The transportation routing map is increasingly used in various transportation network modeling applications such as vehicle navigation and traffic assignment modeling. A typical navigation GIS map contains all detailed road facility layers and may not be as computationally efficient as a lower-resolution map for path finding. A lower-resolution transportation routing map retains only route-finding related roadways and is efficient for path finding but may result in sub-optimal routes because of misclassification links. With the goal in balancing the traffic analysis requirement of intended application and computation requirements of transportation navigation and traffic assignment, the systematic abstraction of the lower-resolution transportation routing map from high resolution map is an important and non-trivial task. For vehicle navigation applications, the traffic analysis requirement is the shortest path quality. An innovative transportation routing map abstraction method or Connectivity Enhancement Algorithm (CEA) is proposed to deal with vehicle navigation application routing map abstraction. The algorithm starts from a low-resolution network and keeps updating the map by adding links and nodes when it processes each search set. The outcome of the algorithm is an abstract map that retains the original detailed map's hierarchical structure with quality topological connectivity at a significant computations saving. With the development of traffic assignment modeling, a detailed network is desired to describe the real world traffic network. It is the consensus that one should not directly apply a GIS map blind-sight without a systematic approach and unnecessarily overuse the network details causes excessive run time. The traffic analysis requirement of those applications is the dynamic user equilibrium (DUE) condition network performance is identical or near-identical with high resolution network. The lowest network resolution level that meets the requirements of emerging traffic analysis is not easy to determine. The proposed traffic analysis network abstraction method gives a solution for this problem. It is an iterative network abstraction approach and considers the link travel time with DUE traffic condition. The case study and numerical analysis prove that the two network abstraction methods are sound and promising. The transportation routing map abstraction method could detect most misclassification links and is robust for different network scales. The abstracted navigation map provides the identical or near-identical SP cost/travel time for any OD pair while the computation burden is much lighter than that on original map. In another hand, the case studies about the traffic analysis network abstraction tell that the method converges very quick and the rendered the abstracted network that has lowest resolution of network or least links and nodes but the DUE condition network performance or trips cost/travel time is much closer to that on the original map.

The cell transmission model (CTM) based single destination system optimal dynamic traffic assignment (SD-SO-DTA) model has been widely applied to situations such as mass evacuations on a transportation network. Although formulated as a linear programming (LP) model, embedded multi-period cell network representation yields an extremely large model for real-size networks. As a result, most of these models are not solvable using existing LP solvers. Solutions obtained by LP also involve holding vehicles at certain locations, violating CTM flow dynamics. This doctoral research is aimed at developing innovative algorithms that overcome both computational efficiency and solution realism issues. We first prove that the LP formulation of the SD-SO-DTA problem is equivalent to the earliest arrival flow (EAF), and then develop efficient algorithms to solve EAF. Two variants of the algorithm are developed under different model assumptions and network operating conditions. For the case of time-varying network parameters, we develop a network flow algorithm on a time-expanded network. The main challenge in this approach is to address the issue of having backward wave speed lower than forward wave speed. This situation leads to non-typical constraints involving coefficients with value of less than 1. In this dissertation we develop a new network algorithm to solve this problem in optimal, even with coefficients of value less than 1. Additionally, the developed approach solves for optimal flows that exhibit non-vehicle-holding properties, which is a major breakthrough compared to all existing solution techniques for SD-SODTA. For the case of time-invariant network parameters, we reduce the SD-SO-DTA to a standard EAF problem on a dynamic network, which is constructed on the original roadway network without dividing it into cells. We prove that the EAF under free flow status is one of the optimal solutions of SD-SO-DTA, if cell properties follow a trapezoidal/triangular fundamental diagram. We use chain flows obtained on a static network to induce dynamic flows, an approach applicable to large-scale networks. Another contribution of this research is to provide a simple and practical algorithm solving the EAF with multiple sources, which has been an active research area for many years. Most existing studies involve submodular function optimization as subroutines, and thus are not practical for real-life implementation. This study’s contribution in this regard is the development of a practical algorithm that avoids submodular function optimization. The main body of the given method is comprised of |S⁺| iterations of earliest arrival s - t flow computations, where |S⁺| is the number of sources. Numerical results show that our multi-source EAF algorithm solves the SD-SO-DTA problem with time-invariant parameters to optimum.

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.

Disasters, ranging from manmade events to natural occurrences, can happen anywhere on the planet, and their consequences can range from economic loss to catastrophic loss of life. Determining how the transportation system fares in the face of these disasters is important so that proper planning can take place before, rather than after, an event has happened. Modeling the transportation system gives operators the ability to discover bottlenecks, to determine the possible benefit of using lane reversals, and to find out the influence of evacuation speed on system efficiency. Models have already been created that are able to model some of these types of disasters with some level of accuracy. These models range from microscopic simulation to regional, macroscopic models. This research examines how an off-the-shelf regional modeling software package, TransCAD, can be used to model emergency evacuations. More specifically, this thesis presents four case studies involving three different types of disasters in Western Massachusetts. Because this research documents a first-hand experience using TransCAD in emergency evacuation planning, the results give regional modelers the ability to modify their models to fit their specific region. These case studies demonstrate how the modified inputs and existing portions of the four-step transportation planning model can be used in place of the usual data demands of the software. Dynamic traffic assignment is used in three of the case studies while the fourth case study uses static traffic assignment. An evaluation of the software package along with lessons learned is provided to measure the performance of the software.

Urban transportation networks are vulnerable to various incidents. In order to combat the negative effects due to incident-related congestion, various mitigation strategies have been proposed and implemented. The effectiveness of these congestion mitigation strategies for incident conditions largely depends on the accuracy of information regarding network conditions. Therefore, an efficient and accurate procedure to determine the link states, reflected by flows and density over time, is essential to incident management. This thesis presents a user equilibrium Dynamic Traffic Assignment (DTA) model that incorporates the Cell Transmission Model (CTM) to evaluate the temporal variation of flow and density over links, which reflect the link states of a transportation network. Encapsulation of the CTM equips the model with the capability of accepting inputs of incidents like duration and capacity reduction. Moreover, the proposed model is capable of handling multiple origin-destination (OD) pairs. By using this model, the temporal variation of flows over links can be readily evaluated. The visualized prediction of link density variations is used to investigate the link state relationships. By isolating the effects of an incident, the parallel routes of a specific OD pair display the relationship of substituting for each other, which is consistent with the general expectation regarding such parallel routes. A closer examination of the density variations confirms the existence of a substitution relationship between the unshared links of the two parallel routes. This information regarding link state relationship can be used as general guidance for incident management purposes. / Master of Science

This dissertation addresses the development and analysis of optimization models for evacuation planning. Specifically we consider the cases of large-scale regional evacuation using household vehicles and hospital evacuation. Since it is difficult to estimate the exact number of people evacuating, we first consider the case where the population size is uncertain. We review the methods studied in the literature, mainly the strategy of using a deterministic counterpart, i.e., a single deterministic parameter to represent the uncertain population, and we show that these methods are not very effective in generating a good traffic management strategy. We provide alternatives, where we describe some networks where an optimal policy exist independent of the demand realization and we propose some simple heuristics for more complex ones. Next we consider the traffic management tools that can be generated from an evacuation plan. We start by introducing the cell transmission model with flow reduction. This model captures the flow reduction after the onset of congestion. We then discuss the management tools that can be extracted from this model. We also propose some simplification to the model formulation to enhance its tractability. A heuristic for generating a solution is also proposed, and its solution quality is analyzed. Finally, we discuss the hospital evacuation problem where we develop an integer programming model that integrates the building evacuation with the transportation of patients. The impact of building evacuation capabilities on the transportation plan is investigated through the case of a large regional hospital case study. We also propose a decomposition scheme to improve the tractability of the integer program. / Ph. D.

Appraisal methodologies for congestion mitigation projects are relatively less well developed compared to methodologies for projects reducing free flow travel times. For instance, static assignment models are incapable of representing the build-up and dissipation of traffic queues, or capturing the experienced crowding caused by uneven on-board passenger loads. Despite the availability of dynamic traffic assignment, only few model systems have been developed for cost-benefit analysis of real applications. The six included papers present approaches and tools for analysing traffic and transit projects where congestion relief is the main target. In the transit case studies, we use an agent-based simulation model to analyse congestion and crowding effects and to conduct cost-benefit analyses. In the case study of a metro extension in Stockholm, we demonstrate that congestion and crowding effects constitute more than a third of the total benefits and that a conventional static model underestimates these effects vastly. In another case study, we analyse various operational measures and find that the three main measures (boarding through all doors, headway-based holding and bus lanes) had an overall positive impact on service performance and that synergetic effects exist. For the congestion charging system in Gothenburg, we demonstrate that a hierarchal route choice model with a continuous value of time distribution gives realistic predictions of route choice effects although the assignment is static. We use the model to show that the net social benefit of the charging system in Gothenburg is positive, but that low income groups pay a larger share of their income than high income groups. To analyse congestion charges in Stockholm however, integration of dynamic traffic assignment with the demand model is necessary, and we demonstrate that this is fully possible. Models able to correctly predict these effects highlight the surprisingly large travel time savings of pricing policies and small operational measures. These measures are cheap compared to investments in new infrastructure and their implementation can therefore lead to large societal gains. / <p>QC 20160829</p>

The basic design concept of most advanced traveler information systems (ATIS) is to present generic information to travelers, leaving travelers to react to the information in their own way. This passive way of managing traffic by providing generic traffic information makes it difficult to predict the outcome and may even incur an adverse effect, such as overreaction (also referred to as the herding effect). Active traffic and demand management (ATDM) is another approach that has received continual attention from both academic research and real-world practice, aiming to effectively influence people's travel demand, provide more travel options, coordinate between travelers, and reduce the need for travel. The research discussed in this article deals with how to provide users with a travel option that aims to minimize the marginal system impact that results from this routing. The goal of this research is to take better advantage of the available real-time traffic information provided by ATIS, to further improve the system level traffic condition from User Equilibrium (UE), or a real-world traffic system that is worse than UE, toward System Optimal (SO), and avoid passively managing traffic. A behaviorally induced, system optimal travel demand management model is presented to achieve this goal through incremental routing. Both analytical derivation and numerical analysis have been conducted on Tucson network in Arizona, as well as on the Capital Area Metropolitan Planning Organization (CAMPO) network in Austin, TX. The outcomes of both studies show that our proposed modeling framework is promising for improving network traffic conditions toward SO, and results in substantial economic savings.

abstract: The development of microsimulation approaches to urban systems modeling has occurred largely in three parallel streams of research, namely, land use, travel demand and traffic assignment. However, there are important dependencies and inter-relationships between the model systems which need to be accounted to accurately and comprehensively model the urban system. Location choices affect household activity-travel behavior, household activity-travel behavior affects network level of service (performance), and network level of service, in turn, affects land use and activity-travel behavior. The development of conceptual designs and operational frameworks that represent such complex inter-relationships in a consistent fashion across behavioral units, geographical entities, and temporal scales has proven to be a formidable challenge. In this research, an integrated microsimulation modeling framework called SimTRAVEL (Simulator of Transport, Routes, Activities, Vehicles, Emissions, and Land) that integrates the component model systems in a behaviorally consistent fashion, is presented. The model system is designed such that the activity-travel behavior model and the dynamic traffic assignment model are able to communicate with one another along continuous time with a view to simulate emergent activity-travel patterns in response to dynamically changing network conditions. The dissertation describes the operational framework, presents the modeling methodologies, and offers an extensive discussion on the advantages that such a framework may provide for analyzing the impacts of severe network disruptions on activity-travel choices. A prototype of the model system is developed and implemented for a portion of the Greater Phoenix metropolitan area in Arizona to demonstrate the capabilities of the model system. / Dissertation/Thesis / Ph.D. Civil and Environmental Engineering 2012

A identificação dos segmentos críticos da rede viária é um conhecimento básico que todo planejador de transportes deve ter sobre a rede viária. É inevitável a ocorrência de incidentes e eventos de redução da capacidade nos elementos da rede. O efeito de acidentes e obstruções em segmentos críticos da rede ocasionam impactos que prejudicam o desempenho da rede. Este estudo foi desenvolvido com o apoio do modelo de alocação de tráfego do software VISUM (versão 2015) e propõe um método para determinar a importância de cada segmento da rede viária, a identificação de segmentos críticos da rede e a avaliação de sua obstrução de forma estática e dinâmica. Para isso, são utilizados diversos indicadores de desempenho da rede viária. O método foi aplicado na região do Litoral Norte do Rio Grande do Sul, utilizando os dados de tráfego fornecidos pela CONCEPA TRIUNFO, DAER e DNIT. A determinação da importância de cada segmento decorreu da avaliação do impacto na rede causado pela obstrução do próprio segmento. Através do método proposto neste estudo foi possível identificar o segmento crítico da rede viária estudada e, de forma qualitativa, verificar a extensão da obstrução desse segmento nas análises estática e dinâmica Verificou-se que o indicador diferença do total de tempo despendido na rede é o indicador que mais apresenta crescimento com o incremento da demanda, não apresenta alterações de priorização dos segmentos frente a variações de intensidade e sentido da demanda. Os resultados deste estudo mostraram que o segmento crítico da rede pertence a BR-101 entre os municípios de Osório e Terra de Areia. O método de hierarquização proposto independe do sentido e da intensidade da demanda, e está sujeito a mais de uma métrica para avaliar o segmento crítico. Estes resultados podem subsidiar o planejamento de transportes, identificando trechos críticos da rede viária que necessitam de mais atenção dos gestores e apontando medidas de operação no caso de eventos disruptivos nos trechos críticos. / Identifying the most important link of the network is essential knowledge that the transport planners should have over the network. Incidents and events of capacity reduction in network elements are inevitable. The effect of accidents and obstructions on critical network links causes impacts that hamper network performance. This study was developed with support of VISUM (version 2015) traffic assignment model software with proposes a method to determinate each network link importance level, to identify the critical link and to measure the critical link blockage impact on network. For this, several road network performance indicators are used. The method was applied in the North Coast region of Rio Grande do Sul, using traffic data provided by CONCEPA TRIUNFO, DAER and DNIT. The link level importance in define from the own link impact due its obstruction. The proposed method identified the most critical link of the studied network and verified the qualitative impact of its obstruction extent in the static and dynamic assignment analyses It was verified that the measure total spent time difference in the network is the most sensible measure that growth with a demand increase, this measure does not present changes the link importance rank against variations of intensity and direction of demand flow changes. The results of this study show that the critical link of the network belongs to the BR-101 highway between the municipalities of Osório and Terra de Areia. The proposed hierarchical method developed with several metrics measures fond the critical link in an independent demand direction and intensity analysis. The findings may support transport planners to identify the most critical arc of a network. To better implement resources of road management and repairs. Also identify where the operation measures may be implanted in face a disruptive event on a critical link.