Veículos autônomos são objeto de crescente estudo em todo o mundo. Face à Engenharia de Transportes, é tema que deve provocar uma revolução nas próximas décadas, pois é concreta a tendência ao uso destes veículos na sociedade. Podem se citar como grandes beneficiados a segurança, a logística, o fluxo de trânsito, o meio ambiente e também os portadores de deficiências. Com o objetivo de fazer um veículo atingir um ponto com coordenadas conhecidas de forma autônoma, uma plataforma veicular terrestre em escala foi utilizada, a qual recebeu um sistema computacional micro controlado e tecnologias para proporcionar mobilidade através de motores elétricos para tração e servo-motores para direcionamento; posicionamento por satélite através de receptor GNSS e bússola eletrônica para orientação; sensoriamento por ultra-som para evitar colisões; e comunicação sem fio, a fim de se realizar remotamente monitoramento e instrução em tempo real através de um aplicativo para computador pessoal (PC). Foi desenvolvido um algoritmo de navegação que, fazendo uso dos recursos disponíveis, proporcionou autonomia ao veículo, de forma a navegar para pontos com coordenadas conhecidas sem controle humano. Os testes realizados visaram avaliar a capacidade de autonomia do veículo, a trajetória de navegação realizada e a acurácia de chegada aos pontos de destino. O veículo foi capaz de atingir os pontos em todos os testes realizados, sendo considerado funcional seu algoritmo de navegação e também os sistemas de mobilidade, posicionamento, sensoriamento e comunicação. / Autonomous vehicles are an on growing research target around the world. Face to Transports Engineering, it is a subject which is expected to make a revolution on the next decades. The great benefits are on security, logistic, traffic flow, environment and handicap. With the goal to make a vehicle navigate autonomously to known geodesics coordinates, a reduced scale terrestrial vehicular platform was used. This platform received a microcontrolled computational system and technologies to give it mobility, through electrical motors for traction and servo-motors for direction; satellite positioning, through a GNSS receiver and magnetic compass for orientation; ultrasound sensing in order to avoid collision; and wireless communication, in order to do remote monitoring and instruction at real time through a PC application. It was developed a navigation algorithm which, from the available resources, gave autonomy to the vehicle, in order to navigate to known geodesics coordinates without human control. The test set was intended to evaluate the autonomy capacity of the vehicle, the navigation trajectory that was done and the arrival accuracy to the destination points. The vehicle reached the destination points on all tests done, being evaluated as functional its navigation algorithm and also the mobility, positioning, sensing and communication systems.

Time keeps on changing our perception of what is possible in our personal life and around us. Over time, jobs such as elevator operator was essential to make the elevator keep its speed, stop parallel to the floor and keep passengers safe in case of emergency. Nowadays elevator passengers just have to enter their destination and wait to be transported there. An operator would be superfluous for this, today, simple procedure. This paper aims to create a set of interaction strategies to provide an efficient and pleasurable journey for the passenger traveling with an autonomous bus, as well as evaluate concepts where these strategies have been applied. The strategies and concepts will be developed from an extensive user- and literature research where the situation of today will be analysed and looked upon with the eyes of tomorrow, to find challenges and needs. Findings shows that passengers have to trust the vehicle and service. At the same time vehicle and service providers have to provide a reliable and consistent service. Four design directions were created to establish this trust between the user and vehicle and service. To enable control and give passengers an efficient journey, passengers have to be provided with adequate and reliable information. The information regarding the bus’s behaviour should be communicated in a transparent way so the bus’s intentions and actions are understandable from a passenger point of view. Also, passengers have to be enabled to stay safe when using the bus, during commuting and emergency, through giving them cues in how an emergency should be handled.

Devido à grande importância do ambiente aquático sobre a vida humana e às dificuldades inerentes ao seu estudo e exploração, a aplicação de AUVs tem se mostrado bastante benéfica e seu uso vem crescendo ao longo dos anos. Este trabalho apresenta um estudo sobre o desenvolvimento de veículos autônomos submarinos para realização de missões oceanográficas, com foco nas características de seus sistemas embarcados que permitam atender melhor os requisitos desta aplicação. Analisando trabalhos publicados nos últimos anos pode-se notar uma grande quantidade de AUVs desenvolvidos ou adaptados para aplicações em oceanografia, com uma grande variedade de soluções aplicadas em seus diversos sistemas, visando a realização de diversos tipos de missões necessárias para tais estudos. Como estudo de caso, foi apresentada a adaptação do AUV Pirajuba, desenvolvido inicialmente como uma plataforma de testes hidrodinâmicos, para aplicação em missões de levantamento de dados para estudos oceanográficos. Para tal, foi necessário realizar uma série de modificações em seus subsistemas, permitindo a instalação de novos sensores e equipamentos para aumento da segurança nas operações em mar aberto. As modificações necessárias envolveram tanto o sistema hidromecânico do veículo, com instalação de novos módulos no casco, quanto no seu sistema embarcado, implicando no desenvolvimento de uma nova versão do sistema de hardware e uma atualização no software de controle. Tendo em vista esta necessidade, foi proposto um estudo dos requisitos da aplicação oceanográfica de AUVs e os impactos no seu desenvolvimento. Para isso, foi realizado um levantamento dos requisitos das principais aplicações oceanográficas e seus impactos no desenvolvimento dos veículos, envolvendo os sistemas hidromecânico, energia, navegação, comunicação e controle. Foi realizado também um estudo da arquitetura de controle CANARMES, desenvolvida para o AUV Pirajuba, envolvendo os requisitos de seu projeto e as principais características da arquitetura de controle, que serviu como base para a atualização do veículo para as novas aplicações. São apresentados os resultados obtidos em testes de campo realizados no litoral de Ubatuba - SP, nos quais foram feitas manobras com movimentação vertical com a aquisição de dados de diversos sensores oceanográficos, utilizados para o estudo de detecção de camadas finas. / Due to the great importance of the aquatic environment on human life and the inherent difficulties of its study and exploration, the application of AUVs has been shown to be very beneficial and its use has been growing over the years. This work presents a study on the development of autonomous submarine vehicles for the accomplishment of oceanographic missions, focusing on the characteristics of the embedded systems of these vehicles in order to better meet the application requirements. Analyzing published works in the last five years, it can be noticed a great amount of AUVs developed or adapted for applications in oceanography, with a great variety of solutions applied in their embedded systems, involving both hardware and software, aiming at the accomplishment of several types of missions necessary for such studies. As a case study, the adaptation of the AUV Pirajuba, initially developed as a platform for hydrodynamic tests, was presented for application in data collection missions for oceanographic studies. For this, it was necessary to make a series of modifications in its subsystems, allowing the installation of new sensors and equipment to increase the safety in the operations in the open sea. The necessary modifications involved both the vehicle\'s hydromechanical system, with the installation of new modules in the hull, and in its embedded system, requiring the development of a new version of the hardware system and an update in the control software. Due to this necessities, a study was proposed to better understand the requirements of AUVs for oceanographic application and the impacts on their development. For that, a survey was made of the requirements of the main oceanographic applications and their impacts on the development of the vehicles, involving the hydromechanical, energy, navigation, communication and control systems. A study of the CANARMES control architecture, developed for the Pirajuba AUV, was carried out, involving the requirements of its design and the main characteristics of the control architecture, which served as a basis for updating the vehicle for new applications. We present the results obtained in field tests conducted in the coastal area of Ubatuba - SP, Brazil, in which maneuvers were performed with vertical movement, while acquiring data from several oceanographic sensors, used for the study of thin layer detection.

Orientadores: Douglas Eduardo Zampieri, Isabelle Fantoni Coichot / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecanica / Made available in DSpace on 2018-08-19T04:14:42Z (GMT). No. of bitstreams: 1 MirandaNeto_Arthurde_D.pdf: 4965049 bytes, checksum: 6d16ee5315ee6bbbfd893b534fde6729 (MD5) Previous issue date: 2011 / Resumo: Esta tese aborda o problema de evitamento de obstáculos para plataformas terrestres semie autônomas em ambientes dinâmicos e desconhecidos. Baseado num sistema monocular, propõe-se um conjunto de ferramentas que monitoram continuamente a estrada a frente do veículo, provendo-o de informações adequadas em tempo real. A partir de um algoritmo robusto de detecção da linha do horizonte é possível investigar dinamicamente somente a porção da estrada a frente do veículo, a fim de determinar a área de navegação, e da deteção de obstáculos. Uma área de navegação livre de obstáculos é então representa a partir de uma imagem multimodal 2D. Esta representação permite que um nível de segurança possa ser selecionado de acordo com o ambiente e o contexto de operação. A fim de reduzir o custo computacional, um método automático para descarte de imagens é proposto. Levando-se em conta a coerência temporal entre consecutivas imagens, uma nova metodologia de gerenciamento de energia (Dynamic Power Management) é aplicada ao sistema de percepção visual a fim de otimizar o consumo de energia. Estas propostas foram testadas em diferentes tipos de ambientes, e incluem a deteção da área de navegação, navegação reativa e estimação do risco de colisão. Uma característica das metodologias apresentadas é a independência em relação ao sistema de aquisição de imagem e do próprio veículo. Este sistema de percepção em tempo real foi avaliado a partir de diferentes bancos de testes e também a partir de dados reais obtidos por diferentes plataformas inteligentes. Em tarefas realizadas com uma plataforma semi-autônoma, testes foram conduzidos em velocidades acima de 100 Km/h. A partir de um sistema em malha aberta, deslocamentos reativos autônomos foram realizados com sucesso / Resumé: Les études développées dans ce projet doctoral ont concerné deux problématiques actuelles dans le domaine des systèmes robotiques pour la mobilité terrestre: premièrement, le problème associé à la navigation autonome et (semi)-autonome des véhicules terrestres dans un environnement inconnu ou partiellement connu. Cela constitue un enjeu qui prend de l'importance sur plusieurs fronts, notamment dans le domaine militaire. Récemment, l'agence DARPA1 aux États-Unis a soutenu plusieurs challenges sur cette problématique robotique; deuxièmement, le développement de systèmes d'assistance à la conduite basés sur la vision par ordinateur. Les acteurs de l'industrie automobile s'intéressent de plus en plus au développement de tels systèmes afin de rendre leurs produits plus sûrs et plus confortables à toutes conditions climatiques ou de terrain. De plus, grâce à l'électronique embarquée et à l'utilisation des systèmes visuels, une interaction avec l'environnement est possible, rendant les routes et les villes plus sûres pour les conducteurs et les piétons. L'objectif principal de ce projet doctoral a été le développement de méthodologies qui permettent à des systèmes mobiles robotisés de naviguer de manière autonome dans un environnement inconnu ou partiellement connu, basées sur la perception visuelle fournie par un système de vision monoculaire embarqué. Un véhicule robotisé qui doit effectuer des tâches précises dans un environnement inconnu, doit avoir la faculté de percevoir son environnement proche et avoir un degré minimum d'interaction avec celui-ci. Nous avons proposé un système de vision embarquée préliminaire, où le temps de traitement de l'information (point critique dans des systèmes de vision utilisés en temps-réel) est optimisé par une méthode d'identification et de rejet d'informations redondantes. Suite à ces résultats, on a proposé une étude innovante par rapport à l'état de l'art en ce qui concerne la gestion énergétique du système de vision embarqué, également pour le calcul du temps de collision à partir d'images monoculaires. Ainsi, nous proposons le développement des travaux en étudiant une méthodologie robuste et efficace (utile en temps-réel) pour la détection de la route et l'extraction de primitives d'intérêts appliquée à la navigation autonome des véhicules terrestres. Nous présentons des résultats dans un environnement réel, dynamique et inconnu. Afin d'évaluer la performance de l'algorithme proposé, nous avons utilisé un banc d'essai urbain et réel. Pour la détection de la route et afin d'éviter les obstacles, les résultats sont présents en utilisant un véhicule réel afin d'évaluer la performance de l'algorithme dans un déplacement autonome. Cette Thèse de Doctorat a été réalisée à partir d'un accord de cotutelle entre l' Université de Campinas (UNICAMP) et l'Université de Technologie de Compiègne (UTC), sous la direction du Professeur Docteur Douglas Eduardo ZAMPIERI, Faculté de Génie Mécanique, UNICAMP, Campinas, Brésil, et Docteur Isabelle FANTONI-COICHOT du Laboratoire HEUDIASYC UTC, Compiègne, France. Cette thèse a été soutenue le 26 août 2011 à la Faculté de Génie Mécanique, UNICAMP, devant un jury composé des Professeurs suivants / Abstract: This thesis addresses the problem of obstacle avoidance for semi- and autonomous terrestrial platforms in dynamic and unknown environments. Based on monocular vision, it proposes a set of tools that continuously monitors the way forward, proving appropriate road informations in real time. A horizon finding algorithm was developed to sky removal. This algorithm generates the region of interest from a dynamic threshold search method, allowing to dynamically investigate only a small portion of the image ahead of the vehicle, in order to road and obstacle detection. A free-navigable area is therefore represented from a multimodal 2D drivability road image. This multimodal result enables that a level of safety can be selected according to the environment and operational context. In order to reduce processing time, this thesis also proposes an automatic image discarding criteria. Taking into account the temporal coherence between consecutive frames, a new Dynamic Power Management methodology is proposed and applied to a robotic visual machine perception, which included a new environment observer method to optimize energy consumption used by a visual machine. This proposal was tested in different types of image texture (road surfaces), which includes free-area detection, reactive navigation and time-to-collision estimation. A remarkable characteristic of these methodologies is its independence of the image acquiring system and of the robot itself. This real-time perception system has been evaluated from different test-banks and also from real data obtained by two intelligent platforms. In semi-autonomous tasks, tests were conducted at speeds above 100 Km/h. Autonomous displacements were also carried out successfully. The algorithms presented here showed an interesting robustness / Doutorado / Mecanica dos Sólidos e Projeto Mecanico / Doutor em Engenharia Mecânica

In the field of robotics and autonomous vehicles, the use of RGB-D data and LiDAR sensors is a popular practice for applications such as SLAM[14], object classification[19] and scene understanding[5]. This thesis explores the problem of semantic segmentation using deep multimodal fusion of LRF and depth data. Two data set consisting of 1080 and 108 data points from two scenes is created and manually labeled in 2D space and transferred to 1D using a proposed label transfer method utilizing hierarchical clustering. The data set is used to train and validate the suggested method for segmentation using a proposed dual encoder-decoder network based on SalsaNet [1] with gradual fusion in the decoder. Applying the suggested method yielded an improvement in the scenario of an unseen circuit when compared to uni-modal segmentation using depth, RGB, laser, and a naive combination of RGB-D data. A suggestion of feature extraction in the form of PCA or stacked auto-encoders is suggested as a further improvement for this type of fusion. The source code and data set are made publicly available at https://github.com/Anguse/salsa_fusion.

<p>Ninety-five percent of all roadway crashes are attributed fully or partially to human error, and a multitude of safety-related programs, policies, and initiatives have seen limited success in reducing roadway crashes and their accompanying fatalities, injuries, and property damage. For this reason, safety professionals have lauded the emergence of autonomous vehicles (AVs) as a promising palliative to the persistent problem of road crashes. Such optimism is reflected in recent literature that have argues from a conceptual standpoint, that road safety enhancement will be one of the prospective benefits of AV operations because automation removes humans from vehicle driving operations and therefore criminates or mitigates human error. It can be argued that the safety benefits of AVs will be manifest when AV market penetration reaches 100%. However, it seems clear from a practical standpoint that the transition from a system of exclusively human-driven vehicles (HDVs) to that of exclusively AVs will not only be necessary but also an arduous journey. This transition period will be characterized by heterogeneous traffic, where human-driven vehicles (HDVs) and AVs share the road space, and whence the prospective safety benefits of AVs may not be fully realized due to human error arising from the HDV operations in the mixed traffic space. These traffic conflicts, which may lead to collisions, could arise from any of several contexts of driving maneuvers, one of which is aggressive lane changes, the focus of this thesis. From the literature, it is clear that lane changing is inherently more collision-prone compared to most other maneuvers including car following, and therefore the consequences of errant human driving behavior such as inattention of misjudgment during lane changing, are more severe. To address this problem, this thesis developed a control framework to be used by AVs to help them avoid collision in a mixed traffic stream with human drivers who exhibit aggressive lane-changing behavior. The developed framework, which is based on a Model Predictive Control (MPC) approach, is designed to control the AV’s movements safely by duly accommodating potential human error from the HDVs that could otherwise lead to any of two common collision patterns: rear-end and side-impact. Further, the thesis investigated how connectivity between the HDVs, and AVs could facilitate joint operational decision-making and sharing of real-time information, thereby further enhancing the safety of the entire traffic stream. Finally, the thesis presents the results of driving simulations carried out to test and validate the performance of the control framework under different traffic conditions.</p>

<div>Advances in information and communication technologies enable new paradigms for connectivity involving vehicles, infrastructure, and the broader road transportation system environment. Vehicle-to-vehicle (V2V) communications under the aegis of the connected vehicle are being leveraged for novel applications related to traffic safety, management, and control, which lead to a V2V-based traffic system. Within the framework of a V2V-based traffic system, this study proposes an integrated modeling framework to model the dynamics of a V2V-based traffic system that entails spatiotemporal interdependencies among the traffic flow dynamics, V2V communication constraints, the dynamics of information flow propagation, and V2V-based application. The proposed framework systematically exploits their spatiotemporal interdependencies by theoretical and computational approaches.</div><div>First, a graph-based multi-layer framework is proposed to model the V2V-based advanced traveler information system (ATIS) as a complex system which is comprised of coupled network layers. This framework addresses the dynamics of each physical vehicular traffic flow, inter-vehicle communication, and information flow propagation components within a layer, while capturing their interactions among layers. This enables the capabilities to transparently understand the spatiotemporal evolution of information flow propagation through a graph structure. A novel contribution is the systematic modeling of an evolving information flow network that is characterized as the manifestation of spatiotemporal events in the other two networks to enhance the understanding of the information flow evolution by capturing the dynamics of the interactions involving the traffic flow and the inter-vehicle communication layers. The graph-based approach enables the computationally efficient tracking of information propagation using a simple graph-based search algorithm and the computationally efficient storage of information through a single graph database.</div><div>Second, this dissertation proposes analytical approaches that enable theoretical investigation into the qualitative properties of information flow propagation speed. The proposed analytical models, motivated from spatiotemporal epidemiology, introduce the concept of an information flow propagation wave (IFPW) to facilitate the analysis of the information propagation characteristics and impacts of traffic dynamics at a macroscopic level. The first model consists of a system of difference equations in the discrete-space and discrete-time domains where an information dissemination is described in the upper layer and a vehicular traffic flow is modeled in the lower layer. This study further proposes a continuous-space and continuous-time analytical model that can provide a closed-form solution for the IFPW speed to establish an analytical relationship between the IFPW speed and the underlying traffic flow dynamics. It can corporate the effects of congested traffic, such as the backward traffic propagation wave, on information flow propagation. Thereby, it illustrates the linkage between information flow propagation and the underlying traffic dynamics. Further, it captures V2V communication constraints in a realistic manner using a probabilistic communication kernel (which captures the probability).<br></div><div>Third, within the integrated modeling framework, this dissertation captures the impact of information flow propagation on traffic safety and control applications. The proposed multi-anticipative forward collision warning system predicts the driver’s maneuver intention using a coupled hidden Markov model, which is one of statistical machine learning techniques. It significantly reduces the false alarm rates by addressing the uncertainty associate improves the performance of the future motion prediction, while currently available sensor-based kinematic models for addressing the uncertainty associated with the future motion prediction. A network-level simulation framework is developed to investigate a V2V-based ATIS in a large-scale network by capturing its inter-dependencies and feedback loop. This modeling framework provides the understanding of the relationship between the travelers’ routing decisions and information flow propagation.</div><div>This thesis provides a holistic understanding of information flow propagation characteristics in space and time by characterizing interactions among information flow propagation, and underlying traffic flow, and V2V communications characteristics. The proposed models and the closed-form solution of IFPW speed can help in designing effective V2V-based traffic systems, without relying on computationally expensive numerical methods. An innovative aspect of this approach represents a building block to develop both descriptive capabilities and prescriptive strategies related to propagating the flow of useful information efficiently and synergistically generating routing mechanisms that enhance the traffic network performance. Given the lack of appropriate methodologies to characterize the information flow propagation, this thesis expects to make a novel and significant contribution to understanding the characteristics of V2V-based traffic systems and their analysis.</div>

The study of this research has a challenge of learning data gathering sensor programming and design of electronic sensor circuit. The cost of autonomous vehicle development is expensive compared to purchasing an economy vehicle such as the Hyundai Elantra. Keeping the development cost down is critical to maintaining a competitive edge on vehicle pricing with newer technologies. Autonomous vehicle sensor integration was designed and then tested for the driving vision data-gathering system that requires the system to gather driving vision data utilizing area scan sensors, Lidar, ultrasonic sensor, and camera on real road scenarios. The project utilized sensors such as cheap cost LIDAR, which is that drone is used for on the road testing; other sensors include myRIO (myRIO Hardware), LabVIEW (LabVIEW software), LIDAR-Lite v3 (Garmin, 2019), Ultrasonic sensor, and Wantai stepper motor (Polifka, 2020). This research helps to reduce the price of usage of autonomous vehicle driving systems in the city. Due to resolution and Lidar detecting distance, the test environment is limited to within city areas. Lidar is the most expensive equipment on autonomous vehicle driving data gathering systems. This study focuses on replacing expensive Lidar, ultrasonic sensor, and camera to drone scale low-cost Lidar to real size vehicle. With this study, economic expense autonomous vehicle driving data acquisition is possible. Lowering the price of autonomous vehicle driving data acquisition increases involving new companies on the autonomous vehicle market. Multiple testing with multiple cars is possible. Since multiple testing at the same time is possible, collecting time reduces.

The operation of groups of heavy-duty vehicles at small inter-vehicular distances, known as platoons, lowers the overall aerodynamic drag and, therefore, reduces fuel consumption and greenhouse gas emissions. Experimental tests conducted on a flat road and without traffic have shown that platooning has the potential to reduce the fuel consumption up to 10%. However, platoons are expected to drive on public highways with varying topography and traffic. Due to the large mass and limited engine power of heavy-duty vehicles, road slopes can have a significant impact on feasible and optimal speed profiles. Therefore, maintaining a short inter-vehicular distance without coordination can result in inefficient or even infeasible speed trajectories. Furthermore, external traffic can interfere by affecting fuel-efficiency and threatening the safety of the platooning vehicles. This thesis addresses the problem of safe and fuel-efficient control for heavy-duty vehicle platooning. We propose a hierarchical control architecture that splits this complex control problem into two layers. The layers are responsible for the fuel-optimal control based on look-ahead information on road topography and the real-time vehicle control, respectively. The top layer, denoted the platoon coordinator, relies on a dynamic programming framework that computes the fuel-optimal speed profile for the entire platoon. The bottom layer, denoted the vehicle control layer, uses a distributed model predictive controller to track the optimal speed profile and the desired inter-vehicular spacing policy. Within this layer, constraints on the vehicles' states guarantee the safety of the platoon. The effectiveness of the proposed controller is analyzed by means of simulations of several realistic scenarios. They suggest a possible fuel saving of up to 12% for the follower vehicles compared to the use of existing platoon controllers. Analysis of the simulation results shows how the majority of the fuel saving comes from a reduced usage of vehicles brakes. A second problem addressed in the thesis is model predictive control for obstacle avoidance and lane keeping for a passenger car. We propose a control framework that allows to control the nonlinear vehicle dynamics with linear model predictive control. The controller decouples the longitudinal and lateral vehicle dynamics into two successive stages. First, plausible braking and throttle profiles are generated. Second, for each profile, linear time-varying models of the lateral dynamics are derived and used to formulate a collection of linear model predictive control problems. Their solution provides the optimal control input for the steering and braking actuators. The performance of the proposed controller has been evaluated by means of simulations and real experiments. / <p>QC 20150911</p>

This thesis proposes a planning framework for Autonomous Electric Vehicle (AEV) charging. The framework is intended to help transportation decision-makers determine Electric Vehicle (EV) charging facility locations and capacities for the mixed fleet of Autonomous Vehicle (AV) and Human-driven Vehicle (HDV). The bi-level nature of the framework captures the decision-making processes of the transportation agency decision-makers and travelers, thereby providing solid theoretical and practical foundations for the EV charging network design. At the upper level, the decision-makers seek to determine the locations and operating capacities of the EV charging facilities, in a manner that minimizes total travel time and construction costs subject to budgetary limitations. In addition, the transportation decision-makers provide AV-exclusive lanes to encourage AV users to reduce travel time, particularly at wireless-charging lanes, as well as other reasons, including safety. At the lower level, the travelers seek to minimize their travel time by selecting their preferred vehicle type (AV vs. HDV) and route. In measuring the users delay costs, the thesis considered network user equilibrium because the framework is designed for urban networks where travelers route choice affects their travel time. The bi-level model is solved using the Non-Dominated Sorting Genetic Algorithm (NSGA-II) algorithm.