uses advanced statistical tools including principal component analysis (PCA) and recursive partitioning to identify relationships between data collection sites (i.e., WIM, AVC) such that the data collected at WIM sites can be utilized to estimate weight and length distributions at AVC sites. The research also examines methodologies to include the distribution or measures of central tendency and dispersion (i.e., mean, variance) into the calibration process. The approach is applied using the CORSIM model and calibrated utilizing an automated genetic algorithm methodology.

Submitted by Lucienne Costa (lucienneferreira@ufcg.edu.br) on 2018-05-03T18:38:37Z No. of bitstreams: 1 WILLY CARVALHO TIENGO – TESE (PPGCC) 2018.pdf: 4153575 bytes, checksum: 929b905dca8b61fcb0f831264752540f (MD5) / Made available in DSpace on 2018-05-03T18:38:37Z (GMT). No. of bitstreams: 1 WILLY CARVALHO TIENGO – TESE (PPGCC) 2018.pdf: 4153575 bytes, checksum: 929b905dca8b61fcb0f831264752540f (MD5) Previous issue date: 2018 / No Brasil, o transporte rodoviário é responsável por 58% do transporte de carga, que tem os acidentes como um grande problema, pois, em geral, esses ocasionam muitas vítimas, prejuízos econômicos relevantes e em alguns casos danos ambientais decorrentes de derramamento de carga. Estudos apontam que os prejuízos com os acidentes no transporte de carga em 2012 foram de mais de 9 bilhões de reais. Estudo realizado em 2007 pela PAMCARY, corretora de seguros e gestora de riscos, revelou que os eventos que combinam maior frequência e gravidade são tombamento e capotagem. Nesse sentido, esta pesquisa consiste na elaboração de um assistente avançado para motorista que objetiva alertar previamente sobre a velocidade limite da curva, a fim de diminuir os riscos de tombamento. Em outras palavras, consiste em buscar mitigar o problema auxiliando o motorista para que ele mantenha o veículo em uma velocidade segura, por meio de alertas e em prazo adequado, que permitam ao motorista tomar medidas corretivas em caso de estado inseguro. A solução foi desenvolvida a partir de uma arquitetura modular, que funciona da seguinte forma: por meio de sensores (velocidade, GPS e posição do acelerador), associado a mapas digitais, o risco de acidente é controlado constantemente. Com isso, um dispositivo poderia ser embarcado na cabine do veículo para emitir alertas visual e auditivo de risco de tombamento. A solução utiliza o indicador de estabilidade chamado Limiar Estático de Tombamento que, associado à informação a priori de mapas digitais, permite o cálculo do risco de tombamento com diferentes abordagens. No contexto da pesquisa, foram desenvolvidas 04 versões de assistentes. Além disso, foi proposto um arcabouço de simulação microscópica de trânsito baseado no modelo de raciocínio prático denominado de belief-desire-intention (BDI) para permitir o desenvolvimento e a validação de agentes inteligentes para Sistemas Avançados de Assistência ao Motorista de maneira rápida, flexível e fácil. Para avaliar o potencial dos assistentes, foi escolhida a BR-101, estrada federal de Alagoas com mais ocorrências de tombamento. Nessa rodovia, foram simulados 400 veículos para avaliar o desempenho dos assistentes propostos. Em particular, foram investigadas a efetividade, intrusividade, omissão e a segurança para avaliar o desempenho dos assistentes. / In Brazil, highway transportation is responsible for 58% of cargo transport. A relevant problem associated to cargo transport are the accidents, that generally cause an elevated number of victims, relevant economic losses and, in some cases, damages to the environment due to cargo spills, since there are also dangerous products being transported. Researches point out that the cost of accidents in cargo transportation in 2012 was more than BRL 9 billion. A study performed in 2007 by PAMCARY revealed the accidents profile: the events that combine higher frequency and gravity are rollover and tipping (considered here as the same nature). In this study, incompatible speed and fatigue, factors that are related to human actions, were pointed out as main causes of accidents; for another hand, sharp curve and poorly maintained roads are contributing factors to accidents. Therefore, the research proposal consists of the adoption of an assistant for warning in advance of over speed for a specific curve. This may reduce rollover risks. In other words, it would be mitigated the problem by helping the driver to maintain the vehicle in a safe speed, through customized alerts just in time to allow the driver to take corrective maneuvers in case of unsafe state. The solution is a modular architecture, which works as follows: through sensors (speed, GPS and throttle position) associated with digital maps, it is controlled the risk of accident constantly. With that, an embedded device at the vehicle’s cab could to emit visual and sound alerts warning the risk of rollover. In this work, it is proposed the adoption of the stability indicator known as Static Rollover Threshold, which is combined with a priori information from digital maps to allow the calculation of the rollover risk by different approaches. In the context of this research, 04 versions of assistants were developed. In addition, a microscopic traffic simulation framework was proposed based on the practical reasoning model named belief-desire-intention (BDI) to support the development and validation of intelligent agents for Advanced Driver Assistance Systems in a fast, flexible and easy way. To evaluate the assistants’ potential, the BR-101, Federal Highway of Alagoas with more occurrence of rollover, was chosen. On this highway, 400 vehicles were simulated to evaluate the performance of the proposed assistants. The effectiveness, intrusiveness, omission and safety of the assistants were investigated.

Les systèmes de transport intelligents ont acquis un grand intérêt pour la recherche ces dernières années. Alors que la simulation réaliste du trafic joue un rôle important, elle n'a pas reçu suffisamment d'attention. Cette thèse est consacrée à l'étude de la simulation du trafic au niveau microscopique et propose des modèles de mobilité des véhicules correspondants. À l'aide de méthodes d'apprentissage profond, ces modèles de mobilité ont fait leurs preuves avec une crédibilité prometteuse pour représenter les véhicules dans le monde réel. D'abord, un modèle de mobilité basé sur un réseau de neurones piloté par les données est proposé. Ce modèle provient de données de trajectoires du monde réel et permet de mimer des comportements de véhicules locaux. En analysant les performances de ce modèle de mobilité basé sur un apprentissage de base, nous indiquons qu’une amélioration est possible et proposons ses spécifications. Un MMC est alors introduit. La préparation de cette intégration est nécessaire, ce qui comprend un examen des modèles de mobilité traditionnels basés sur la dynamique et l’adaptation des modèles « classiques » à notre situation. Enfin, le modèle amélioré est présenté et une simulation de scénarios sophistiqués est construite pour valider les résultats théoriques. La performance de notre modèle de mobilité est prometteuse et des problèmes de mise en œuvre sont également discutés / The intelligent transportation systems gain great research interests in recent years. Although the realistic traffic simulation plays an important role, it has not received enough attention. This thesis is devoted to studying the traffic simulation in microscopic level, and proposes corresponding vehicular mobility models. Using deep learning methods, these mobility models have been proven with a promising credibility to represent the vehicles in real-world. Firstly, a data-driven neural network based mobility model is proposed. This model comes from real-world trajectory data and allows mimicking local vehicle behaviors. By analyzing the performance of this basic learning based mobility model, we indicate that an improvement is possible and we propose its specification. An HMM is then introduced. The preparation of this integration is necessary, which includes an examination of traditional dynamics based mobility models and the adaptation method of “classical” models to our situation. At last, the enhanced model is presented, and a sophisticated scenario simulation is built with it to validate the theoretical results. The performance of our mobility model is promising and implementation issues have also been discussed

Auf vielen hochbelasteten Autobahnabschnitten kommen Streckenbeeinflussungsanlagen (SBA) zum Einsatz, um die Verkehrssicherheit und den Verkehrsfluss zu verbessern. Hierbei werden Maßnahmen wie Geschwindigkeitsbeschränkungen und Warnungen weitestgehend automatisiert aufgrund der vorherrschenden Verkehrs- und Wetterbedingungen abgeleitet und über Wechselverkehrszeichen an die Verkehrsteilnehmer ausgegeben. Diese bewährte Form der Verkehrsbeeinflussung trifft auf sich verändernde Randbedingungen: Durch zunehmende Fahrzeugkonnektivität und -automatisierung sind signifikante Veränderungen im Fahrverhalten und somit auch in den Wirkungen einer SBA zu erwarten. Auch unabhängig davon stellt in der Praxis die Qualitätssicherung der komplexen automatisierten Steuerung einer SBA und die hierbei erforderliche Bewertung von Verbesserungsmaßnahmen eine große Herausforderung dar. Die mikroskopische Verkehrsflusssimulation bietet Potenziale, um Wirkungen kollektiver Verkehrsbeeinflussung zu untersuchen und Veränderungen am Verkehrssystem a-priori zu bewerten. Jedoch wird mikroskopische Verkehrsflusssimulation bislang kaum in Untersuchungen zu SBA eingesetzt. Dies ist unter anderem auf die Vielfalt zu berücksichtigender Situationen und Einflüsse auf das Fahrverhalten zurückzuführen: Anzeigezustände der SBA können sich in kurzen Zyklen ändern und zugrunde liegende Beeinflussungsstrategien sich überlagern; zugleich wirken sich auch die Verkehrs- und Wetterbedingungen auf das Fahrverhalten aus. Bislang ist kein Modellierungsansatz bekannt, um derart vielfältige Einflüsse auf das Fahrverhalten in der mikroskopischen Verkehrsflusssimulation zu berücksichtigen. Vor diesem Hintergrund wurde im Rahmen dieser Arbeit ein neuartiges Verfahren entwickelt, das erstmals eine differenzierte Modellierung des Fahrverhaltens in der mikroskopischen Verkehrsflusssimulation in einem sich dynamisch verändernden Situationskontext ermöglicht. Hierbei werden ausgewählte Parameter fahrzeugbezogener Verhaltensmodelle während der Simulation nachgeführt. Verschiedene Einflussfaktoren, Verhaltenskenngrößen und Modellparameter wurden dabei als Zustandsknoten eines hybriden Bayesschen Netzes modelliert, das anhand empirischer Daten mehrerer realer SBA sowie verschiedener simulativer Untersuchungen kalibriert wurde. Die Eignung des Verfahrens konnte im Rahmen einer Validierung bestätigt werden. In einem Forschungsprojekt im Auftrag der Bundesanstalt für Straßenwesen (BASt) wurde das Verfahren pilothaft zur Untersuchung der Einflüsse automatisierten Fahrens auf SBA eingesetzt.

No description available.