Intelligent Transportation Systems (ITS) have emerged to use different technologies to promote safety, convenience, and efficiency of transportation networks. Many applications of ITS depend on the availability of the real-time positioning of the vehicles in the network. In this research, the two open challenges in the field of vehicle localization for ITS are introduced and addressed. First, in order to have safe and efficient transportation systems, the locations of the vehicles need to be available everywhere in a network. Conventional localization techniques mostly rely on Global Positioning System (GPS) technology which cannot meet the accuracy requirements for all applications in all situations. This work advances the study of vehicle positioning in ITS by introducing an integrated positioning framework which uses several resources including GPS, vehicle-to-infrastructure and vehicle-to-vehicle communications, radio-frequency identification, and dead reckoning. These technologies are used to provide more reliable and accurate location information. The suggested framework fills the gap between the accuracy of the current vehicle localization techniques and the required one for many ITS applications. Second, different ITS applications have different localization accuracy and latency requirements. A smart positioning algorithm is proposed which enable us to change the positioning accuracy delivered by the algorithm based on different applications. The algorithm utilizes only the most effective resources to achieve the required accuracy, even if more resources are available. In this way, the complexity of the system and the running time decrease while the desired accuracy is obtained. The adjective Smart is selected because the algorithm smartly selects the most effective connection which has the most contribution to vehicle positioning when a connection needs to be added. On the other hand, when a connection should be removed, the algorithm smartly selects the least effective one which has the least contribution to the position estimation. This study also provides an overview about the positioning requirements for different ITS applications. A close-to-real-world scenario has been developed and simulated in MATLAB to evaluate the performance of the proposed algorithms. The simulation results show that the vehicle can acquire accurate location in different environments using the suggested Integrated framework. Moreover, the advantages of the proposed Smart algorithm in terms of accuracy and running time are presented through a series of comprehensive simulations. / Master of Science

When implementing an intelligent transportation system (ITS), stakeholders often overlook the importance of evaluating the system once it is in place. Determining the extent to which the objectives of an investment have been met is important to not only the agency involved, but also to other agencies, so that lessons are learned and mistakes are not repeated in future projects. An effective evaluation allows a transit provider to identify and address areas that could use improvement. Agencies implementing ITS investments often have different goals, needs, and concerns that they hope their project will address and consequently the development of a generic evaluation plan is difficult to develop. While it is recognized that the U.S. Department of Transportation has developed guidelines to aid agencies in evaluating such investments, this research is intended to complement these guidelines by assisting in the evaluation of a site specific ITS investment. It presents an evaluation framework and plan that provides a systematic method for assessing the potential impacts associated with the project by defining objectives, measures, analysis recommendations, and data requirements. The framework developed specifically addresses the ITS investment on the OmniLink local route deviation bus service in Prince William County, Virginia, but could be used as a basis for the evaluation of similar ITS investments. The OmniLink ITS investment includes an automatic vehicle location (AVL) system, mobile data terminals (MDTs), and computer-aided dispatch (CAD) technology. / Master of Science

Changeable Message Signs (CMS) are commonly utilized by transportation agencies to inform motorists of traffic, roadway, and environmental conditions. They may be used to provide information, such as delay and alternate route guidance, in the event of an incident, construction or a roadway closure. The effectiveness of CMS in managing freeway traffic, however, is a function of many factors including the number of CMS installations, the location of CMS, the messages displayed, varied traffic network characteristics, and drivers' response to incident conditions and CMS information. The objective of this thesis is to develop a CMS location planning model that can be used by transportation agencies to develop a CMS location plan that could achieve the largest long-term benefit to the system. This research is mainly motivated by the lack of systematic, robust and practical methods for locating CMS. State-of-practice methods rely mostly on the practitioner's experience and judgement. Other methods fail to incorporate reasonable driver behaviour models, consider time-varying demand, allow for computational efficiency on large networks, or consider the spatial variation of incidents on a traffic network. A new CMS location optimization model has been developed that is unique in both model realism and computational efficiency. The model incorporates several components to estimate incident delay, predict driver response, estimate network-wide benefit, and choose those CMS locations that would provide the most benefit. Deterministic queuing methods are used in conjunction with historic incident characteristics to approximate the delay impact of an incident with and without CMS. A discrete choice model is used to predict the rate at which drivers would switch from the incident route to a less congested alternative under CMS information. A network traffic assignment model is then incorporated in an attempt to estimate the resulting traffic induced by incidents. Genetic algorithms are utilized as an optimization technique to choose a set of CMS that would provide the most benefit. An extensive computational analysis was performed on both a hypothetical network and a segment of Highway 401 through Toronto. A sensitivity analysis was performed to test the model's response to parameter and data estimation errors. The model was found to be most sensitive to the diversion model parameters. The model produced reasonable results with locations selected upstream of major freeway interchange diversion points. Considering the additional components included in the proposed model, and its ability to consider more location schemes, the proposed model may be considered superior to previous CMS location models.

Changeable Message Signs (CMS) are commonly utilized by transportation agencies to inform motorists of traffic, roadway, and environmental conditions. They may be used to provide information, such as delay and alternate route guidance, in the event of an incident, construction or a roadway closure. The effectiveness of CMS in managing freeway traffic, however, is a function of many factors including the number of CMS installations, the location of CMS, the messages displayed, varied traffic network characteristics, and drivers' response to incident conditions and CMS information. The objective of this thesis is to develop a CMS location planning model that can be used by transportation agencies to develop a CMS location plan that could achieve the largest long-term benefit to the system. This research is mainly motivated by the lack of systematic, robust and practical methods for locating CMS. State-of-practice methods rely mostly on the practitioner's experience and judgement. Other methods fail to incorporate reasonable driver behaviour models, consider time-varying demand, allow for computational efficiency on large networks, or consider the spatial variation of incidents on a traffic network. A new CMS location optimization model has been developed that is unique in both model realism and computational efficiency. The model incorporates several components to estimate incident delay, predict driver response, estimate network-wide benefit, and choose those CMS locations that would provide the most benefit. Deterministic queuing methods are used in conjunction with historic incident characteristics to approximate the delay impact of an incident with and without CMS. A discrete choice model is used to predict the rate at which drivers would switch from the incident route to a less congested alternative under CMS information. A network traffic assignment model is then incorporated in an attempt to estimate the resulting traffic induced by incidents. Genetic algorithms are utilized as an optimization technique to choose a set of CMS that would provide the most benefit. An extensive computational analysis was performed on both a hypothetical network and a segment of Highway 401 through Toronto. A sensitivity analysis was performed to test the model's response to parameter and data estimation errors. The model was found to be most sensitive to the diversion model parameters. The model produced reasonable results with locations selected upstream of major freeway interchange diversion points. Considering the additional components included in the proposed model, and its ability to consider more location schemes, the proposed model may be considered superior to previous CMS location models.

Flow of traffic on freeways and limited access highways can be represented as a series of kinemetic waves. Solutions to these systems of equations become problematic under congested traffic flow conditions, and under complicated (real-world) networks. A simplified theory of kinematics waves was previously proposed. Simplifying elements includes translation of the problem to moving coordinate system, adoption of bi-linear speed-density relationships, and adoption of restrictive constraints at the on- and off-ramps. However, these simplifying assumptions preclude application of this technique to most practical situations. This research explores the limitations of the simplified theory of kinematic waves. First this research documents a relaxation of several key constraints. In the original theory, priority was given to on-ramp merging vehicles so that they can bypass any queue at the merge. This research proposes to relax this constraint using a capacity-based weighted fair queuing (CBWFQ) merge model. In the original theory, downstream queue affects upstream traffic as a whole and exiting traffic can always be able to leave as long as it gets to the diverge. This research proposes that this diverge constraint be replaced with a contribution-based weighted splitting (CBWS) diverge model. This research proposes a revised notation system, permitting the solution techniques to be extended to freeway networks with multiple freeways and their ramps. This research proposes a generalization to permit application of the revised theory to general transportation networks. A generalized CBWFQ merge model and a generalized CBWS diverge model are formulated to deal with merging and diverging traffic. Finally, this research presents computational procedure for solving the new system of equations. Comparisons of model predictions with field observations are conducted on GA 400 in Atlanta. Investigations into the performance of the proposed CBWFQ and CBWS models are conducted. Results are quite encouraging, quantitative measures suggest satisfactory accuracy with narrow confidence interval.

abstract: Unmanned aerial systems (UASs) have recently enabled novel applications such as passenger transport and package delivery, but are increasingly vulnerable to cyberattack and therefore difficult to certify. Legacy systems such as GPS provide these capabilities extremely well, but are sensitive to spoofing and hijacking. An alternative intelligent transport system (ITS) was developed that provides highly secure communications, positioning, and timing synchronization services to networks of cooperative RF users, termed Communications and High-Precision Positioning (CHP2) system. This technology was implemented on consumer-off-the-shelf (COTS) hardware and it offers rapid (<100 ms) and precise (<5 cm) positioning capabilities in over-the-air experiments using flexible ground stations and UAS platforms using limited bandwidth (10 MHz). In this study, CHP2 is considered in the context of safety-critical and resource limited transport applications and urban air mobility. The two-way ranging (TWR) protocol over a joint positioning-communications waveform enables distributed coherence and time-of-flight(ToF) estimation. In a multi-antenna setup, the cross-platform ranging on participating nodes in the network translate to precise target location and orientation. In the current form, CHP2 necessitates a cooperative timing exchange at regular intervals. Dynamic resource management supports higher user densities by constantly renegotiating spectral access depending on need and opportunity. With these novel contributions to the field of integrated positioning and communications, CHP2 is a suitable candidate to provide both communications, navigation, and surveillance (CNS) and alternative positioning, navigation, and timing (APNT) services for high density safety-critical transport applications on a variety of vehicular platforms. / Dissertation/Thesis / Doctoral Dissertation Electrical Engineering 2020

Automobile accidents are one of the leading causes of death and claim more than 40,000 lives annually in the US alone. A substantial portion of these accidents occur at road intersections. Stop signs and traffic signals are some of the intersection control devices used to increase safety and prevent collisions. However, these devices themselves can contribute to collisions, are costly, inefficient, and are prone to failure. This thesis proposes an adaptive, decentralized, cooperative collision avoidance (CCA) system that optimizes each vehicle's controls subject to the constraint that no collisions occur. Three major contributions to the field of collision avoidance have resulted from this research. First, a nonlinear 5-state variable vehicle model is expanded from an earlier model developed in [1]. The model accounts for internal engine characteristics and more realistically approximates vehicle behavior in comparison to idealized, linear models. Second, a set of constrained, coupled Extended Kalman Filters (EKF) are used to predict the trajectory of the vehicles approaching an intersection in real-time. The coupled filters support decentralized operation and ensure that the optimization algorithm bases its decisions on good, reliable estimates. Third, a vehicular network based on the new WAVE standard is presented that provides cooperative capabilities by enabling intervehicle communication. The system is simulated against today's common intersection control devices and is shown to be superior in minimizing average vehicle delay. / Master of Science

A presente dissertação traz a questão da aderência de viagens de veículos em monitoramentos inteligentes com sistemas Automatic Vehicle Location (AVL) que operam em rotas rodoviárias. Uma viagem é considerada como uma série de \"passadas\", que correspondem ao tempo em que o veículo está em movimento, mas excluindo os tempos gastos em paradas para atividades como carregamento/descarregamento entre outras. A partir de dados históricos coletados via Global Positioning System (GPS) pelo sistema AVL, uma metodologia de filtragem e aplicações estatísticas para geração das passadas é apresentada. Além disso, são propostos métodos para geração de padrões de viagem de referência, baseados em tempos de viagem e velocidades, desvios padrões, locais de descontinuidades entre outros parâmetros. A geração desses padrões em conjunto com procedimentos operacionais permite o monitoramento eficiente do progresso de viagens de frotas de veículos, para finalidades logísticas e de segurança. O progresso de um veículo ao longo de uma rota é analisado diante dos padrões de viagem de referência obtidos a partir de suas viagens prévias, de veículos similares na mesma rota ou de viagens em rotas de mesma classe, dependendo do que for mais adequado. A geração de padrões é um processo dinâmico que gera conhecimento sobre o veículo e comportamento da rodovia ao longo do tempo. Desenho do processo de monitoramento do progresso de viagem é apresentado, no qual, a cada nova coleta de dado GPS ou a cada instante solicitado pelo usuário, a aderência é medida, eventuais descontinuidades (saídas da rota, paradas ou mudança de sentido) são identificadas e avisos são gerados. Tal aderência é definida por índice de desempenho que considera os desvios de tempo em relação a valores de referência e respectivas tolerâncias. Para experimentação da metodologia, foi realizada simulação de viagem na rodovia BR116 na ligação São Paulo - Rio de Janeiro, sobre base com cerca de 130.000 registros de dados GPS associados. Com integração em Geographic Information System (GIS) para suporte de funcionalidades, foram gerados os padrões de viagem e simulado o processo de monitoramento com sucesso. / This dissertation addresses the question of vehicle travel adherence in intelligent monitoring with Automatic Transportation Location (AVL) operating in a regional environment. A trip is considered as series of runs, corresponding to time in movement but excluding time spent on activities such as loading/unloading and others. Based on historic data collected from AVL/GPS a statistical data filtering method to generate the runs is presented. Furthermore, statistical methods are proposed to generate travel patterns based on travel time, speed, standard deviation and other parameters. The pattern generation together with operational procedures allows effective monitoring of large fleets in logistics and safety. The progress of a vehicle along a route is evaluated face to the statistical patterns of its previous successful trips or against statistical patterns of similar vehicles on the same route, whichever appropriate. The generation of patterns is a dynamic continuous process that generates knowledge on vehicle and road behavior along time. A broad outline of the travel monitoring process is presented. Whenever the requested by user, the process calculates the travel adherence, identifies abnormalities and generates alarms. That adherence is defined by a performance index, which considers the travel time deviations from the reference values and the respective tolerances. Successful experimentation was carried out on the Rio de Janeiro - São Paulo motorway, with 130.000 Global Positioning System (GPS) positional data relayed from trucks to a Geographic Information System (GIS) based monitoring system in Brazil.

Le monde industriel, et en particulier l’industrie automobile, cherche à représenter au mieux le réel pour concevoir des outils et produits les plus adaptés aux enjeux et marchés actuels. Dans cette optique, le groupe Volvo a développé de puissants outils pour la simulation de la dynamique des véhicules industriels. Ces outils permettent notamment l’optimisation de composants véhicules ou de stratégies de contrôle. De nombreuses activités de recherche portent sur des technologies innovantes permettant de réduire la consommation des véhicules industriels et d’accroitre la sécurité de leurs usages dans différents environnements. En particulier, le développement des systèmes d’aide à la conduite automobile ITS et ADAS. Afin de pouvoir développer ces systèmes, un environnement de simulation permettant de prendre en compte les différents facteurs pouvant influencer la conduite d’un véhicule doit être mis en place. L’étude se concentre sur la simulation de l’environnement du véhicule et des interactions entre le véhicule et son environnement direct, i.e. le véhicule qui le précède. Les interactions entre le véhicule étudié et le véhicule qui le précède sont modélisées à l’aide de modèles mathématiques, nommés lois de poursuites. De nombreux modèles existent dans la littérature mais peu concernent le comportement des véhicules industriels. Une étude détaillée de ces modèles et des méthodes de calage est réalisée. L’environnement du véhicule peut être représenté par deux catégories de paramètres : statiques (intersections, nombre de voies…) et dynamiques (état du réseau). A partir d’une base de données de trajets usuels, ces paramètres sont calculés, puis utilisés pour générer de manière automatisée des scénarios de simulation réalistes. / The industrial world, and in particular the automotive industry, is seeking to best represent the real world in order to design tools and products that are best adapted to current challenges and markets, by reducing development times and prototyping costs. With this in mind, the Volvo Group has developed powerful tools to simulate the dynamics of industrial vehicles. These tools allow the optimization of vehicle components or control strategies. Many research activities focus on innovative technologies to reduce the consumption of industrial vehicles and increase the safety of their use in different environments. Particularly, the development of ITS and ADAS is booming. In order to be able to develop these systems, a simulation environment must be set up to take into account the various factors that can influence the driving of a vehicle. The work focuses on simulating the vehicle environment and the interactions between the vehicle and its direct environment, i.e. the vehicle in front of it. The interactions between the vehicle under study and the vehicle in front of it are modelled using mathematical models, called car-following models. Many models exist in the literature, but few of them deals specifically with heavy duty vehicles. A specific focus on these models and their calibration is realized. The vehicle environment can be represented by two categories of parameters: static (intersections, number of lanes) and dynamic parameters (state of the network). From a database of usuals roads, these parameters are computed, then, they are used to automatically generate realist traffic simulation scenarios.

A presente dissertação traz a questão da aderência de viagens de veículos em monitoramentos inteligentes com sistemas Automatic Vehicle Location (AVL) que operam em rotas rodoviárias. Uma viagem é considerada como uma série de \"passadas\", que correspondem ao tempo em que o veículo está em movimento, mas excluindo os tempos gastos em paradas para atividades como carregamento/descarregamento entre outras. A partir de dados históricos coletados via Global Positioning System (GPS) pelo sistema AVL, uma metodologia de filtragem e aplicações estatísticas para geração das passadas é apresentada. Além disso, são propostos métodos para geração de padrões de viagem de referência, baseados em tempos de viagem e velocidades, desvios padrões, locais de descontinuidades entre outros parâmetros. A geração desses padrões em conjunto com procedimentos operacionais permite o monitoramento eficiente do progresso de viagens de frotas de veículos, para finalidades logísticas e de segurança. O progresso de um veículo ao longo de uma rota é analisado diante dos padrões de viagem de referência obtidos a partir de suas viagens prévias, de veículos similares na mesma rota ou de viagens em rotas de mesma classe, dependendo do que for mais adequado. A geração de padrões é um processo dinâmico que gera conhecimento sobre o veículo e comportamento da rodovia ao longo do tempo. Desenho do processo de monitoramento do progresso de viagem é apresentado, no qual, a cada nova coleta de dado GPS ou a cada instante solicitado pelo usuário, a aderência é medida, eventuais descontinuidades (saídas da rota, paradas ou mudança de sentido) são identificadas e avisos são gerados. Tal aderência é definida por índice de desempenho que considera os desvios de tempo em relação a valores de referência e respectivas tolerâncias. Para experimentação da metodologia, foi realizada simulação de viagem na rodovia BR116 na ligação São Paulo - Rio de Janeiro, sobre base com cerca de 130.000 registros de dados GPS associados. Com integração em Geographic Information System (GIS) para suporte de funcionalidades, foram gerados os padrões de viagem e simulado o processo de monitoramento com sucesso. / This dissertation addresses the question of vehicle travel adherence in intelligent monitoring with Automatic Transportation Location (AVL) operating in a regional environment. A trip is considered as series of runs, corresponding to time in movement but excluding time spent on activities such as loading/unloading and others. Based on historic data collected from AVL/GPS a statistical data filtering method to generate the runs is presented. Furthermore, statistical methods are proposed to generate travel patterns based on travel time, speed, standard deviation and other parameters. The pattern generation together with operational procedures allows effective monitoring of large fleets in logistics and safety. The progress of a vehicle along a route is evaluated face to the statistical patterns of its previous successful trips or against statistical patterns of similar vehicles on the same route, whichever appropriate. The generation of patterns is a dynamic continuous process that generates knowledge on vehicle and road behavior along time. A broad outline of the travel monitoring process is presented. Whenever the requested by user, the process calculates the travel adherence, identifies abnormalities and generates alarms. That adherence is defined by a performance index, which considers the travel time deviations from the reference values and the respective tolerances. Successful experimentation was carried out on the Rio de Janeiro - São Paulo motorway, with 130.000 Global Positioning System (GPS) positional data relayed from trucks to a Geographic Information System (GIS) based monitoring system in Brazil.