Report (M.S.)--Virginia Polytechnic Institute and State University. M.S. 1992. / Vita. Abstract. Includes bibliographical references (leaves 60-64). Also available via the Internet.

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Research on connected vehicles (CV) has attracted attention in the last decade due to numerous potential applications and challenges related to exchange of information between the vehicles (and infrastructure). Most of the relevant studies focus on these applications and challenges with the help of novel or existing simulation frameworks. The simulation framework often contains the mobility and communication components, and these components are frequently simplified. In this study, the authors aim to provide the detailed information for developing a fully V2X capable infrastructure within the lab environment. The physical components of the proposed infrastructure include: (i) userdriven Driving Simulator (DS) with the embedded micro-simulation tool (MS); (ii) external traffic signal controller (TSC); (iii) Road Side Unit (RSU) and omnidirectional antenna attached to RSU; (iv) On-Board Unit (OBU) that is integrated within DS‘s cockpit. The proposed framework can be used for advanced applications in the context of connected vehicles. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

Macroscopic fundamental diagram is the concept of the highest importance in traffic flow theory used for development of network-wide control strategies. Previous studies showed that so called Arterial Fundamental Diagrams (AFDs) properly depict relationships between major macroscopic traffic variables on urban arterials. Most of these studies used detector’s occupancy as a surrogate measure to represent traffic density. Nevertheless, detector’s occupancy is not very often present in the field data. More frequently, field data from arterial streets provide performance metrics measured at the stop lines of traffic signals, which represent a hybrid of flow and occupancy. When such performance measures are used in lieu of density, the outcomes of the relationships between macroscopic fundamental variables can be confusing. This study investigates appropriateness of using degree of saturation, as a representative surrogate measure of traffic density, obtained from an adaptive traffic control system that utilizes stop-line detectors, for development of AFDs. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2016. / FAU Electronic Theses and Dissertations Collection

With the remarkable increase in the population and number of vehicles, traffic has become a severe problem in most metropolitan areas. Traffic congestion has imposed tight constraints on economic growth, national security, and mobility of riders and goods. The open-mode integrated transportation system (OMITS) has been designed to improve the traffic condition of roadways by increasing the ridership of vehicles and optimizing transportation modes through smart services integrating emerging information communication technologies, big data management, social networking, and transportation management. Even a modest reduction in the number of vehicles on roadways will lead to a considerable cost savings in terms of time and money. Additionally the reduction in traffic jams will lead to a significant decrease in both gasoline consumption and greenhouse gas emissions. As a result, novel transportation management is critical to reduce vehicle mileage in the peak time of the road network. The OMITS was proposed to enhance transportation services in respect to the following three aspects: optimization of the transportation modes by multimodal traveling assignment, dynamic routing and ridesharing service with advanced traveler information systems, and interactive user interface for social networking and traveling information. Therefore, the OMITS encompasses a broad range of advanced transportation research topics, say dynamic trip- match, transportation-mode optimization, traffic prediction, dynamic routing, and social network- based carpooling. This dissertation will focus on a kernel part of the OMITS, namely traffic simulation and prediction based on data containing the distribution of vehicles and the road network configuration. A microscopic traffic simulation framework has been developed to take into account various traffic phenomena, such as traffic jams resulting from bottlenecking, incidents, and traffic flow shock waves. Four fundamental contributions of the present study are summarized as follows: Firstly, an accurate and robust vehicle trajectory data collection method based on image data of unmanned aerial vehicle (UAV) has been presented, which can be used to rapidly and accurately acquire the real-time traffic conditions of the region of interest. Historically, a lack in the availability of trajectory data has posed a significant obstacle to the enhancement of microscopic simulation models. To overcome this obstacle, a UAV based vehicle trajectory data collection algorithm has been developed. This method extracts vehicle trajectory data from the UAV’s video at different altitudes with different view scopes. Compared with traditional methods, the present data collection algorithm incorporates many unique features to customize the vehicle and traffic flow, through which vehicle detection and tracking system accuracy can be considerably increased. Secondly, an open mechanics-based acceleration model has been presented to simulate the longitudinal motion of vehicles, in which five general factors—namely the subject vehicle’s speed and acceleration sensitivity, safety consideration, relative speed sensitivity and gap reducing desire—have been identified to describe drivers’ preferences and the interactions between vehicles. Inspired by the similarity between vehicle interactions and particle interactions, a mechanical system with force elements has been introduced to quantify the vehicle’s acceleration. Accordingly, each of the aforementioned five factors are assumed to function as an individual trigger to alter each vehicle’s speed. Based on Newton’s second law of motion, the subject vehicle’s longitudinal behavior can be simulated by the present open mechanics-based acceleration model. By introducing feeling gap, multilane acceleration behavior is included in the presented model. The simulation results fit realistic conditions for the traffic flow and the road capacity very well, where traffic shockwaves can be observed for a certain range of the traffic density. This model can be extended to more general scenarios if other factors can be recognized and introduced into the modeling framework. Thirdly, a driver decision-based lane change execution model has been developed to describe a vehicle’s lane change execution process, which includes two steps, i.e. driver’s lane selection and lane change execution. Currently, most lane change models focus on the driver’s lane selection, and overlook the driver’s behavior during a process of lane change execution which plays a significant role in the simulation of traffic flow characteristics. In this model, a lane change execution is analyzed as a driver’s decision-making process, which consists of desire point setting, priority decision-making, corresponding actions and achievement of consensus analysis. Compared with the traditional lane change execution models, the present model describes a realistic lane change process, and it provides more accurate and detailed simulation results in the microscopic traffic simulation. Based on the presented open mechanics-based acceleration model and the driver decision- based lane change execution model, a reverse lane change model has further been developed to simulate some complex traffic situations such as reverse lane change process at a two-way-two- lane road section where one lane is blocked by a traffic incident. Based on this reverse lane change model, information on the average waiting time and road capability can be obtained. The simulation results show that the present model is able to reflect real driver behavior and the corresponding traffic phenomenon during a reverse lane change process Through a homogenization process of the microscopic vehicle motion, we can obtain the macroscopic traffic flow of the roadway network within certain time and spatial ranges, which will be integrated into the OMITS system for traffic prediction. The validation of the models through future OMITS operations will also enable them to be high fidelity models in future driverless technologies and autonomous vehicles.

Nas últimas décadas, fatores como maior facilidade de crédito e aumento da renda média dos brasileiros motivaram o crescimento das vendas de veículos novos. Com isso, a quantidade de veículos em circulação também aumentou significativamente. Como consequência desse crescimento observa-se o aumento de congestionamento nas grandes cidades, maior número de acidentes de trânsito com vítimas fatais, dentre outros problemas. Neste contexto surge o Sistema de Transporte Inteligente (ITS), que oferece serviços e produtos que utilizam a comunicação de dados no intuito de melhorar o sistema de transporte. Neste sistema, os veículos, os equipamentos móveis e a infraestrutura nas proximidades das vias de tráfego podem transferir dados entre si, formando assim uma rede de comunicação de dados denominada VANET. Esta comunicação permite a implantação de uma série de serviços e soluções de segurança, informação e entretenimento no trânsito. Para gerenciar o roteamento de dados nestas redes de topologia altamente dinâmica, uma série de algoritmos baseados em ACO (Ant Colony Optmization) vem sendo criados. Estes algoritmos são baseados no comportamento das formigas ao saírem de seus ninhos em busca de alimento, as quais tendem a escolher o caminho mais curto entre ninho e alimento. No entanto, observa-se que na literatura não há um padrão para comparação de desempenho destes algoritmos heurísticos, sendo comumente comparados entre si ou com algoritmos de redes MANETs. Neste trabalho foi criado um benchmark com várias instâncias de roteamento multiobjetivo em redes VANETs que podem ser utilizadas para teste de outros algoritmos. Os simuladores de mobilidade e de rede foram configurados para que os cenários de simulação se aproximassem de redes VANETs reais. A área de simulação escolhida para cada cenário foi uma região localizada próxima ao centro da cidade de Curitiba/PR, na qual várias densidades de veículos foram distribuídas de duas formas distintas, uma aleatória e outra tendenciosa a obter maior fluxo nas grandes avenidas. Foram também aplicados o modelo de propagação three log distance sozinho e combinado com o modelo de desvanecimento de Nakagami. Em cada cenário, os veículos origem e destino foram mantidos fixos em lados opostos da área de simulação. Para cada instante da simulação foi aplicado o algoritmo Dijkstra para obter o menor caminho entre origem e destino para a transmissão de pacotes de dados. Um algoritmo de roteamento multiobjetivo baseado em ACO foi proposto e seus resultados foram comparados com o benchmark. Os caminhos encontrados pelo ACO apresentaram maiores números de saltos e, consequentemente, custos superiores aos encontrados pelo algoritmo de Dijkstra. Um benchmark com vários cenários foi criado. As simulações destes cenários mostraram a influência de diversos fatores na conectividade de uma rede VANET, como a densidade de veículos, suas localizações geográficas e modelo de propagação usado. Os resultados obtidos são promissores e apontam a importância na escolha dos modelos de simulação. Tais resultados incentivam o uso de algoritmos heurísticos para roteamento de dados em redes VANET. / In the last decades, we have witnessed an increasing sale of new cars, driven by extensive credit availability and the growth of average income. Hence, the number of vehicles on the roads has increased. Due to this high density of vehicles, the traffic jams as well as fatal accidents are increasing. In order to reduce such factors, the Intelligent Transportation Systems (ITS) aroused, offering connected services and products related to entertainment and road safety. In this system, vehicles, mobile equipments and the infrastructure in the neighborhood of the traffic ways can transfer data to each other, thus creating a network called VANET (Vehicular Ad-hoc Network). To optimize the packets routing in these dynamic networks, several Ant Colony Optmization (ACO) - based algorithms have been proposed. Such algorithms are inspired by the foraging behavior of ants, which are capable of finding the shortest paths from food sources to the nest. However, there are no performance evaluation standards in the recent literature. The algorithms are often compared to each other or with MANET’s algorithms. In this dissertation, a bench-mark of several routing instances for VANETs was created. These benchmarks can be used for testing routing algorithms. The mobility and network simulators were configured in order to create real-world VANET-like scenarios. The geographical area chosen for the scenarios was near to Curitiba downtown. Different vehicle densities were distributed in two way: purely random and biased in such a way that avenues receive higher vehicle flows. The three log-distance path loss model was applied to each scenario, sometimes combined with the Nakagami fading model. In each scenario the source and destination vehicles are fixed on opposite sides of the simulated area. For each simulation time step, the Dijkstra algorithm was run to find the shortest path data transmission between source and destination. A multiobjective ACO-based algorithm was proposed and compared with the Dijkstra algorithm. The paths found by ACO include higher number of hops than those found by the Dijkstra algorithm. A benchmark with several scenarios was created. The scenario’s simulations show the importance of several factors in the VANET connectivity, such as vehicle density, geographical location and propagation models. The results are promising and indicate the importance of choosing appropriated simulation models.

Nas últimas décadas, fatores como maior facilidade de crédito e aumento da renda média dos brasileiros motivaram o crescimento das vendas de veículos novos. Com isso, a quantidade de veículos em circulação também aumentou significativamente. Como consequência desse crescimento observa-se o aumento de congestionamento nas grandes cidades, maior número de acidentes de trânsito com vítimas fatais, dentre outros problemas. Neste contexto surge o Sistema de Transporte Inteligente (ITS), que oferece serviços e produtos que utilizam a comunicação de dados no intuito de melhorar o sistema de transporte. Neste sistema, os veículos, os equipamentos móveis e a infraestrutura nas proximidades das vias de tráfego podem transferir dados entre si, formando assim uma rede de comunicação de dados denominada VANET. Esta comunicação permite a implantação de uma série de serviços e soluções de segurança, informação e entretenimento no trânsito. Para gerenciar o roteamento de dados nestas redes de topologia altamente dinâmica, uma série de algoritmos baseados em ACO (Ant Colony Optmization) vem sendo criados. Estes algoritmos são baseados no comportamento das formigas ao saírem de seus ninhos em busca de alimento, as quais tendem a escolher o caminho mais curto entre ninho e alimento. No entanto, observa-se que na literatura não há um padrão para comparação de desempenho destes algoritmos heurísticos, sendo comumente comparados entre si ou com algoritmos de redes MANETs. Neste trabalho foi criado um benchmark com várias instâncias de roteamento multiobjetivo em redes VANETs que podem ser utilizadas para teste de outros algoritmos. Os simuladores de mobilidade e de rede foram configurados para que os cenários de simulação se aproximassem de redes VANETs reais. A área de simulação escolhida para cada cenário foi uma região localizada próxima ao centro da cidade de Curitiba/PR, na qual várias densidades de veículos foram distribuídas de duas formas distintas, uma aleatória e outra tendenciosa a obter maior fluxo nas grandes avenidas. Foram também aplicados o modelo de propagação three log distance sozinho e combinado com o modelo de desvanecimento de Nakagami. Em cada cenário, os veículos origem e destino foram mantidos fixos em lados opostos da área de simulação. Para cada instante da simulação foi aplicado o algoritmo Dijkstra para obter o menor caminho entre origem e destino para a transmissão de pacotes de dados. Um algoritmo de roteamento multiobjetivo baseado em ACO foi proposto e seus resultados foram comparados com o benchmark. Os caminhos encontrados pelo ACO apresentaram maiores números de saltos e, consequentemente, custos superiores aos encontrados pelo algoritmo de Dijkstra. Um benchmark com vários cenários foi criado. As simulações destes cenários mostraram a influência de diversos fatores na conectividade de uma rede VANET, como a densidade de veículos, suas localizações geográficas e modelo de propagação usado. Os resultados obtidos são promissores e apontam a importância na escolha dos modelos de simulação. Tais resultados incentivam o uso de algoritmos heurísticos para roteamento de dados em redes VANET. / In the last decades, we have witnessed an increasing sale of new cars, driven by extensive credit availability and the growth of average income. Hence, the number of vehicles on the roads has increased. Due to this high density of vehicles, the traffic jams as well as fatal accidents are increasing. In order to reduce such factors, the Intelligent Transportation Systems (ITS) aroused, offering connected services and products related to entertainment and road safety. In this system, vehicles, mobile equipments and the infrastructure in the neighborhood of the traffic ways can transfer data to each other, thus creating a network called VANET (Vehicular Ad-hoc Network). To optimize the packets routing in these dynamic networks, several Ant Colony Optmization (ACO) - based algorithms have been proposed. Such algorithms are inspired by the foraging behavior of ants, which are capable of finding the shortest paths from food sources to the nest. However, there are no performance evaluation standards in the recent literature. The algorithms are often compared to each other or with MANET’s algorithms. In this dissertation, a bench-mark of several routing instances for VANETs was created. These benchmarks can be used for testing routing algorithms. The mobility and network simulators were configured in order to create real-world VANET-like scenarios. The geographical area chosen for the scenarios was near to Curitiba downtown. Different vehicle densities were distributed in two way: purely random and biased in such a way that avenues receive higher vehicle flows. The three log-distance path loss model was applied to each scenario, sometimes combined with the Nakagami fading model. In each scenario the source and destination vehicles are fixed on opposite sides of the simulated area. For each simulation time step, the Dijkstra algorithm was run to find the shortest path data transmission between source and destination. A multiobjective ACO-based algorithm was proposed and compared with the Dijkstra algorithm. The paths found by ACO include higher number of hops than those found by the Dijkstra algorithm. A benchmark with several scenarios was created. The scenario’s simulations show the importance of several factors in the VANET connectivity, such as vehicle density, geographical location and propagation models. The results are promising and indicate the importance of choosing appropriated simulation models.