Preferential treatments are employed to provide preemption for emergency vehicles (EV) and conditional priority for transit vehicles at signalized intersections. EV preemption employs technologies and signal control strategies seeking to reduce emergency vehicle crash potential and response times. Transit priority employs the same technologies with signal control strategies seeking to reduce travel time and travel time variability. Where both preemption and transit technologies are deployed, operational strategies deconflict simultaneous requests. Thus far, researchers have developed separate evaluation frameworks for preemption and priority. This research addresses the issue of preemption and priority signal control strategies in breadth and depth. In breadth, this research introduces a framework that reveals planning interdependence and operational interaction between preemption and priority from the controlling strategy down to roadway hardware operation under the inclusive title: preferential treatment. This fulfills a current gap in evaluation. In depth, this research focuses on evaluation of EV preemption. There are two major analytical contributions resulting from this research. The first is a method to evaluate the safety benefits of preemption based on conflict analysis. The second is an algorithm, suitable for use in future traffic simulation models, that incorporates the impact of auto driver behavior into the determination of travel time savings for emergency vehicles operating on signalized arterial roadways. These two analytical methods are a foundation for future research that seeks to overcome the principal weakness of current EV preemption evaluation. Current methods, which rely on modeling and simulation tools, do not consider the unique auto driver behaviors observed when emergency vehicles are present. This research capitalizes on data collected during a field operational test in Northern Virginia, which included field observations of emergency vehicles traversing signalized intersections under a wide variety of geometric, traffic flow, and signal operating conditions. The methods provide a means to quantify the role of EV preemption in reducing the number and severity of conflict points and the delay experienced at signalized intersections. This forms a critical basis for developing deployment and operational guidelines, and eventually, warrants. / Ph. D.

Driver violations of traffic signals are a major cause of intersection vehicle crashes. The duration of yellow intervals is highly associated with driver yellow/red time stopping behavior. Rainy weather and wet pavement surface conditions may result in changes in both driver behavior and vehicle performance. The research presented in this thesis quantifies the impact of wet pavement surface and rainy weather conditions on driver perception-reaction times (PRTs) and deceleration levels, which are used in statistical models for the design of yellow intervals. A new dataset with a total of 648 stop-run records were collected as part of the research effort during rainy weather and wet pavement surface conditions at the Virginia Department of Transportation's Smart Road facility. This experiment was conducted at a 72.4 km/h (45 mi/h) approach speed where participant drivers encountered a yellow indication initiation. The participant drivers were randomly selected in different age groups (under 40 years old, 40 to 59 years old, and 60 years of age or older) and genders (female and male). Combined with an existing dataset that was collected by the same research group under clear weather conditions during the summer of 2008, statistical models for driver PRT and deceleration levels are developed, considering roadway surface and environmental parameters, driver attributes (age and gender), roadway grade, and time to the intersection at the onset of yellow. Using the state-of-the-practice procedures with the modeled PRT and deceleration levels, inclement weather yellow timings are then developed as a function of different factors (e.g., driver age/gender, roadway grade, speed limits, and precipitation levels). The results indicate that an increase in the duration of change interval is required for wet roadway surface and rainy weather conditions. Lookup tables are developed with different reliability levels to provide practical guidelines for the design of yellow signal timings in wet and rainy weather conditions. These recommended change durations can be integrated within the Vehicle Infrastructure Integration (VII) initiative to provide customizable driver warnings prior to a transition to a red indication. / Master of Science

Signal Replacement decisions are often made based on the experience of the Traffic Engineers. These decisions are made while considering the deployment time of the system, the new technology available, and the performance of the system in the given location. However, there is no set of proper guidelines or methods which can quantify the system replacement decision in large scale projects. This thesis presents a methodology that can be applied to determine optimal migration plans for traffic signal controllers. A Multi-Criteria Decision Making technique has been adopted to evaluate various traffic signal controllers. Various controller manuals were studied and information was obtained from the vendors of the controllers. In addition to that, Geographic Information System (GIS) has been used as a tool to evaluate and identify the areas where the traffic signal controllers have to be replaced first. The study considers the budget constraints and the benefits that can be obtained by the replacement of the controllers. This thesis presents the Methodology adopted for the Migration Plan and a case study implementation on the Northern Virginia Region. Finally it presents the conclusions drawn from the research with insights into the scope for further research. / Master of Science

Traffic congestion negatively affects traveler mobility and air quality. Stop and go vehicular movements associated with traffic jams typically result in higher fuel consumption levels compared to cruising at a constant speed. The first objective in the dissertation is to investigate the spatial relationship between air quality and traffic flow patterns. We developed and applied a recursive Bayesian estimation algorithm to estimate the source location (associated with traffic jam) of an airborne contaminant (aerosol) in a simulation environment. This algorithm was compared to the gradient descent algorithm and an extended Kalman filter algorithm. Results suggest that Bayesian estimation is less sensitive to the choice of the initial state and to the plume dispersion model. Consequently, Bayesian estimation was implemented to identify the location (correlated with traffic flows) of the aerosol (soot) that can be attributed to traffic in the vicinity of the Old Dominion University campus, using data collected from a remote sensing system. Results show that the source location of soot pollution is located at congested intersections, which demonstrate that air quality is correlated with traffic flows and congestion caused by signalized intersections. Sustainable mobility can help reduce traffic congestion and vehicle emissions, and thus, optimizing the performance of available infrastructure via advanced traffic signal controllers has become increasingly appealing. The second objective in the dissertation is to develop a novel de-centralized traffic signal controller, achieved using a Nash bargaining game-theoretic framework, that operates a flexible phasing sequence and free cycle length to adapt to dynamic changes in traffic demand levels. The developed controller was implemented and tested in the INTEGRATION microscopic traffic assignment and simulation software. The proposed controller was compared to the operation of an optimum fixed-time coordinated plan, an actuated controller, a centralized adaptive phase split controller, a decentralized phase split and cycle length controller, and a fully coordinated adaptive phase split, cycle length, and offset optimization controller to evaluate its performance. Testing was initially conducted on an isolated intersection, showing a 77% reduction in queue length, a 17% reduction in vehicle emission levels, and a 64% reduction in total delay. In addition, the developed controller was tested on an arterial network producing statistically significant reductions in total delay ranging between 36% and 67% and vehicle emissions reductions ranging between 6% and 13%. Analysis of variance, Tukey, and pairwise comparison tests were conducted to establish the significance of the proposed controller. Moreover, the controller was tested on a network of 38 intersections producing significant reduction in the travel time by 23.6%, a reduction in the queue length by 37.6%, and a reduction in CO2 emissions by 10.4%. Finally, the controller was tested on the Los Angeles downtown network composed of 457 signalized intersections, producing a 35% reduction in travel time, a 54.7% reduction in queue length, and a 10% reduction in the CO2 emissions. The results demonstrate that the proposed decentralized controller produces major improvements over other state-of-the-art centralized and de-centralized controllers. The proposed controller is capable of alleviating congestion as well as reducing emissions and enhancing air quality. / PHD / Traffic congestion affects traveler mobility and also has an impact on air quality, and consequently, on public health. Stop-and-go driving, which is typically associated with traffic jams, results in increased fuel consumption when compared to cruising at a constant speed. This in turn contributes to the amount of vehicle emissions that create air pollution, which contributes to global warming. Consequently, studying the spatial relationships between air quality and traffic flow patterns is directly related to enhancing air quality, as improving these patterns can reduce traffic congestion. The first objective in this dissertation is to investigate the spatial relationship between air quality and traffic flow patterns. We developed and applied a recursive Bayesian estimation algorithm to estimate the source location of an airborne contaminant (aerosol) in a simulation environment. This algorithm was compared to the gradient descent algorithm and the extended Kalman filter. Results suggest that Bayesian estimation is less sensitive to the choice of the initial state and to the plume dispersion model when compared to the other two approaches. Consequently, an experimental investigation using Bayesian estimation was conducted to identify the location (correlated with traffic flows) of the aerosol (soot) that can be attributed to traffic in the vicinity of the Old Dominion University campus, using data collected from a remote sensing system (a compact light detection and ranging [LiDAR] system). The results show that the location of soot pollution in the study area is located at congested intersections, which demonstrates that air quality is correlated with traffic flows and congestion caused by signalized intersections. Sustainable mobility could enhance air quality and alleviate congestion. Accordingly, optimizing the utilization of the available infrastructure using advanced traffic signal controllers has become necessary to mitigate traffic congestion in a world with growing pressure on financial and physical resources. The second objective in the dissertation is to develop a novel de-centralized traffic signal controller that is achieved using a Nash bargaining game-theoretic framework. This framework has a flexible phasing sequence and free cycle length, and thus can adapt to dynamic changes in traffic demand. The controller was implemented and evaluated using the INTEGRATION microscopic traffic assignment and simulation software. The proposed controller was tested and compared to state-of-the-art isolated and coordinated traffic signal controllers. The proposed controller was tested on an isolated intersection, producing a reduction in the queue length ranging from 58% to 77%, and a reduction in vehicle emission levels ranging from 6% to 17%. In the case of the arterial testing, the controller was compared to an optimum fixed-time coordinated plan, an actuated controller, a centralized adaptive phase split controller, a decentralized phase split and cycle length controller, and a fully coordinated adaptive phase split, cycle length, and offset optimization controller to evaluate its performance. On the arterial network, the proposed controller produced reductions in the total delay ranging from 36% to 67%, and a reduction in vehicle emissions ranging from 6% to 13%. Statistical tests show that the proposed controller produces major improvements over other state-of-the-art centralized and de-centralized controllers. In the domain of large scale networks, simulations were conducted on the town of Blacksburg, Virginia composed of 38 signalized intersections. The results show significant reductions on the intersection approaches with travel time savings of 23.6%, a reduction in the average queue length of 37.6%, a reduction in the average number of vehicle stops of 23.6%, a reduction in CO₂ emissions of 10.4%, a reduction in the fuel consumption of 9.8%, and a reduction in NO<sub>X<\sub> emissions of 5.4%. In addition, the proposed controller was tested on downtown Los Angles, California, including the most congested downtown area, which has 457 signalized intersections, and compared to the performance of a decentralized phase split and cycle length controller. The results show significant reductions on the intersections links in the average travel time of 35.1%, a reduction in the average queue length of 54.7%, a reduction in the average number of stops of 44%, a reduction in CO₂ emissions of 10%, a reduction in the fuel consumption of 10%, and a reduction in NO<sub>X<\sub> emissions of 11.7%. Furthermore, simulations were conducted at lower traffic flow levels and showed significant reductions on the network performance producing reductions in vehicle average total delay of 36.7%, a reduction in the stopped delay by 90.2%, and a reduction in the average number of stops by 35%, over a decentralized phase split and cycle length controller. The results demonstrate that the proposed decentralized controller reduces traffic congestion, fuel consumption and vehicle emission levels, and produces major improvements over other state-of-the-art centralized and de-centralized controllers.

Motivated by recent advances in vehicle positioning and vehicle-to-infrastructure (V2I) communication, traffic signal controllers are able to make smarter decisions. Most of the current state-of-the-practice signal priority control systems aim to provide priority for only one mode or based on first-come-first-served logic. Consideration of priority control in a more general framework allows for several different modes of travelers to request priority at any time from any approach and for other traffic control operating principles, such as coordination, to be considered within an integrated signal timing framework. This leads to provision of priority to connected priority eligible vehicles with minimum negative impact on regular vehicles. This dissertation focuses on providing a real-time decision making framework for multi modal traffic signal control that considers several transportation modes in a unified framework using Connected Vehicle (CV) technologies. The unified framework is based on a systems architecture for CVs that is applicable in both simulated and real world (field) testing conditions. The system architecture is used to design both hardware-in-the-loop and software-in-the-loop CV simulation environment. A real-time priority control optimization model and an implementation algorithm are developed using priority eligible vehicles data. The optimization model is extended to include signal coordination concepts. As the penetration rate of the CVs increases, the ability to predict the queue more accurately increases. It is shown that accurate queue prediction improves the performance of the optimization model in reducing priority eligible vehicles delay. The model is generalized to consider regular CVs as well as priority vehicles and coordination priority requests in a unified mathematical model. It is shown than the model can react properly to the decision makers' modal preferences.

Enabling vehicles to preempt the normal operation of traffic signals has the potential to improve the safety and efficiency of both the requesting vehicle and all of the other vehicles. Little is known about which strategy is the most effective to exit from preemption control and transition back to the traffic signals normal timing plan. Common among these traffic signal transition strategies is the method of either increasing or decreasing the cycle length of the signal timing plan, as the process followed to return to the coordination point of the effected signal timing plan, to coordinate its operation with adjacent traffic signals. This research evaluates commonly available transition strategies: best way, long, short, and hold strategies. The major contribution of this research is enhancing the methodology to evaluate the impacts of using these alternative transition strategies. Part of this methodology consists of the "software-in-the-loop" simulation tool which replicates the stochastic characteristics of traffic flow under different traffic volume levels. This tool combines the software from a traffic signal controller (Gardner NextPhase Suitcase Tester, version 1.4B) with a microscopic traffic simulation model (CORSIM, TSIS 5.2 beta version). The research concludes that a statistically significant interaction exists between traffic volume levels and traffic signal transition strategies. This interaction eliminates the ability to determine the isolated effects of either the transition strategies on average travel delay and average travel time, or the effects of changes in traffic volume levels on average travel delay and average travel time. Conclusions, however, could be drawn on the performance of different transition strategies for specific traffic volume levels. As a result, selecting the most effective transition strategy needs to be based on the traffic volume levels and conditions specific to each traffic signal or series of coordinated traffic signals. The research also concludes that for the base traffic volume and a 40% increase in traffic volume, the most effective transition strategies are the best way, long or hold alternatives. The best way was the most effective transition strategy for a 20% increase in traffic volume. The least effective strategy is the short transition strategy for both the base and 40% increase in traffic volume, and the long and short for a 20% increase in traffic volume. Further research needs to be conducted to assess the performance of different transition strategies in returning to coordinated operation under higher levels of traffic volume (e.g., approaching or exceeding congested flow regime), with varying cycle lengths, with different signal timing plans, and when different roadway geometric configurations (e.g., turn lanes, length of turn lanes, number of lanes, spacing between intersections) are present. / Ph. D.

Increasing congestion and environmental concerns have evoked an interest in promoting urban Public Transport (PT) the last decades. In 2012 the City of Stockholm adopted an “Urban mobility strategy” stating that public transport, cycling and walking should be prioritised over cars in central Stockholm. One of the most important factors influencing the modal choice is the travel time ratio between car and PT travel. According to earlier studies Public Transport Traffic Signal Priority (PTSP) can reduce travel times for public transport with only small negative impacts on other traffic. Conditional PTSP can also help to regulate the PT service. Thus PTSP may support drivers’ decision to change travel mode from car to PT, thus supporting adopted policy goals. Conventional control strategies for coordinated traffic signals have pre-set timings based on traffic surveys. Some traffic adaptation based on real time detector actuations can also take place within the frames of the pre-set cycle time. PTSP changes the signal timings, within pre-set limits, when a PT vehicle is detected. Self-optimising control strategies use a traffic model to predict the traffic flows from traffic counts, and determine the signal changes in real-time by minimising a cost function including delay, number of stops etc. PTSP is included directly in the optimisation by giving PT vehicles a higher weight compared to cars. In this thesis the fundamentals of signal control theory are reviewed as well as unconditional and conditional PTSP criteria and strategies. A simulation based method for evaluation of impacts of different PTSP strategies in coordinated controlled traffic signals is implemented. The simulation setup includes Software-In-the-Loop (SIL) signal controller simulators running the same control logic as used in field. Such simulation models can be useful to test and fine tune PTSP before being implemented in field. Simulations with a SIL setup also enable comparisons of signal control strategies or systems on equal terms, not practically or economically possible in field studies. The implemented SIL simulation model was used to evaluate the impacts on buses and other traffic from the different PTSP functions used in the “PRIBUSS” PTSP method. Short green time extensions showed travel time reductions for buses, with almost no travel time increase for other traffic. Long green time extensions gave somewhat larger benefits for the buses, but more delay to other traffic. Red truncation gave less travel time savings to the prioritised buses and more extra delay for cross street traffic, compared to green extensions. Double red truncation and Extra phase showed some additional travel time savings to the buses, but had the largest negative impact on other traffic. A combination of PRIBUSS functions showed the best results. Depending on the structure of the signal coordination and the location of the bus stops different PTSP functions may be needed. Based on the conclusions from the evaluation of the different PRIBUSS functions a conditional “differential on-time-status” based PTSP strategy was proposed and tested in the SIL simulation environment. The proposed method is focusing on direct travel time savings as well as on reduced bus bunching. The two self-optimising signal control systems Utopia/Spot and ImFlow were tested, and their impacts were compared to conventional control including PTSP with the PRIBUSS method in a SIL simulation environment. The aim was to test if commercially available self-optimising control systems can reduce the overall delay per person by applying more sophisticated PTSP. Both systems reduced the delay for buses, cyclists and pedestrians at a cost of increased delay and increased number of stops compared to the existing conventional control used in field. The total delay for all road users was reduced substantially. / Intresset för att påverka resvanorna i våra städer så att kollektivtrafikandelen ökar har växt de senaste decennierna på grund av en ökad trängsel i gatunätet samt ökad miljömedvetenhet. Stockholms stad har antagit ”Framkomlighetsstrategin” som innebär att kollektivtrafik, gång och cykel ska prioriteras framför biltrafik i centrala Stockholm. En av de faktorer som påverkar färdmedelsvalet mest är restidskvoten mellan bil och kollektivtrafik. Tidigare studier har visat att kollektivtrafikprioritering i trafiksignaler kan minska körtiden för kollektivtrafiken väsentligt, med små eller inga negativa konsekvenser för övrig trafik. Villkorlig prioritering kan dessutom förbättra kollektivtrafikens regularitet. Kollektivtrafikprioritering i trafiksignaler kan på så sätt hjälpa till att förbättra kollektivtrafikens attraktivitet och därigenom öka kollektivtrafikandelen. Samordnade trafiksignaler styrda med konventionell teknik har en fast tidsättning framtagen med insamlade historiska trafikdata som grund. Viss trafikstyrning kan åstadkommas inom ramen för den fasta omloppstiden. Om bussprioritering finns ändras signalväxlingen av prioriteringsfunktionerna när en buss detekteras, inom vissa begränsningar för att hålla ihop det samordnade systemet. Självoptimerande signalstyrning bygger på att fordonsrörelserna genom systemet predikteras med en trafikmodell utifrån trafikräkningar med detektorer. Signaltidsättningen bestäms sedan i realtid genom att minimera en kostnadsfunktion som innehåller fördröjning, antal stopp mm. för de modellerade fordonsrörelserna. Kollektivtrafiken prioriteras genom att dess fordon detekteras separat från övrig trafik, och ges en högre vikt i optimeringen av signaltidssättningen. I denna avhandling beskrivs de teoretiska grunderna för trafiksignalstyrning, liksom metoder och kriterier för villkorlig och ovillkorlig signalprioritering av kollektivtrafik. En simuleringsbaserad metod för att utvärdera effekterna av olika signalprioritering har implementerats. Denna använder styrapparatsimulatorer med samma programmering som styrapparaterna på gatan, inklusive prioriteringsfunktioner. Sådana simuleringar kan vara ett användbart verktyg för att justera in prioriteringsfunktionerna innan dessa implementeras i signalstyrningen på gatan. Simuleringar med styrapparatsimulatorer möjliggör också jämförelser av olika styrstrategier under kontrollerade förhållanden som inte vore praktiskt, eller ekonomiskt möjliga att genomföra i fält. I den framtagna simuleringsmiljön har effekterna av de olika prioriteringsfunktionerna i PRIBUSS utvärderats. Korta (maxtids-)förlängningar gav körtidsvinster för bussar och knappast några restidsförsämringar för övrig trafik. Långa förlängningar (fråntidsförlängning och återtagen start) gav ytterligare restidsvinster för busstrafiken, men ökad fördröjning för övrig trafik. Avkortning gav, jämfört med förlängningar, mindre restidsvinster för busstrafiken och mer störning för övrig trafik. De mer komplicerade funktionerna Dubbel avkortning och extrafas gav viss ytterligare restidsvinst för bussarna, men hade den största inverkan på övrig trafik. Bäst resultat uppkom dock med en kombination av PRIBUSS funktioner. Beroende på samordningens struktur och busshållplatsernas placering i förhållande till trafiksignalerna kan olika prioriteringsfunktioner ge större eller mindre nytta. Baserat på utvärderingen av de olika PRIBUSS funktionernas effekter på bussar och övrig trafik har en tidhållningsbaserad differentierad prioriteringsstrategi föreslagits, som förutom att skapa direkta restidvinster också försöker motverka ihopklumpning av bussar. Denna strategi har implementerats och testats i den framtagna simuleringsmiljön. Med hjälp av simuleringar har de självoptimerande signalstyrsystemen Utopia/Spot och ImFlow testats och jämförts med konventionell styrning, inklusive bussprioritering med PRIBUSS. Syftet med denna studie var att undersöka om fördröjningen per person i trafiknätet kan minskas genom bättre kollektivtrafikprioritering med hjälp av ett kommersiellt tillgängligt självoptimerande signalstyrsystem. De båda testade systemen gav minskad fördröjning för kollektivtrafik, gående och cyklister, men ökad fördröjning och antal stopp för biltrafik. Den totala fördröjningen minskades betydligt med de båda testade självoptimerande signalstyrsystemen. / <p>QC 20140513</p>

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.

Exclusive bus lanes and the Transit Signal Priority are often not effective in saturated peak-traffic conditions. An alternative way of providing priority for transit can be queue jumpers, which allows buses to bypass and then cut out in front of waiting queue by getting an early green signal. Utah Transit authority deployed Bus Rapid Transit system at Salt Lake County, Utah along W 3500 S. This research evaluates the impacts of queue jumpers with TSP on Bus Rapid Transit (BRT) and private vehicular traffic. Four VISSIM models were developed for analysis : Basic scenario, no TSP with queue jumpers, TSP with no queue jumbers, and TSP with queue jumpers. In TQ scenario travel time was reduced between 13.2-19.82% with respect to basic scenario. At the same time, travel time of private traffic increased very little 0.38-3.28%. Two TSP strategies : green extension and red truncation are implemented in this research work. / by R.M. Zahid Reza. / Thesis (M.S.C.S.)--Florida Atlantic University, 2012. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

Os planos de coordenação semafórica são reconhecidamente eficientes para promover a fluidez das correntes de tráfego e melhorar a qualidade operacional do sistema viário. Portanto, os técnicos responsáveis pela gestão do tráfego deveriam, sempre que possível, adotar métodos para a definição adequada das defasagens, utilizando ferramentas que auxiliem na decisão das operações. Porém, uma pesquisa realizada em cidades das regiões Sul e Sudeste sobre as estratégias de coordenação empregadas, demonstrou especialmente para municípios de porte médio que somente 13% utilizam ferramentas computacionais para prover planos de coordenação nos semáforos monitorados por centrais. Para os demais corredores semaforizados, cerca de 27% utilizam o diagrama espaço-tempo, 36% realizam ajustes locais através da observação do tráfego, 14% utilizam veículo-teste e 23% não adotam esquemas de coordenação. O objetivo desta dissertação é avaliar a eficiência de dois programas de coordenação semafórica que poderiam ser utilizados em cidades que não dispõem de técnicas mais eficientes para definir os planos semafóricos. Uma revisão bibliográfica sobre os métodos mais conhecidos foi realizada, identificando que os programas disponíveis seguem três critérios distintos: a maximização da largura da banda verde; a minimização dos atrasos e paradas; e a combinação das vantagens de ambos os critérios. O primeiro programa, cujo nome é SBAND, consiste em uma implementação computacional do critério de maximização de banda baseada no método half-integer synchronization, proposto por Morgan e Little. O segundo programa é o simulador INTEGRATION, que coordena semáforos baseado no critério de minimização de atrasos e paradas. Com esses programas, foram gerados planos semafóricos para diversas condições de tráfego em vias arteriais de Londrina e São Carlos, simuladas com o INTEGRATION. A análise das medidas de desempenho - tempo de percurso, atraso médio e número médio de paradas - indica que é possível planos semafóricos melhores do que aqueles em vigência nos corredores analisados, com redução dos valores médios destas medidas. A análise sugere que o programa INTEGRATION é mais recomendado para os casos em que o fluxo de veículos é elevado e semelhante na via principal e nas transversais, enquanto o programa SBAND é recomendado quando a via principal apresenta volume de tráfego leve ou moderado, maior do que nas vias secundárias. / Traffic signal synchronization strategies are useful to improve traffic flow mobility and level of service of arterial streets. Therefore, technicians in charge of management of the traffic system operation should take advantage of the benefits of these tools, as always as possible, in order to define the most adequate traffic signal offsets. However, interviews carried on mid-size cities of southern and southwestern regions of Brazil indicated that only 13% of these cities define plans for traffic signal networks, controlled by a central control room, based on any type of traffic signal coordination software. For non-controlled streets, 27% of the cities define offsets using the traditional space-time diagram, 36% make local adjustments in a trial and error basis, 14% use a test vehicle and the remaining 23% do not use any strategy for synchronization. Based on these findings, the objective of this master thesis is to assess the performance of two traffic signal synchronization tools that might be used in cities which do not make use of more efficient techniques to define signal plans. Literature review indicates that the available softwares are developed according to three distinct approaches: bandwidth maximization, minimization of delays and stops and combination of both previous methods. The first software tested, named SBAND, is based on the Morgan and Little half-integer synchronization algorithm, which maximizes bandwidth of signalized arterial streets. The second software is the INTEGRATION traffic simulation tool, which synchronizes traffic signals minimizing delays and stops. Different signal plans were defined by means of these two softwares, for several traffic conditions in arterial streets of Londrina and São Carlos, and simulated with INTEGRATION. The analysis of measures of effectiveness generated on the simulations – travel time, average delay and average number of stops – indicate that is possible to obtain better traffic signal plans, with reduction on the measures of effectiveness for the plans currently adopted for these arterials. The results also suggest that INTEGRATION is more recommended for scenarios when traffic flow on principal arterials is heavy and similar to the traffic on secondary streets, while SBAND is recommended for light to moderate traffic flow on main street, with through trips predominating and lighter traffic on secondary streets.