Diploma thesis indicates on traffic problems that arise not only in the huge world metropolis but increasingly appeal in smaller towns. They cause not only time and money losses but also irreversible environmental damages. This issue represents a big challenge not only for cities, transport companies, logistics service providers but also for each human being in the world. The thesis focuses on the utilization of a relatively new concept called city logistics, which should be the key for improvement of traffic situation in the cities through a higher level of transport organization and its management, cooperation between the parties and the search of new forms of transport, which don't support just the economic part of certain territory, but also brings sustainable development of transport in the future. While some cities try to become familiar only in theory, others have already obtained positive effects of its implementation. To those progressive cities belongs as well Paris to which I paid attention in diploma thesis.

Bicycle use is increasing in many parts of the U.S. Local and regional governments have set ambitious bicycle mode share goals as part of their strategy to curb greenhouse gas emissions and relieve traffic congestion. In particular, Portland, Oregon has set a 25% mode share goal for 2030 (PBOT 2010). Currently bicycle mode share in Portland is 6.1% of all trips. Other cities and regional planning organizations are also setting ambitious bicycle mode share goals and increasing bicycle facilities and programs to encourage bicycling. Increases in bicycle mode share are being encouraged to increase. However, cities with higher-than-average bicycle mode share are beginning to experience locations with bicycle traffic congestion, especially during peak commute hours. Today, there are no established methods are used to describe or measure bicycle traffic flows. In the 1960s, the Highway Capacity Manual (HCM) introduced Level of Service (LOS) measurements to describe traffic flow and capacity of motor vehicles on highways using an A-to-F grading system; "A" describes free flow traffic with no maneuvering constraints for the driver and an "F" grade corresponds to over capacity situations in which traffic flow breaks down or becomes "jammed". LOS metrics were expanded to highway and road facilities, operations and design. In the 1990s, the HCM introduced LOS measurements for transit, pedestrians, and bicycles. Today, there are many well established and emerging bicycle level of service (BLOS) methods that measure the stress, comfort and perception of safety of bicycle facilities. However, it was been assumed that bicycle traffic volumes are low and do not warrant the use of a LOS measure for bicycle capacity and traffic flow. There are few BLOS methods that take bicycle flow into consideration, except for in the case of separated bicycle and bicycle-pedestrian paths. This thesis investigated the state of BLOS capacity methods that use bicycle volumes as a variable. The existing methods were applied to bicycle facility elements along a corridor that experiences high bicycle volumes in Portland, Oregon. Using data from the study corridor, BLOS was calculated and a sensitivity analysis was applied to each of the methods to determine how sensitive the models are to each of the variables used. An intercept survey was conducted to compare the BLOS capacity scores calculated for the corridor with the users' perception. In addition, 2030 bicycle mode share for the study corridor was estimated and the implications of increased future bicycle congestion were discussed. Gaps in the BLOS methods, limitations of the thesis study and future research were summarized. In general, the existing methods for BLOS capacity are intended for separated paths; they are not appropriate for existing high traffic flow facilities. Most of the BLOS traffic flow methods that have been developed are most sensitive to bicycle volumes. Some of these models may be a good starting point to improve BLOS capacity and traffic flow measures for high bicycle volume locations. Without the tools to measure and evaluate the patterns of bicycle capacity and traffic flow, it will be difficult to monitor and mitigate bicycle congestion and to plan for efficient bicycle facilities in the future. This report concludes that it is now time to develop new BLOS capacity measures that address bicycle traffic flow.

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

This thesis aims to give insight into a novel approach for quantifying car traffic in developing cities. This is necessary to improve efficiency in resource allocation for improvements in infrastructure. The project took form of a case study of neighborhoods in the city of Nairobi, Kenya. The approach consists of a method which relies on topics from the field of Topological Data Analysis, together with the use of large data sources from taxi services in the city. With this, both qualitative and quantitative insight can be given about the traffic. The method was proven useful for understanding how traffic spreads, and to differentiate between levels of congestion: quantifying it. However, it failed to detect the effect of previous improvements of infrastructure. / Målet med rapporten är att ge insikt i en innovativ ansats för att kvantifiera biltrafik i utvecklingsstäder. Detta kommer som en nödvändighet för att kunna förbättra resursfördelning i utvecklandet av infrastruktur. Projektet utspelade sig som en fallstudie där stadsdelar i Nairobi, Kenya studerades. Ansatsen innefattar en metod som bygger på tekniker från topologisk dataanalys (eng. \textit{Topological Data Analysis}), tillsammans med stora datakällor från taxitjänster i staden. Detta hoppas ge både kvalitativ och kvantitativ information om trafiken i staden. Metoden visade sig vara användbar för att förstå hur trafik sprider sig och att differentiera mellan nivåer av trafik, alltså att kvantifiera den. Tyvärr så misslyckades metoden visa sig användbar för att mäta förbättringar i infrastruktur.

The selection of the most appropriate traffic control actions to solve non-recurrent traffic congestion is a complex task which requires significant expert knowledge and experience. In this thesis we develop and investigate the application of an intelligent traffic control decision support system for road traffic management to assist the human operator to identify the most suitable control actions in order to deal with non-recurrent and non-predictable traffic congestion in a real-time situation. Our intelligent system employs a Fuzzy Neural Networks (FNN) Tool that combines the capabilities of fuzzy reasoning in measuring imprecise and dynamic factors and the capabilities of neural networks in terms of learning processes. In this work we present an effective learning approach with regard to the FNN-Tool, which consists of three stages: initializing the membership functions of both input and output variables by determining their centres and widths using self-organizing algorithms; employing an evolutionary Genetic Algorithm (GA) based learning method to identify the fuzzy rules; tune the derived structure and parameters using the back-propagation learning algorithm. We evaluate experimentally the performance and the prediction capability of this three-stage learning approach using well-known benchmark examples. Experimental results demonstrate the ability of the learning approach to identify all relevant fuzzy rules from the training data. A comparative analysis shows that the proposed learning approach has a higher degree of predictive capability than existing models. We also address the scalability issue of our intelligent traffic control decision support system by using a multi-agent based approach. The large network is divided into sub-networks, each of which has its own associated agent. Finally, our intelligent traffic control decision support system is applied to a number of road traffic case studies using the traffic network in Riyadh, in Saudi Arabia. The results obtained are promising and show that our intelligent traffic control decision support system can provide an effective support for real-time traffic control.

A lo largo de los años ha sido notorio el incremento de vehículos en el Perú, de igual manera en sus ciudades y este proyecto se desarrolla en la provincia de Chiclayo, precisamente en una intersección vial muy concurrida entre la avenida Chinchaysuyo con avenida Fitzcarrald y la avenida Víctor Raúl Haya de la Torre. En dicha intersección se genera congestión vehicular, esto se puede evidenciar en las colas de vehículos y la excesiva demora que se generan paracruzar una avenida sobre todo en horas punta. Teniendo en cuenta esta problemática y enfocando a la Ingeniería de Tránsito, la cual busca una planificación, diseño y principalmente busca una solución para mejorar el flujo vehicular. La investigación se centrará en analizar dicha intersección, elaborar un estudio de tráfico, levantamiento topográfico, con estos estudios se elabora un nuevo diseño geométrico, con esto también se hace una simulación vehicular. Al resultado de todos los datos se evaluarán dos propuestas y se determinara cual es la más conveniente para dicha intersección y se elaborara un modelamiento elaborando el programa de simulación Synchro 8. / Throughout the years, the increase in vehicles has been notorious in Peru, in the same way in its cities and this project is developed in the province of Chiclayo, precisely in a very busy road intersection between Chinchaysuyo avenue with Fitzcarrald avenue and Víctor Raul avenue. Haya de la Torre. In this intersection, traffic congestion is generated, this can be evidenced in the queues of vehicles and the excessive delay that is generated to cross an avenue, especially at peak times. Taking into account this problem and focusing on Traffic Engineering, which seeks planning, design and mainly seeks a solution to improve traffic flow. The research will focus on analyzing said intersection, developing a traffic study, topographic survey, with these studies a new geometric design is developed, with this a vehicular simulation is also made. At the result of all the data, two proposals will be evaluated and it will be determined which is the most convenient for said intersection and a modeling will be elaborated using the Synchro 8 simulation program.

Braess' paradox is a counter-intuitive phenomenon which can occur in congesting networks. It refers to those cases where the introduction of a new link in the network results in the total travel time on the network increasing. The dissertation starts by introducing the traffic assignment problem and the concept of equilibrium in traffic assignment. The concept of equilibrium is based on Wardrop's first principle that all travellers will attempt to minimize their own travel time regardless of the effect on others. A literature review includes details of a number of papers that have been published investigating theoretical aspects of the paradox. There is also a brief description of Game Theory and the Nash Equilibrium. It has been shown that the equilibrium assignment is an example of Nash Equilibrium. The majority of work that has been published deals with networks where the delay functions that are used to compute the travel times on the links of the network do not include explicit representation of the capacity of the links. In this dissertation a network that is similar in form to the one first presented by Braess was constructed with the difference being that the well-known BPR function was used in the delay functions. This network was used to show that a number of findings that had been presented previously using simpler functions also applied to this network. It was shown that when it occurs, Braess' paradox only occurs over a range of values at relatively low levels of congestion. Real-world networks were then investigated and it was found that similar results occurred to those found in the simpler test networks that are often used in discussions of the paradox. Two methodologies of eliminating the paradox were investigated and the results are presented. / Decision Sciences / M.Sc.

The selection of the most appropriate traffic control actions to solve non-recurrent traffic congestion is a complex task which requires significant expert knowledge and experience. In this thesis we develop and investigate the application of an intelligent traffic control decision support system for road traffic management to assist the human operator to identify the most suitable control actions in order to deal with non-recurrent and non-predictable traffic congestion in a real-time situation. Our intelligent system employs a Fuzzy Neural Networks (FNN) Tool that combines the capabilities of fuzzy reasoning in measuring imprecise and dynamic factors and the capabilities of neural networks in terms of learning processes. In this work we present an effective learning approach with regard to the FNN-Tool, which consists of three stages: initializing the membership functions of both input and output variables by determining their centres and widths using self-organizing algorithms; employing an evolutionary Genetic Algorithm (GA) based learning method to identify the fuzzy rules; tune the derived structure and parameters using the back-propagation learning algorithm. We evaluate experimentally the performance and the prediction capability of this three-stage learning approach using well-known benchmark examples. Experimental results demonstrate the ability of the learning approach to identify all relevant fuzzy rules from the training data. A comparative analysis shows that the proposed learning approach has a higher degree of predictive capability than existing models. We also address the scalability issue of our intelligent traffic control decision support system by using a multi-agent based approach. The large network is divided into sub-networks, each of which has its own associated agent. Finally, our intelligent traffic control decision support system is applied to a number of road traffic case studies using the traffic network in Riyadh, in Saudi Arabia. The results obtained are promising and show that our intelligent traffic control decision support system can provide an effective support for real-time traffic control.

Rede Ad hoc Veicular (VANET) é um subconjunto singular das redes ad hoc móveis (MANET), com o diferencial de que os nós são veículos providos de tecnologia própria de comunicação e que interagem para formar redes espontâneas, valendo-se de pouca ou nenhuma infraestrutura estabelecida previamente. VANETs admitem a integração de diferentes tecnologias sem fio na pretensão de mitigar adversidades, agregar segurança e eficiência ao tráfego. Na disseminação de dados, um salto único é suficiente para orientar os elementos ao alcance do sinal de rádio, e nós intermediários sustentam a comunicação aos demais, em encaminhamento multihop. Amparados em dispositivos embarcados, os veículos produzem registros, detectam sinais, trocam advertências e métricas. Avaliações dessas informações permitem ao condutor decisões ou reações antecipadas em situações adversas, a exemplo dos acidentes ou congestionamentos. Nesse contexto, a execução deste trabalho trata questões para elaborar estratégias adaptativas inteligentes de disseminação de dados, uma vez que as mesmas se consolidam como lastros da comunicação em VANET com condições adversas de operação. A abordagem proposta se utiliza de sistemas fuzzy para a detecção de congestionamento, com o propósito de agregar autonomia e adaptar a estratégia de disseminação às condições de tráfego identificadas. A convergência nos desenvolvimentos realizados se reflete na estratégia eFIRST, uma solução robusta para a detecção autônoma da condição atual de congestionamento que resguarda a disseminação adaptativa de alertas e abranda o problema da interrupção no tráfego. A abordagem se sustenta apenas na comunicação entre veículos e nos registros de identificação da vizinhança local, agregados em uma estratégia fuzzy e no ajuste adaptativo da potência do sinal de transmissão. Em conformidade com as tendências de condução e com os sistemas inteligentes, este desenvolvimento contribui com subsídios para ratificar a aproximação fuzzy como estratégia adaptativa às flutuações na densidade veicular, em diferentes cenários e regimes de tráfego. As avaliações comparativas do eFIRST respaldam concluir que a estratégia oportuniza o equilíbrio otimizado das perdas, colisões e cobertura, com superior alcance de propagação e redução dos congestionamentos. / Vehicular Ad hoc Network (VANET) is a unique subset of mobile ad hoc networks (MANET), with the difference that nodes are vehicles provided with their own communication technology and interact to form spontaneous networks, with little or no infrastructure previously established. VANETs support the integration of different wireless technologies in order to mitigate adversities, add security and efficiency to traffic. In the data dissemination, a single hop is sufficient to guide the elements within reach of the radio signal, and intermediary nodes support the communication with the others in multihop routing. Supported by embedded devices, vehicles produce records, detect signals, exchange warnings and metrics. Assessments of this information allow the driver to make decisions or react beforehand in adverse situations, such as accidents or traffic congestions. From the observations in this context, this work deals with questions to elaborate intelligent adaptive strategies in data dissemination, since they consolidate themselves as ballast communication in VANET with adverse operating conditions. The proposed approach uses fuzzy systems to detect traffic congestion, with the purpose of aggregating autonomy and adapting the dissemination strategy to the identified traffic conditions. The convergence in the developments performed is reflected in the eFIRST strategy, a robust solution for the autonomous detection of the current traffic congestion condition that protects the adaptive dissemination of alerts and reduces the problem of the interruption in the traffic. The approach is supported only by communication between vehicles and in local neighborhood identification records, aggregated in a fuzzy strategy and in the adaptive adjustment of transmission signal power. In accordance with the driving trends and with the intelligent systems, this development contributes with assistance for ratify the fuzzy approach as an adaptive strategy to fluctuations in vehicular density in different scenarios and traffic regimes. Comparative evaluations of eFIRST support the conclusion that the strategy favors the optimal balance of losses, collisions and coverage, with a greater range of propagation and reduction of congestion.

A Região Metropolitana de São Paulo (RMSP) sofre de sérios problemas de congestionamento, assim como muitas outras cidades de grande porte. Uma possível solução, proposta por pesquisadores de transportes, economia e ciências ambientais, é a implantação de um sistema de congestion charging, chamada no Brasil de pedágio urbano. Um dos objetivos do presente trabalho foi estabelecer os conceitos relacionados a este assunto e ilustrar as principais questões relacionadas à sua implantação. Espera-se que este trabalho possa auxiliar o desenvolvimento de estudos de avaliação da viabilidade e de impactos de sistemas propostos de congestion charging. Para atingir este objetivo, toca-se em diversos assuntos, como a definição de congestionamento e as formas de medi-lo, a base conceitual e teórica dos sistemas de congestion charging e seus diversos esquemas de diferenciação. São expostas também as medidas de mitigação de congestionamento que já foram implantadas na RMSP, quais foram os estudos já desenvolvidos considerando este tipo de política para a RMSP, e casos em que sistemas de congestion charging já foi implantado. Neste trabalho, desenvolveu-se também um modelo de escolha discreta a partir dos dados da Pesquisa Origem e Destino 2007 do METRÔ, onde pessoas deveriam escolher entre \"Transporte Coletivo\" e \"Transporte Público\". Este modelo foi utilizado para avaliar o potencial de impacto na divisão modal e de arrecadação de um congestion charge aplicado ao centro expandido de São Paulo. Adverte-se, porém, que os resultados obtidos são meramente ilustrativos. Mostra-se, também, que é possível avaliar a capacidade ociosa do sistema de transporte coletivo a partir dos dados disponíveis de bilhetagem e de GPS dos ônibus. Este processo é exemplificado através do cálculo de capacidade de uma única viagem de um único ônibus, dada a dificuldade de automatização deste processo para abranger toda a frota. / The São Paulo Metropolitan Region (SPMR) suffers from severe traffic congestion, as do many other large-scale urban areas around the world. A possible solution to this issue, which has been suggested by transportation, economics and environmental researchers, is the implementation of a congestion charging system. One of the objectives of this project is to establish clear concepts and shed light on the main issues regarding these systems by means of a comprehensive literary review. It is expected that this project may help the development of in-depth studies carried in order to evaluate the viability and impacts of congestion charging proposals. In order to achieve this goal, many subjects are addressed, such as the definition of congestion, how its measured, the theoretical backgrounds that support congestion charging schemes, their different degrees of differentiation, which policies were enacted in order to reduce traffic congestion in São Paulo, what considerations and studies have already been developed for Brazil and São Paulo regarding these systems and where have these systems been successfully installed. Later chapters deal with another goal of this project: estimating how a congestion charging system would affect SPMR. This was achieved through a multinomial logit model, where decision-makers choose between \"Public Transportation\" and \"Private Automobile\". The results presented at this phase are merely indicative of certain tendencies and should not be considered final. This project also attempts to show that given the available Automated Fare Collection (AFC) data and Automated Vehicle Location (AVL) data, it is possible to estimate the current public transportation system\'s unused capacity. The author shows this by calculating the capacity of one bus trip using these data, but also explains the difficulties of expanding this analysis to the whole of SPMR\'s public transportation system.