O rápido crescimento das regiões urbanas tem impacto significativo nos sistemas de tráfego e transportes. Políticas de gerenciamento e estratégias de planejamento alternativas são claramente necessárias para o tratamento da capacidade limitada, e cada vez mais deficitária, das redes viárias. O conceito de Sistemas Inteligentes de Transportes (ITS) surge neste cenário; mais do que procurar aumentar a capacidade por meio de modificações físicas na infraestrutura, sua premissa baseia-se na utilização de tecnologias avançadas de comunicação e computação para melhor gerir os recursos de tráfego e transportes atuais. Influenciar o padrão do comportamento dos usuários é um desafio que tem estimulado muita pesquisa na área de ITS, onde fatores humanos passam a ter grande importância na modelagem, simulação e avaliação dessa abordagem inovadora. Este trabalho tem como foco a utilização de Sistemas Multiagentes (MAS) na representação dos sistemas de tráfego e transporte, com base nas novasmedidas de desempenho impostas pelas tecnologias ITS. As características de agentes têm grande potencial para representar componentes geográfica e funcionalmente distribuídos, como a maioria dos elementos no domínio da aplicação. Uma arquitetura BDI (beliefs, desires, intentions) é apresentada como alternativa a modelos tradicionais, usados para representar o comportamento do motorista em simulação microscópica, considerando-se a representação explícita dos estados mentais dos usuários. Os conceitos básicos de ITS e MAS são apresentados, assim como exemplos de aplicações relacionados com o tema do trabalho. Esta foi a motivação para a extensão de um simulador microscópico existente, no sentido de incorporar as características dos MAS para melhorar a representação dos motoristas. Assim, a demanda é gerada a partir de uma população de agentes, resultando da decisão sobre a rota e o tempo de partida ao longo de vários dias. O modelo estendido, que passa a suportar a interação de motoristas BDI, foi efetivamente implementado e foram executados diferentes experimentos para testar a abordagem em cenários de tráfego urbano. MAS permite uma abordagem direcionada a processos que facilita a construção de representações modulares, robustas, e extensíveis, características pouco presentes em abordagens voltadas ao resultado. Suas premissas de abstração permitem uma associação direta entre modelo e implementação. Incerteza e variabilidade são assim tratadas de maneira mais intuitiva, uma vez que arquiteturas cognitivas permitem uma fácil representação do comportamento humano na estrutura do motorista. Desta forma, MAS estende a simulação microscópica de tráfego no sentido de melhor representar a complexidade inerente às tecnologias ITS. / 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.

O rápido crescimento das regiões urbanas tem impacto significativo nos sistemas de tráfego e transportes. Políticas de gerenciamento e estratégias de planejamento alternativas são claramente necessárias para o tratamento da capacidade limitada, e cada vez mais deficitária, das redes viárias. O conceito de Sistemas Inteligentes de Transportes (ITS) surge neste cenário; mais do que procurar aumentar a capacidade por meio de modificações físicas na infraestrutura, sua premissa baseia-se na utilização de tecnologias avançadas de comunicação e computação para melhor gerir os recursos de tráfego e transportes atuais. Influenciar o padrão do comportamento dos usuários é um desafio que tem estimulado muita pesquisa na área de ITS, onde fatores humanos passam a ter grande importância na modelagem, simulação e avaliação dessa abordagem inovadora. Este trabalho tem como foco a utilização de Sistemas Multiagentes (MAS) na representação dos sistemas de tráfego e transporte, com base nas novasmedidas de desempenho impostas pelas tecnologias ITS. As características de agentes têm grande potencial para representar componentes geográfica e funcionalmente distribuídos, como a maioria dos elementos no domínio da aplicação. Uma arquitetura BDI (beliefs, desires, intentions) é apresentada como alternativa a modelos tradicionais, usados para representar o comportamento do motorista em simulação microscópica, considerando-se a representação explícita dos estados mentais dos usuários. Os conceitos básicos de ITS e MAS são apresentados, assim como exemplos de aplicações relacionados com o tema do trabalho. Esta foi a motivação para a extensão de um simulador microscópico existente, no sentido de incorporar as características dos MAS para melhorar a representação dos motoristas. Assim, a demanda é gerada a partir de uma população de agentes, resultando da decisão sobre a rota e o tempo de partida ao longo de vários dias. O modelo estendido, que passa a suportar a interação de motoristas BDI, foi efetivamente implementado e foram executados diferentes experimentos para testar a abordagem em cenários de tráfego urbano. MAS permite uma abordagem direcionada a processos que facilita a construção de representações modulares, robustas, e extensíveis, características pouco presentes em abordagens voltadas ao resultado. Suas premissas de abstração permitem uma associação direta entre modelo e implementação. Incerteza e variabilidade são assim tratadas de maneira mais intuitiva, uma vez que arquiteturas cognitivas permitem uma fácil representação do comportamento humano na estrutura do motorista. Desta forma, MAS estende a simulação microscópica de tráfego no sentido de melhor representar a complexidade inerente às tecnologias ITS. / 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.

When further demands are placed on emissions and performance of cars, trucks and busses, the vehicle manufacturers are looking to have cheap ways to evaluate their products for specific customers' needs. Using simulation tools to quickly compare use cases instead of manually recording data is a possible way forward. However, existing traffic simulation tools do not provide enough detail in each vehicle for the driving to represent real life driving patterns with regards to road features. For the purpose of this thesis data has been recorded by having different people drive a specific route featuring highway driving, traffic lights and many curves. Using this data, models have then been estimated that describe how human drivers adjust their speed through curves, how long braking distances typically are with respect to the driving speed, and the varying deceleration during braking sequences. An additional model has also been created that produces a speed variation when driving on highways. In the end all models are implemented in Matlab using a traffic control interface to interact with the traffic simulation tool SUMO. The results of this work are promising with the improved simulation being able to replicate the most significant characteristics seen from human drivers when approaching curves, traffic lights and intersections.

Cette thèse est consacrée à la conception et au développement d’une plateforme multi-agent, en réalité virtuelle, de pilotage de véhicules intelligents pour la simulation du comportement microscopique du trafic. D’abord, un système de simulation intelligent des véhicules en réalité virtuelle (VR-ISSV), basé sur les multi-agents, est proposé : c’est un système modulaire hiérarchique de modélisation et de simulation, comprenant une couche matérielle, réseau et système d’exploitation ; une couche de gestion de la visualisation ; une couche de multi-agents et une couche d’interface homme-machine. Ensuite, pour le modèle d’agent du véhicule intelligent, un paradigme de conception décentralisée est utilisé basé sur l’approche multi-contrôleurs, où le comportement du suivi des véhicules et le comportement du dépassement des véhicules sont réalisées par coordination entre multi-contrôleurs. L’agent d’environnement est construit en tenant compte de l’interaction entre les véhicules et l’environnement naturel synthétique. Un système d’information géographique (GIS) est par ailleurs utilisé afin de définir l’agent d’environnement. Enfin, pour assurer la sécurité dans les manœuvres microscopiques du trafic, plusieurs contrôleurs du véhicule intelligent, adaptés à l’environnement complexe, sont considérés. Les contrôleurs, basés sur la logique floue, sont proposés pour envoyer les commandes appropriées aux actionneurs du véhicule - volant de direction, accélérateur, frein... Les modèles de comportement microscopique du trafic basé sur l’agent de véhicule intelligent sont étudiés considérant différents scénarios et l’environnement / This PhD thesis is dedicated to the modeling and simulation of microscopic traffic behavior in virtual reality system, with the intent of providing a new approach to effectively ensure traffic safety. At first, Virtual Reality Intelligent Simulation System of Vehicles (VR-ISSV), based on multi-agent, is proposed to simulate the intelligent microscopic traffic, which is a hierarchical modular modeling and simulation system consisting of hardware, network and operating system layers, visualization management layer, multi-agent layer, human-machine interface layer. The multi-agent layer includes entity agents (intelligent vehicle agents and around vehicle agents), service agent and environment agent. Second, for the intelligent vehicle agent model, a decentralized design paradigm is used for developing the multi-controller based intelligent vehicle, whereby the car following behavior and the overtaking behavior could be realized by the coordination of the multi-controller. The environment agent is constructed based on the conception of Synthetic Natural Environment (SNE), taking into account the interaction between the vehicles and the natural environment. Geographic Information System (GIS) is used to establish environment agent. Finally, to ensure the safety in microscopic traffic maneuver, the intelligent vehicle controllers adapting to complex environment are considered. Fuzzy logic based controllers are designed for sending the appropriate outputs to the vehicle’s actuators – the steering wheel and the throttle/brake pedals. Microscopic traffic behavior models based on the intelligent vehicle agent involving environment are studied

One of the most significant urban transport problems is traffic congestion. All major cities both in developed and developing countries are facing the problem due to increasing travel demand caused by increasing urbanization and the attendant economic and population growth. Recognizing the growing burden of traffic congestion, community leaders and transportation planners in Addis Ababa are still actively promoting large-scale road constructions to alleviate traffic congestion. Although Intelligent Transportation Systems(ITS) applications seem to have the potential to improve signalization performance, highly congested intersections in Addis Ababa are still controlled by a timed signal and manual operation. Moreover, these pre-timed signal controls are functioning sub-optimally as they are not being regularly monitored and updated to cope with varying traffic demands. Even though the benefits are well known theoretically, at the time of writing of this thesis, Adaptive Traffic Signal Controllers (ATSC) haven’t been deployed in Ethiopia and no research has been conducted to demonstrate and quantify their effectiveness. This master’s research thesis, therefore, intends to fill the identified gap, by undertaking a microscopic traffic simulation investigation, to evaluate the benefits of adopting a Traffic-responsive Urban Control (TUC) strategy and optimizing traffic signal timings. For the purpose of this study, an oversaturated three-intersection test corridor located in the heart of Addis Ababa city is modeled in VISSIM using real-world traffic data. After validating the calibrated model, the corridor was evaluated with the existing pre-timed, TRANSYT optimized pre-timed plan and TUC strategy. Multiple simulation runs were then made for each scenario alternatives and various measures of effectiveness were considered in the evaluation process. Simulation evaluation has demonstrated an average delay reduction of 24.17% when the existing pre-timed alternative is compared to TRANSYT optimized plan and 35% when compared to the TUC strategy. Overall evaluation results indicate that deploying the TUC strategy and optimizing the aging pre-timed signal plans exhibits a significant flow improvement. It is expected that the result of the thesis work will be an input for future comprehensive policy development processes.

Microscopic traffic simulation has become an important tool to investigate traffic efficiency and road safety. In order to produce meaningful results, incorporated driver behaviour models need to be carefully calibrated to represent real world conditions. In addition to macroscopic relationships such as the speed-density diagram, they should also adequately represent the average risk of accidents occurring on the road. In this thesis, I present a two stage computationally feasible multi-objective calibration process. The first stage performs a parameter sensitivity analysis to select only parameters with considerable effect on the respective objective functions to keep the computational complexity of the calibration at a manageable level. The second stage employs a multi-objective genetic algorithm that produces a front of Pareto optimal solutions with respect to the objective functions. Compared to traditional methods which focus on only one objective while sacrificing accuracy of the other, my method achieves a high degree of realism for both traffic flow and average risk. / Mikroskopisk trafiksimulering har blivit ett viktigt verktyg för att undersöka trafik effektivitet och trafiksäkerhet. För att producera meningsfulla resultat måste inbyggda drivrutinsbeteendemodeller noggrant kalibreras för att representera verkliga förhållanden i världen. Förutom makroskopiska relationer, såsom hastighetsdensitetsdiagrammet, bör de också på ett adekvat sätt representera den genomsnittliga risken för olyckor som uppträder på vägen. I denna avhandling presenterar jag en tvåstegs beräkningsberättigbar mångsidig kalibreringsprocess. Det första steget utför en parameterkänslighetsanalysför att bara välja parametrar med stor effekt på respektive objektiv funktioner för att hålla kalibrerings komplexiteten på en hanterbar nivå. Det andra steget använder en mångriktig genetisk algoritm som ger framsidan av Pareto optimala lösningar med hänsyn till objektivfunktionerna. Jämfört med traditionella metoder som fokuserar på endast ett mål, samtidigt som man offrar den andra, ger min metod en hög grad av realism för både trafikflöde och genomsnittlig risk.

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>

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.

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.