Automated shuttles are designed to provide a clean transportation and improve access to areas such as where travelers have to walk long distances to/from bus stops. The introduction of automated shuttles in the road network might affect the safety of pedestrians and cyclists as well as traffic performance of motorized vehicles. Several demonstration trials are being conducted to study how automated shuttles operate in real traffic conditions, but they are limited to few vehicles and evaluations of traffic effects at higher penetration rates are not possible. Traffic simulation is a tool that can be used to study effects on traffic performances at different penetration rates of e.g., automated shuttles. However, automated shuttles have not yet been modeled, calibrated, and validated in microscopic traffic simulation tools. Therefore, the objective of this thesis is to model, calibrate and validate automated shuttle’s behavior using the simulation tool SUMO and data collected from the demonstration trial on the area of campus Valla Linköping University, Sweden. The pilot study consists of two automated shuttles, and they operate on a 2.1 km fixed route. The collected data by one of the automated shuttles is analyzed with a focus on the free driving behavior. The analysis shows that the automated shuttle has different maximum operation speeds at different locations and defining one value for the maximum speed when setting up the simulation is not enough. Therefore, virtual speed limits are derived by mimicking the maximum operation speed of the shuttle from the data and used to define segment specific speed limits in the simulation. Additionally, the data is used to calibrate the acceleration and deceleration parameters. The Krauss and the IDM car-following models have been investigated by calibrating the acceleration and deceleration parameters for the free driving situation. The results indicate that both the Krauss and IDM car-following models follows the general trend of the speed and acceleration profiles. The speed profiles produced with the IDM model have smoother profiles at the start and end of acceleration and deceleration phases while in Krauss model the transition of the speed change is more direct and there are in principle no delays for reaction. Although the IDM model performs slightly better for the free driving situation, it can be of interest to consider both models for the calibration of interactions with other roads users since both models are able to capture the general trend of the speed and acceleration profiles. / <p>Examensarbetet är utfört vid Institutionen för teknik och naturvetenskap (ITN) vid Tekniska fakulteten, Linköpings universitet</p>

Vehicle velocity distributions are of utmost relevance for the efficiency, safety, and sustainability of road traffic. Yet, due to technical limitations, they are often empirically analyzed using spatiotemporal averages. Here, we instead study a novel set of microscopic traffic data from Dresden comprising 346 million data points with a resolution of one vehicle from 145 detector sites with a particular focus on extreme events and distribution tails. By fitting q-exponential and Generalized Extreme Value distributions to the right flank of the empirical velocity distributions, we establish that their tails universally exhibit a power-law behavior with similar decay exponents. We also find that q-exponentials are best suitable to model the vast extent to which speed limit violations in the data occur. Furthermore, combining velocity and time headway distributions, we obtain estimates for free flow velocities that always exceed average velocities and sometimes even significantly exceed speed limits. Likewise, congestion effects are found to play a very minor, almost negligible role in traffic flow at the detector sites. These results provide insights into the current state of traffic in Dresden, hinting toward potentially necessary policy amendments regarding road design, speed limits, and speeding prosecution. They also reveal the potentials and limitations of the data set at hand and thereby lay the groundwork for further, more detailed traffic analyses.

No description available.

This dissertation seeks to advance the modeling of network flows over time for the purposes of improving evacuation planning. The devastation created by Hurricanes Katrina and Rita along the Gulf Coast of the United States in 2005 have recently emphasized the need to improve evacuation modeling and planning. The lessons learned from these events, and similar past emergencies, have highlighted the problem of congestion on the interstate and freeways during an evacuation. The intent of this research is to develop evacuation demand management strategies that can reduce congestion, delay, and ultimately save lives during regional evacuations. The primary focus of this research will concern short-notice evacuations, such as hurricane evacuations, conducted by automobiles. Additionally, this dissertation addresses some traffic flow and optimization deficiencies concerning the modeling of congested network flows. This dissertation is a compilation of three manuscripts. Chapters 3 and 4 examine modeling network flows over time with congestion. Chapter 3 demonstrates the effects of congestion on flows using a microscopic traffic simulation software package, INTEGRATION. The flow reductions from the simulation are consistent with those found in several empirical studies. The simulation allows for the examination of the various contributing factors to the flow reductions caused by congestion, including level of demand, roadway geometry and capacity, vehicle dynamics, traffic stream composition, and lane changing behavior. Chapter 4 addresses some of the modeling and implementation issues encountered in evacuation planning and presents an improved modeling framework that reduces network flows due to congestion. The framework uses a cell-based linear traffic flow model within a mixed integer linear program (MILP) to model network flows over time in order to produce sets of decisions for use within an evacuation plan. The traffic flow model is an improvement based upon the Cell Transmission Model (CTM) introduced in Daganzo (1994) and Daganzo (1995) by reducing network flows due to congestion. The flow reductions are calibrated according to the traffic simulation studies conducted in Chapter 3. The MILP is based upon the linear program developed in Ziliaskopoulos (2000); however, it eliminates the "traffic holding" phenomenon where it cannot be implemented realistically within a transportation network. This phenomenon is commonly found in mathematical programs used for dynamic traffic assignment where the traffic is unrealistically held back in order to determine an optimum solution. Lastly, we propose additional constraints for the MILP that improve the computational performance by over 90%. These constraints exploit the relation of the binary variables based on the network topology. Chapter 5 applies the improved modeling framework developed in Chapter 4 to implement a demand management strategy called group-level staging -- the practice of evacuating different groups of evacuees at different times in order to reduce the evacuation duration. This chapter evaluates the benefits of group-level staging, as compared to the current practice of simultaneous evacuation, and explores the behavior of the modeling framework under various objective functions. / Ph. D.

Traffic simulation is a safe and efficient tool to investigate infrastructural changes as well as traffic conditions. This master thesis aims to analyse a microscopic traffic simulation method for evaluation of bus terminal capacity. The evaluation is performed by investigating a case study of the bus terminal at Norrköping travel centre. The analysed method, referred to as terminal logic in the thesis, uses a combination of time based and event based simulation. Through the combination of time and event, it is possible to capture all movements within the terminal for individual vehicles. The simulation model is built in the software Vissim. A new travel centre for Norrköping is under development. Among the reasons for a new travel centre is the railway project Ostlänken in the eastern part of Sweden. An evaluation of the bus terminal is interesting due to a suspicion of overcapacity and the opportunity of redesigning. To investigate both the terminal capacity and the terminal logic, three scenarios were implemented. Scenario 1: Current design and frequency Scenario 2: Current design with higher frequency Scenario 3: Decreased number of bus stops with current frequency The results from the scenarios confirm the assumption of overcapacity. The capacity was evaluated based on several different measures, all indicating a low utilization. Even so, the utilization was uneven over time and congestion could still occur when several buses departed at the same time. This was also seen when studying the simulation, which showed congestions when several buses departed at the same time. The case study established the terminal logic to be useful when evaluating capacity at bus terminals. It provides a good understanding of how the terminal operates and captures the movements. However, it was time-consuming to adjust the logic to the studied terminal. This is a disadvantage when investigating more than one alternative. The thesis resulted in two main conclusions. Firstly, a more optimised planning of the buses at Norrköping bus terminal would probably be achievable and lead to less congestions at the exits. Secondly, the terminal logic is a good method to use when evaluating bus terminals but it is not straight forward to implement.

No description available.

In this thesis, multiple on-road vehicle tracking problem is explored, with greater consideration of road constraints and interactions between vehicles. A comprehensive method for tracking multiple on-road vehicles is proposed by making use of domain knowledge of on-road vehicle motion. Starting with raw measurements provided by sensors, bias correction methods for sensors commonly used in vehicle tracking are briefly introduced and a fast but effective bias correction method for airborne video sensor is proposed. In the proposed method, by assuming errors in sensor parameter measurements are close to zero, the bias is separately addressed in converted measurements of target position by a linear term of errors in sensor parameter measurements. Based on this model, the bias is efficiently estimated by addressing it while tracking or using measurements of targets that are observed by multiple airborne video sensors simultaneously. The proposed method is compared with other airborne video bias correction methods through simulations. The numerical results demonstrate the effectiveness of the proposed method for correcting bias as well as its high computational efficiency. Then, a novel tracking algorithm that utilizes domain knowledge of on-road vehicle motion, i.e., road-map information and interactions among vehicles, by integrating a car-following model into a road coordinate system, is proposed for tracking multiple vehicles on single-lane roads. This algorithm is extended for tracking multiple vehicles on multi-lane roads: The road coordinate system is extended to two-dimension to express lanes on roads and a lane-changing model is integrated for modeling lane-changing behavior of vehicles. Since the longitudinal and lateral motions are mutually dependent, the longitudinal and lateral states of vehicles are estimated sequentially in a recursive manner. Two estimation strategies are proposed: a) The unscented Kalman filter combined with the multiple hypothesis tracking framework to estimate longitudinal and lateral states of vehicles, respectively. b) A unified particle filter framework with a specifically designed computationally-efficient joint sampling method to estimate longitudinal and lateral states of vehicles jointly. Both of two estimation methods can handle unknown parameters in motion models. A posterior Cramer-Rao lower bound is derived for quantifying achievable estimation accuracy in both single-lane and multi-lane cases, respectively. Numerical results show that the proposed algorithms achieve better track accuracy and consistency than conventional multi-vehicle tracking algorithms, which assumes that vehicles move independently of one another. / Thesis / Doctor of Philosophy (PhD)

The dissertation studies traffic dispersion modeling in four parts. In the first part, the dissertation focuses on the Robertson platoon dispersion model which is the most widely used platoon dispersion model. The dissertation demonstrates the importance of the Yu and Van Aerde calibration procedure for the commonly accepted Robertson platoon dispersion model, which is implemented in the TRANSYT software. It demonstrates that the formulation results in an estimated downstream cyclic profile with a margin of error that increases as the size of the time step increases. In an attempt to address this shortcoming, the thesis proposes the use of three enhanced geometric distribution formulations that explicitly account for the time-step size within the modeling process. The proposed models are validated against field and simulated data. The second part focuses on implementation of the Robertson model inside the popular TRANSYT software. The dissertation first shows the importance of calibrating the recurrence platoon dispersion model. It is then demonstrated that the value of the travel time factor &#946; is critical in estimating appropriate signal-timing plans. Alternatively, the dissertation demonstrates that the value of the platoon dispersion factor &#945; does not significantly affect the estimated downstream cyclic flow profile; therefore, a unique value of &#945; provides the necessary precision. Unfortunately, the TRANSYT software only allows the user to calibrate the platoon dispersion factor but does not allow the user to calibrate the travel time factor. In an attempt to address this shortcoming, the document proposes a formulation using the basic properties of the recurrence relationship to enable the user to control the travel time factor indirectly by altering the link average travel time. In the third part of the dissertation, a more general study of platoon dispersion models is presented. The main objective of this part is to evaluate the effect of the underlying travel time distribution on the accuracy and efficiency of platoon dispersion models, through qualitative and quantitative analyses. Since the data used in this study are generated by the INTEGRATION microsimulator, the document first describes the ability of INTEGRATION in generating realistic traffic dispersion effects. The dissertation then uses the microsimulator generated data to evaluate the prediction precision and performance of seven different platoon dispersion models, as well as the effect of different traffic control characteristics on the important efficiency measures used in traffic engineering. The results demonstrate that in terms of prediction accuracy the resulting flow profiles from all the models are very close, and only the geometric distribution of travel times gives higher fit error than others. It also indicates that for all the models the prediction accuracy declines as the travel distance increases, with the flow profiles approaching normality. In terms of efficiency, the travel time distribution has minimum effect on the offset selection and resulting delay. The study also demonstrates that the efficiency is affected more by the distance of travel than the travel time distribution. Finally, in the fourth part of the dissertation, platoon dispersion is studied from a microscopic standpoint. From this perspective traffic dispersion is modeled as differences in desired speed selection, or speed variability. The dissertation first investigates the corresponding steady-state behavior of the car-following models used in popular commercially available traffic microsimulation software and classifies them based on their steady-state characteristics in the uncongested regime. It is illustrated that with one exception, INTEGRATION which uses the Van Aerde car-following model, all the software assume that the desired speed in the uncongested regime is insensitive to traffic conditions. The document then addresses the effect of speed variability on the steady-state characteristics of the car-following models. It is shown that speed variability has significant influence on the speed-at-capacity and alters the behavior of the model in the uncongested regime. A method is proposed to effectively consider the influence of speed variability in the calibration process in order to control the steady-state behavior of the model. Finally, the effectiveness and validity of the proposed method is demonstrated through an example application. / Ph. D.

Ο ρόλος των Ευφυών Συστημάτων Μεταφορών είναι η βελτίωση της οδικής ασφάλειας, μέσω της έγκαιρης ανίχνευσης συμβάντων και της αποτελεσματικής διαχείρισης της κυκλοφορίας. Στο πλαίσιο αυτό, η έρευνα αυτή εστιάζει στην ανάλυση της σχέσης μεταξύ ενός καθημερινού σοβαρού φαινομένου της κυκλοφορίας, όπως το κυκλοφοριακό πλήγμα (shockwave) και τα οχήματα που κινούνται σε σχηματισμό cluster, μέσω του κυκλοφοριακού πλήγματος. Για να σχηματιστεί ένα cluster απαιτείται δύο ή περισσότερα οχήματα να περιλαμβάνονται στην ακολουθία οχημάτων είτε λόγω της εγγύτητάς τους είτε λόγω της σχετικής τους απόστασής από άλλα οχήματα. Ξεκινώντας με βίντεο κυκλοφοριακής στον αυτοκινητόδρομο I-94, Minnesota, USA, οι τροχιές των οχημάτων εξήχθησαν. Τα αποτελέσματα χρησιμοποιήθηκαν στη συνέχεια προκειμένου να καθοριστούν μεταβλητές όπως χρονοαπόσταση, ταχύτητα, επιτάχυνση για τρεις ομάδες οχημάτων, το Cluster, η ομάδα Πριν το Cluster και η ομάδα Μετά το Cluster. Η σχέση μεταξύ αυτών των ομάδων μελετήθηκε και αποτυπώθηκε σε γραμμικές συναρτήσεις με πολλαπλές ανεξάρτητες μεταβλητές. / The role of Intellignet Transportation Systems is to enhance traffic safety, through timely detection of incidents and effective traffic management. In this framework, this research focuses into analyzing the relationship between a daily severe traffic phenomenon such as shockwave and vehicles which move in cluster formation through the shockwave. For a cluster to be formed it is required for two or more vehicles to be included either because of their closeness or because of their relative distance from other vehicles on the link. Starting with video recordings of traffic flow on I-94, Minnesota, USA, vehicles trajectories were extracted. The results were then used in order to define variables such as vehicles space and time headway, velocity, acceleration for three groups of vehicles; the Cluster, the Before Cluster group and the After Cluster group. The relationship between these groups was studied and was modeled in linear functions with multiple variables.

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.