Overuse of the Interstate and National Highway Systems has led many urban freeways to suffer from recurrent congestion and high crash rates. One method of ameliorating these problems is through the use of Active Traffic Management (ATM). Within ATM, the practice of speed harmonization is well suited to improving safety and reducing delay. In this study, speed harmonization is applied to a segment of Interstate Highway 35, just south of downtown Austin, Texas. First, the need for congestion and safety improvements will be established. Then, the framework of a speed harmonization system will be developed through a synthesis of speed harmonization best practice. Next, the speed harmonization framework will be evaluated for its impact on efficiency through the development of before and after micro-simulation models. Finally, the trajectory files generated from simulation will be analyzed using surrogate safety measures to assess the safety impact of the proposed speed harmonization system. / text

Esta dissertação apresenta uma análise da modelagem de estratégias de gerenciamento ativo de tráfego para um estudo de caso de uma autoestrada brasileira. O gerenciamento ativo de tráfego busca de uma forma eficiente melhorar as condições do tráfego durante horários e locais mais congestionados. Esta abordagem consiste em uma combinação de estratégias que aperfeiçoam a operação da infraestrutura existente. Esta dissertação é composta de três artigos, nos quais são apresentados: (i) as tendências atuais de gerenciamento ativo de tráfego, discutindo seus propósitos, definições, benefícios e tendências em novos projetos, (ii) uma análise dos dados coletados no trecho em estudo, que servem de base para a calibração e validação do modelo de simulação, (iii) calibração no software VISSIM do segmento de autoestrada estudado para reproduzir os comportamentos observados em campo, incluindo as velocidades, parâmetros de car following e de troca de faixas e (iv) uma avaliação e quantificação da eficácia da modelagem das estratégias de gerenciamento ativo de tráfego para o trecho em estudo. A calibração do modelo foi um estágio importante da modelagem, pois o trecho modelado possui características especiais quanto ao comportamento do tráfego. Assim, o simular não é capaz de reproduzir naturalmente o trecho em estudo com seus parâmetros default, fazendo-se necessário um esforço de calibração para representar de forma satisfatória as características presentes na rodovia. O tempo de headway e a distância mínima entre os veículos, a agressividade nas trocas de faixa, e nas acelerações e desacelerações foram os parâmetros com maior influência na modelagem. Dados coletados através de filmagens e de coletores com laços indutivos foram usados para calibrar e validar o modelo de simulação. As estratégias de gerenciamento ativo de tráfego empregadas na simulação foram a de harmonização da velocidade e a do uso temporário do acostamento. A modelagem demonstrou que o gerenciamento ativo de tráfego tem impactos positivos na operação do tráfego. Redução de headways, redução nos tempos médios de viagem, na variabilidade dos tempos de viagem e no número de trocas de faixa foram benefícios mensurados. Com o uso das estratégias houve também redução do tempo em que o fluxo da via permanece em colapso, aumentando a eficiência do trecho. / This paper presents an analysis of modeling strategies for active traffic management to a case study of a Brazilian highway. The active traffic management search for an efficient way to improve traffic conditions during the most congested times and locations. This approach consists of a combination of strategies that improve the operation of existing infrastructure. This dissertation consists of three articles in which they are presented: (i) the current trends of active traffic management, discussing its purpose, definitions, benefits and trends in new projects, (ii) an analysis of data collected in the stretch under study, serving as a basis for calibration and validation of the simulation model, (iii) calibration of the VISSIM software for a studied freeway segment to reproduce the behaviors observed in the field, including speeds, car following parameters and lane changes and ( iv) an assessment and quantification of the effectiveness of modeling strategies for active traffic management to the stretch under study. The calibration of the model was an important stage of the modeling, because the modeled stretch has special characteristics as the traffic behavior. Thus, the simulator is not able to naturally simulate the performance under study with its default parameters, making it necessary a calibration effort to represent satisfactorily the features present on the highway. The headway time and the minimum distance between vehicles, aggressiveness in lane changes, and the acceleration and deceleration parameters were most influential in the model. Data collected through filming and collectors with inductive loops were used to calibrate and validate the simulation model. The active traffic management strategies assets employed in the simulation were the speed harmonization and temporary hard shoulder use. The modeling showed that the active traffic management has a positive impact on traffic operation. Reducing headways, reduction in average travel time, variability in travel times and the number of lane changes were measured benefits. With the use of strategies were also reduces the time in which the flow pathway remains collapsed, increasing the efficiency of the stretch.

Esta dissertação apresenta uma análise da modelagem de estratégias de gerenciamento ativo de tráfego para um estudo de caso de uma autoestrada brasileira. O gerenciamento ativo de tráfego busca de uma forma eficiente melhorar as condições do tráfego durante horários e locais mais congestionados. Esta abordagem consiste em uma combinação de estratégias que aperfeiçoam a operação da infraestrutura existente. Esta dissertação é composta de três artigos, nos quais são apresentados: (i) as tendências atuais de gerenciamento ativo de tráfego, discutindo seus propósitos, definições, benefícios e tendências em novos projetos, (ii) uma análise dos dados coletados no trecho em estudo, que servem de base para a calibração e validação do modelo de simulação, (iii) calibração no software VISSIM do segmento de autoestrada estudado para reproduzir os comportamentos observados em campo, incluindo as velocidades, parâmetros de car following e de troca de faixas e (iv) uma avaliação e quantificação da eficácia da modelagem das estratégias de gerenciamento ativo de tráfego para o trecho em estudo. A calibração do modelo foi um estágio importante da modelagem, pois o trecho modelado possui características especiais quanto ao comportamento do tráfego. Assim, o simular não é capaz de reproduzir naturalmente o trecho em estudo com seus parâmetros default, fazendo-se necessário um esforço de calibração para representar de forma satisfatória as características presentes na rodovia. O tempo de headway e a distância mínima entre os veículos, a agressividade nas trocas de faixa, e nas acelerações e desacelerações foram os parâmetros com maior influência na modelagem. Dados coletados através de filmagens e de coletores com laços indutivos foram usados para calibrar e validar o modelo de simulação. As estratégias de gerenciamento ativo de tráfego empregadas na simulação foram a de harmonização da velocidade e a do uso temporário do acostamento. A modelagem demonstrou que o gerenciamento ativo de tráfego tem impactos positivos na operação do tráfego. Redução de headways, redução nos tempos médios de viagem, na variabilidade dos tempos de viagem e no número de trocas de faixa foram benefícios mensurados. Com o uso das estratégias houve também redução do tempo em que o fluxo da via permanece em colapso, aumentando a eficiência do trecho. / This paper presents an analysis of modeling strategies for active traffic management to a case study of a Brazilian highway. The active traffic management search for an efficient way to improve traffic conditions during the most congested times and locations. This approach consists of a combination of strategies that improve the operation of existing infrastructure. This dissertation consists of three articles in which they are presented: (i) the current trends of active traffic management, discussing its purpose, definitions, benefits and trends in new projects, (ii) an analysis of data collected in the stretch under study, serving as a basis for calibration and validation of the simulation model, (iii) calibration of the VISSIM software for a studied freeway segment to reproduce the behaviors observed in the field, including speeds, car following parameters and lane changes and ( iv) an assessment and quantification of the effectiveness of modeling strategies for active traffic management to the stretch under study. The calibration of the model was an important stage of the modeling, because the modeled stretch has special characteristics as the traffic behavior. Thus, the simulator is not able to naturally simulate the performance under study with its default parameters, making it necessary a calibration effort to represent satisfactorily the features present on the highway. The headway time and the minimum distance between vehicles, aggressiveness in lane changes, and the acceleration and deceleration parameters were most influential in the model. Data collected through filming and collectors with inductive loops were used to calibrate and validate the simulation model. The active traffic management strategies assets employed in the simulation were the speed harmonization and temporary hard shoulder use. The modeling showed that the active traffic management has a positive impact on traffic operation. Reducing headways, reduction in average travel time, variability in travel times and the number of lane changes were measured benefits. With the use of strategies were also reduces the time in which the flow pathway remains collapsed, increasing the efficiency of the stretch.

Esta dissertação apresenta uma análise da modelagem de estratégias de gerenciamento ativo de tráfego para um estudo de caso de uma autoestrada brasileira. O gerenciamento ativo de tráfego busca de uma forma eficiente melhorar as condições do tráfego durante horários e locais mais congestionados. Esta abordagem consiste em uma combinação de estratégias que aperfeiçoam a operação da infraestrutura existente. Esta dissertação é composta de três artigos, nos quais são apresentados: (i) as tendências atuais de gerenciamento ativo de tráfego, discutindo seus propósitos, definições, benefícios e tendências em novos projetos, (ii) uma análise dos dados coletados no trecho em estudo, que servem de base para a calibração e validação do modelo de simulação, (iii) calibração no software VISSIM do segmento de autoestrada estudado para reproduzir os comportamentos observados em campo, incluindo as velocidades, parâmetros de car following e de troca de faixas e (iv) uma avaliação e quantificação da eficácia da modelagem das estratégias de gerenciamento ativo de tráfego para o trecho em estudo. A calibração do modelo foi um estágio importante da modelagem, pois o trecho modelado possui características especiais quanto ao comportamento do tráfego. Assim, o simular não é capaz de reproduzir naturalmente o trecho em estudo com seus parâmetros default, fazendo-se necessário um esforço de calibração para representar de forma satisfatória as características presentes na rodovia. O tempo de headway e a distância mínima entre os veículos, a agressividade nas trocas de faixa, e nas acelerações e desacelerações foram os parâmetros com maior influência na modelagem. Dados coletados através de filmagens e de coletores com laços indutivos foram usados para calibrar e validar o modelo de simulação. As estratégias de gerenciamento ativo de tráfego empregadas na simulação foram a de harmonização da velocidade e a do uso temporário do acostamento. A modelagem demonstrou que o gerenciamento ativo de tráfego tem impactos positivos na operação do tráfego. Redução de headways, redução nos tempos médios de viagem, na variabilidade dos tempos de viagem e no número de trocas de faixa foram benefícios mensurados. Com o uso das estratégias houve também redução do tempo em que o fluxo da via permanece em colapso, aumentando a eficiência do trecho. / This paper presents an analysis of modeling strategies for active traffic management to a case study of a Brazilian highway. The active traffic management search for an efficient way to improve traffic conditions during the most congested times and locations. This approach consists of a combination of strategies that improve the operation of existing infrastructure. This dissertation consists of three articles in which they are presented: (i) the current trends of active traffic management, discussing its purpose, definitions, benefits and trends in new projects, (ii) an analysis of data collected in the stretch under study, serving as a basis for calibration and validation of the simulation model, (iii) calibration of the VISSIM software for a studied freeway segment to reproduce the behaviors observed in the field, including speeds, car following parameters and lane changes and ( iv) an assessment and quantification of the effectiveness of modeling strategies for active traffic management to the stretch under study. The calibration of the model was an important stage of the modeling, because the modeled stretch has special characteristics as the traffic behavior. Thus, the simulator is not able to naturally simulate the performance under study with its default parameters, making it necessary a calibration effort to represent satisfactorily the features present on the highway. The headway time and the minimum distance between vehicles, aggressiveness in lane changes, and the acceleration and deceleration parameters were most influential in the model. Data collected through filming and collectors with inductive loops were used to calibrate and validate the simulation model. The active traffic management strategies assets employed in the simulation were the speed harmonization and temporary hard shoulder use. The modeling showed that the active traffic management has a positive impact on traffic operation. Reducing headways, reduction in average travel time, variability in travel times and the number of lane changes were measured benefits. With the use of strategies were also reduces the time in which the flow pathway remains collapsed, increasing the efficiency of the stretch.

Traffic growth and limited roadway capacity decrease traveler mobility and increase traffic congestion and fuel consumption. Traffic managers employ various control techniques to mitigate the aforementioned problems. One well-known network-wide control strategy is perimeter control (or gating). Perimeter control is based on the Network Fundamental Diagram (NFD). NFD-based perimeter control techniques are used to solve congestion problems in transportation networks. One well-known method used in the literature is Proportional Integral Control (PIC). PIC solves the congestion problem, but suffers from sensitivity to parameter tuning and the need for model linearization. A weather-tuned perimeter control (WTPC) and a jam density-tuned perimeter controller (JTPC) were developed to cope with parameter sensitivity for different weather conditions and jam densities, respectively. In an attempt to overcome PIC problems, a sliding mode controller (SMC) was developed. SMC does not require model linearization and parameter tuning. It is also robust to varying demand patterns. SMC computes the flow that needs to enter a protected network and converts it to corresponding traffic signal timings to achieve the desired control strategies. Another approach to implementing the sliding mode controller is to control vehicle speeds on the links entering the protected network. Coupling speed harmonization (SH) with sliding mode control (SMC), an SMC-SH was developed and implemented in the INTEGRATION microscopic traffic simulator. The mentioned controllers are all tested on a mid-size grid network replicating downtown Washington DC. SMC-SH improved different performance metrics on the whole grid network compared to the no control case. Specifically, it improved average travel time, total delay, stopped delay, fuel consumption, CO2 emissions by 17.27%, 18.18%, 12.76%, 5.91%, and 7.04%, respectively. In order to test the SMC-SH on a real large-scale network, the downtown Los Angeles (LA) network is used. The LA network is known for its congested freeways, so a development of a Freeway-SMC-SH controller is performed and tested. It shows good results in improving the performance not only of freeways, but also the overall LA network performance. Particularly, the network-wide average travel time, total delay, stopped delay, fuel consumption and CO2 emissions improved with respect to the no control case by 12.17%, 20.67%, 39.58%, 2.6%, and 3.3%, respectively. An identification of a homogeneously congested area is needed to apply SMC-SH on LA roads (not freeways). The geographical self organizing maps (GeoSOM) clustering algorithm is applied and tested on the LA network. The clustering goal is to identify a geographically connected region with small density variance. GeoSOM is able to achieve that objective with better performance than the state-of-the-art Kmeans and DBSCAN clustering algorithms. The enhancements reached up to 15.15% for quantization error, 61.05% for spacial quantization error, and 43.96% for variance. Finally, the SMC-SH is tested on the protected region of the LA network identified by the GeoSOM algorithm. SMC-SH succeeds in improving network-wide vehicle travel time, total delay, stopped delay, fuel consumption and CO2 emissions by 6.25%, 9.4%, 16.47%, 1.7%, and 2.19%, respectively. / Doctor of Philosophy / Road congestion causes vehicular delays and increases travel time and fuel consumption. The goal of the research is to prevent or relieve traffic congestion in a network. That region that we attempt to address is termed the congested network or the protected network (PN). One way to solve the traffic jam problem is to set up gates on the PN borders so that the number of vehicles that enter the network is limited, and consequently traffic jams do not occur. However, the number of vehicles should not be limited too much to avoid overcrowding outside the PN. The developed controller calculates the right number of cars that should enter the network in order to improve the performance inside and outside the PN. The first way to apply the controller commands is to adjust traffic signal timings at the traffic signals located along the PN border. The second way (called SMC-SH) is to adjust the speed of the vehicles entering the network through these gates. In the first part of the work, all the controllers are implemented and tested in a mid-size grid network. In the second part of the work, the goal is to implement the controller on the real large-scale Los Angeles (LA) network. Since the LA network suffers from congestion on freeways, a freeway controller is developed and tested. It does not only succeed in reducing traffic jams on freeways, but also enhances the overall LA network traffic performance. In order to apply the SMC-SH controller on the LA network, we identify homogeneously congested regions. GeoSOM clustering is implemented to achieve this goal and compared to other clustering methods, and is shown to outperform them. Finally, the SMC-SH controller is tested on the congested region of LA, and succeeds in reducing travel time, total delay, and fuel consumption for the LA network.