Active traffic management is a hot topic for addressing issues of highway congestion. It is the use of intelligent transportation systems to provide real time traffic information on highway conditions. In Austin, the segment of Interstate 35 between Riverside Drive and State Highway 71 experiences both congestion and safety issues. This report provides an introduction into the application of active traffic management through the use of a proposed queue warning system in the area. First, select crash data on the region is highlighted to present the safety conditions, particularly the type of collision and crash severity involved. Next, a proposed queue warning system design is described. This includes a description of the equipment used, methodology for system deployment, and expected outcomes. Finally, a computer simulation testing the operational performance of the queue warning system is performed using VISSIM, and the results are reported. This report aims to demonstrate the role that queue warning system and active traffic management may play in addressing metropolitan traffic needs. / text

Increasing demand on freeway facilities is a major challenge facing urban areas in the United States and throughout the world. Active Traffic Management (ATM) strategies can be used to increase the performance of these facilities through improved operations without the significant expenditure associated with adding capacity. One ATM strategy that has been widely deployed in the current state of practice is ramp metering, which controls the traffic demand placed on a freeway. Merge control strategies are less prevalent and largely undeveloped. This study examines the recurrently congested northbound section of Interstate Highway 35 that approaches downtown Austin, Texas. Using the VISSIM microsimulation platform, a model of this segment was developed and calibrated to reflect current peak-hour congestion. Within this model, ramp metering and merge control technologies were implemented. The impacts on traffic throughput, speed and travel time for each of these proposed systems are evaluated. / text

Urban freeway demand that frequently exceeds capacity has caused many agencies to consider many options to reduce congestion. A series of solutions that falls under the Active Traffic Management (ATM) banner have shown promising potential. Perhaps the most popular ATM strategy is ramp metering. Ramp metering involves limiting the access of vehicles to freeways at an entrance ramp. By doing this, freeway throughput, speeds, and travel time reliability can be increased, while the number of traffic incidents can be decreased. This study examines the application of an innovative ramp metering strategy, Intersection Ramp Metering (IRM), at a section of Loop 1 in Austin, TX. IRM implements the ramp metering function at the intersection immediately upstream of the entrance ramp, rather than on the ramp itself. A microsimulation analysis of this application is performed in VISSIM, and the results confirm that freeway throughput (+10%), and system average travel time (-14%), can be improved, as well as several other performance measures. / 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.

Traditional crash frequency prediction models cannot capture the temporal effects of traffic characteristics due to the high level of data aggregation. Also, this approach is less suitable to address the crash risk for active traffic management strategies that typically operate for short-time intervals. Hence, this research proposes short-term crash prediction models for traffic management strategies such as Variable Speed Limit (VSL)/Variable Advisory Speed (VAS), and Part-time Shoulder Use (PTSU). By using high-resolution traffic detectors and VSL/VAS operational data, short-term Safety Performance Functions (SPFs) are estimated at weekday hourly and peak period aggregation levels. The results indicate that the short-term SPFs could capture various crash contributing factors and safety aspects of VSL/VAS more effectively than the traditional highly aggregated Average Annual Daily Traffic (AADT)-based approach. The study also investigates the safety effectiveness of VSL/VAS for different types and severity levels of traffic crashes. The results specify that the VSL/VAS system is effective in reducing rear-end crashes in the Multivariate Poisson Lognormal (MVPLN) crash type model as well as Property Damage Only (PDO) and C (non-incapacitating) crashes in the MVPLN crash severity model. Recommendations include deploying the VSL/VAS system combined with other traffic management strategies, strong enforcement policies, and drivers' compliance to increase the effectiveness of this strategy. Further, this research estimates the Random Parameters Negative Binomial-Lindley (RPNB-L) model for PTSU sections and provides valuable insights on potential crash contributing factors related to PTSU operation, design elements, and high-risk areas. Last, the study proposes a novel integrated crash prediction approach for freeway sections with combined traffic management strategies. By incorporating historical safety conditions from SPFs, real-time crash prediction performance could be improved as a part of proactive traffic management systems. The findings could assist transportation agencies, policymakers, and practitioners in taking appropriate countermeasures for preventing and reducing crash occurrence by incorporating safety aspects while implementing traffic management strategies on freeways.

High speed facilities are considered the backbone of any successful transportation system; Interstates, freeways, and expressways carry the majority of daily trips on the transportation network. Although these types of roads are relatively considered the safest among other types of roads, they still experience many crashes, many of which are severe, which not only affect human lives but also can have tremendous economical and social impacts. These facts signify the necessity of enhancing the safety of these high speed facilities to ensure better and efficient operation. Safety problems could be assessed through several approaches that can help in mitigating the crash risk on long and short term basis. Therefore, the main focus of the research in this dissertation is to provide a framework of risk assessment to promote safety and enhance mobility on freeways and expressways. Multi-level Safety Performance Functions (SPFs) were developed at the aggregate level using historical crash data and the corresponding exposure and risk factors to identify and rank sites with promise (hot-spots). Additionally, SPFs were developed at the disaggregate level utilizing real-time weather data collected from meteorological stations located at the freeway section as well as traffic flow parameters collected from different detection systems such as Automatic Vehicle Identification (AVI) and Remote Traffic Microwave Sensors (RTMS). These disaggregate SPFs can identify real-time risks due to turbulent traffic conditions and their interactions with other risk factors. In this study, two main datasets were obtained from two different regions. Those datasets comprise historical crash data, roadway geometrical characteristics, aggregate weather and traffic parameters as well as real-time weather and traffic data. iii At the aggregate level, Bayesian hierarchical models with spatial and random effects were compared to Poisson models to examine the safety effects of roadway geometrics on crash occurrence along freeway sections that feature mountainous terrain and adverse weather. At the disaggregate level; a main framework of a proactive safety management system using traffic data collected from AVI and RTMS, real-time weather and geometrical characteristics was provided. Different statistical techniques were implemented. These techniques ranged from classical frequentist classification approaches to explain the relationship between an event (crash) occurring at a given time and a set of risk factors in real time to other more advanced models. Bayesian statistics with updating approach to update beliefs about the behavior of the parameter with prior knowledge in order to achieve more reliable estimation was implemented. Also a relatively recent and promising Machine Learning technique (Stochastic Gradient Boosting) was utilized to calibrate several models utilizing different datasets collected from mixed detection systems as well as real-time meteorological stations. The results from this study suggest that both levels of analyses are important, the aggregate level helps in providing good understanding of different safety problems, and developing policies and countermeasures to reduce the number of crashes in total. At the disaggregate level, real-time safety functions help toward more proactive traffic management system that will not only enhance the performance of the high speed facilities and the whole traffic network but also provide safer mobility for people and goods. In general, the proposed multi-level analyses are useful in providing roadway authorities with detailed information on where countermeasures must be implemented and when resources should be devoted. The study also proves that traffic data collected from different detection systems could be a useful asset that should be utilized iv appropriately not only to alleviate traffic congestion but also to mitigate increased safety risks. The overall proposed framework can maximize the benefit of the existing archived data for freeway authorities as well as for road users.