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.

Bus systems have a large passenger capacity when compared to personal vehicles and thus have the potential to improve urban mobility. However, buses that operate in mixed vehicle traffic can undermine the effectiveness of the road system as they travel at lower speeds, take longer to accelerate and stop frequently to board and alight passengers. In traffic flow theory, buses are known as slow-moving bottlenecks that have the potential to create queue-spillbacks and thus increase the probability of gridlock. Currently, traditional metropolitan transportation planning models do not account for these negative effects on roadway capacity. Also, research methods that study multimodal operations are often simulated or algorithmic which can only provide specific results for defined inputs. The objective of this research is to model and understand the effects of bus operations (e.g., headway, number of stops, number of routes) on system performance (e.g. urban corridor and network vehicular capacity) using a parsimonious analytical approach with a few parameters.The models are built using the Macroscopic Fundamental Diagram (MFD) of traffic which provides aggregate measures of vehicle density and flow. Existing MFD theory, which accounts for corridors with only one vehicle class are extended to include network roadway systems and bus operations. The results indicate that buses have two major effects on corridors: the moving bottleneck and the bus short-block effect. Also, these corridor effects are expanded to urban networks through a vehicle density-weighted average. The models have the potential to transform urban multimodal operations and management as they provide a simple tool to capture aggregate performance of transportation systems.

Macroscopic fundamental diagrams (MFD) reveal the relations among flow, speed and density in a large geographic region. After literature review on macroscopic analysis, the similar methodology is applied in this thesis. The purpose of the thesis is to find the evidence that is able to prove MFD existing in Stockholm urban region. Both floating car data (FCD) based on global positioning system (GPS) data from taxis travelling in Stockholm region and traffic data from fixed detectors data source are used to construct the fundamental diagrams. Geographically, the usage of data is extended from single link to multiple links, then to the entire study region. The temporal phase is restricted in one weekday and weekend. The diagram of flow vs. speed based on single detector is found disordered, by contrast, the diagrams of cumulative flow, speed and density for all detectors represent orderly. MFD diagrams proposed in Yokohama case study by Geroliminis and Daganzo are reproduced with cumulative data in this thesis.  Therefore, it can be proved that MFD exists when using data from multiple links. However, the cumulative data from fixed detectors only represents the traffic on links where they locate, not the entire region. To overcome it, GPS data from taxis, which covers the whole region, is analyzed with same method. Because full taxis travel in the same manner as normal vehicles, they are selected to approximate traffic in whole region. A neat curve of flow vs. speed is produced and it coincides with corresponding diagram in the reference paper. It enhances the conclusion that MFD exists in the entire study region. Moreover, based on the constant ratio between average link flow and region exit flow, a controlling density policy is discussed in aiming for maximizing trip completion.

Various theories have been proposed to describe vehicular traffic flow in cities on an aggregate level. This dissertation work shows that a number of MFDs exist in an urban network. The number of MFDs basically indicate the existence of different levels of service on different network routes. It also demonstrate that the modification of control strategy can optimize the signal timing plan for the links with high congestion and spillbacks. With the proposed control strategy, the location of points are shifted from lower MFDs to upper MFDs which means the congestion are reduced and the overall network traffic flow operation is improved. In this thesis, the emergency vehicle preemption (EVP) operation is also evaluated by using the MFDs. The concept of MFD can help to illustrate the effect on various types of roads due to EVP operation. The results show that the volume of links along the emergency route is increased and the volume of other links closed to the emergency route is decreased due to preemption. The researchers and practitioners can apply the proposed approach to identify the affected links and minimize the total network delay during EVP. / Master of Science

The Macroscopic Fundamental Diagram (MFD) is a diagram that presents a relationship between the average flow (production) and the average density in an urban network. Ever since the existence of low scatter MFD in urban road network was verified, significant efforts have been made to describe the MFD quantitatively. Due to the complexity of the traffic environment in urban networks, an accurate and explicit expression for the MFD is not yet developed and many recent research efforts for MFD rely on computer simulations. On a single corridor, an analytical approximation model for the MFD exists. However, this thesis expanded this theory in two directions. First, we specialize the method for models with equal road length on the corridor, which greatly reduces the complexity of the method. We introduce the adoption of seven straight cuts in approximation. Computer simulations are conducted and show a high compatibility with the approximated results. However the analytical approximation can only be applied with the assumption of constant circulating vehicles in the system without turnings and endogenous traffics. Secondly, we show that turnings and endogenous traffic can bring various impact on the shape of the MFD, the capacity, the critical density, the variance in density and cause a phenomenon of clustered traffic status along the MFD curve. Furthermore, the simulation using stochastic variables reveals that the variance in turning rates and endogenous traffic don’t have significant impact on the MFD. This discovery enables studies to focus on scenarios with deterministic parameters for those factors. While traditional objective of engineering for network is to maximize capacity and widen the range for the maximum capacity, our results indicate that traffic stability at the maximum performance is poor if the system does not stay constantly in equilibrium status. This thesis provides insights into the factors that affect the shape of the MFD by analytical approximation and simulation.

No description available.

Fundamental diagram, a graphical representation of the relation among traffic flow, speed, and density, has been the foundation of traffic flow theory and transportation engineering for many years. For example, the analysis of traffic dynamics relies on input from this fundamental diagram to find when and where congestion builds up and how it dissipates; traffic engineers use a fundamental diagram to determine how well a highway facility serves its users and how to plan for new facilities in case of capacity expansion. Underlying a fundamental diagram is the relation between traffic speed and density which roughly corresponds to drivers’ speed choices under varying car-following distances. First rigorously documented by Greenshields some seventy-five years ago, such a relation has been explored in many follow-up studies, but these attempts are dominantly deterministic in nature, i.e. they model traffic speed as a function of traffic density. Though these functional speed-density models are able to coarsely explain how traffic slows down as more vehicles are crowded on highways, empirical observations show a wide-scattering of traffic speeds around the values predicted by these models. In addition, functional speed-density models lead to deterministic prediction of traffic dynamics, which lack the power to address the uncertainty brought about by random factors in traffic flow. Therefore, it appears more appropriate to view the speed-density relation as a stochastic process, in which a certain density level gives rise not only to an average value of traffic speed but also to its variation because of the randomness of drivers’ speed choices. The objective of this dissertation is to develop such a stochastic speed-density model to better represent empirical observations and provide a basis for a probabilistic prediction of traffic dynamics. It would be ideal if such a model is formulated with both mathematical elegance and empirical accuracy. The mathematical elegance of the model must include the features of: a single equation (single-regime) with physically meaningful parameters and must be easy to implement. The interpretation of empirical accuracy is twofold; on the one hand, the mean of the stochastic speeddensity model should match the average behavior of the empirical equilibrium speeddensity observations statistically. On the other hand, the magnitude of traffic speed variance is controlled by the variance function which is dependent on the response. Ultimately, it is expected that the stochastic speed-density model is able to reproduce the wide-scattering speed-density relation observed at a highway segment after being calibrated by a set of local parameters and, in return, the model can be used to perform probabilistic prediction of traffic dynamics at this location. The emphasis of this dissertation is on the former (i.e. the development, calibration, and validation of the stochastic speed-density model) with a few numerical applications of the model to demonstrate the latter (i.e. probabilistic prediction). Following the seminal Greenshields model, a great variety of deterministic speeddensity models have been proposed to mathematically represent the empirical speeddensity observations which underlie the fundamental diagram. Observed in the existing speed-density models was their deterministic nature striving to balance two competing goals: mathematical elegance and empirical accuracy. As the latest development of such a pursuit, we show that the stochastic speed-density model can be developed through discretizing a random traffic speed process using the Karhunen- Lo`eve expansion. The stochastic speed-density relationship model is largely motivated by the prevalent randomness exhibited in empirical observations that mainly comes from drivers, vehicles, roads, and environmental conditions. In a general setting, the proposed stochastic speed-density model has two components: deterministic and stochastic. For the deterministic component, we propose to use a family of logistic speed density models to track the average trend of empirical observations. In particular, the five-parameter logistic speed-density model arises as a natural candidate due to the following considerations: (1) The shape of the five-parameter logistic speed-density model can be adjusted by its physically meaningful parameters to match the average behavior of empirical observations. Statistically, the average behavior is modeled by the mean of empirical observations. (2) A three-parameter and four-parameter logistic speed-density model can be obtained by reducing the shape or scale parameter in the five-parameter model, but the counter-effect is the loss of empirical accuracy. (3) The five-parameter model yields the best accuracy compared to three-parameter and four-parameter model. The magnitude of the stochastic component is dominated by the variance of traffic speeds indexed by traffic density. The empirical traffic speed variance increases as density increases to around 25 - 30 veh/km, then starts decreasing as traffic density gets larger. It has been verified by empirical evidence that traffic speed variation shows a parabolic shape which makes the proposed variance function in a suitable formula to model its variation. The variance function is dependent on the logistic speed-density relationship with varying model parameters. A detailed analysis of empirical traffic speed variance can be found in Chapter 6. Modeling results show that by taking care of second-order statistics (i.e., variance and correlation) the proposed stochastic speed-density model is suitable for describing the observed phenomenon as well as for matching the empirical data. Following the results, a stochastic fundamental diagram of traffic flow can be established. On the application side, the stochastic speed-density relationship model can potentially be used for real-time on-line prediction and to explain phenomenons in a similar manner. This enables dynamic control and management systems to anticipate problems before they occur rather than simply reacting to existing conditions. Finally, we will summarize our findings and discuss our future research directions.

Traffic Congestion is a critical problem in large urban areas. In this thesis, six different control strategies aiming to alleviate congestion are performed through TRANSIMS simulation in the city of Alexandria. Main objective of this thesis is to study and explore the impacts of these control strategy in terms of system performance. Macroscopic Fundamental Diagrams has been used during research to present traffic movement and evaluate traffic performance. This thesis also look at the outcome of each strategy at different household income group in the city. The attention are drawn to the importance of taking socio-economic impact in traffic management decisions. Some of the control strategies presented in this thesis have different impacts on different income groups in the city, while other control strategies have similar impacts (negative, or inconclusive) on different groups in Alexandria city. The thesis gives the conclusions on the impact of selecting different signal control strategies. / Master of Science

La croissance démographique dans les zones urbaines représente un problème pour la planification des transports. La surcharge des systèmes de transport urbains entraîne des coûts monétaires importants et des problèmes environnementaux. Des mesures politiques sont alors nécessaires pour réduire le niveau de congestion et accroître l'efficacité des systèmes de transport. À court terme, les simulateurs de trafic pourraient constituer un outil puissant pour la conception de solutions innovantes. Mais les simulateurs de trafic classiques sont exigeants sur le plan informatique pour les applications à grande échelle. De plus, la mise en place du scénario de simulation est complexe. Une modélisation de trafic agrégée pourrait être une bonne solution (Daganzo-2007, Geroliminis-2008). Le réseau routier des villes est divisé en régions, où un diagramme fondamental macroscopique bien défini (MFD) régule les conditions de circulation à l'intérieur de chacune. Le MFD concerne le débit et la densité de trafic moyens dans une région. Malgré que l’idée d’agréger le réseau de la ville soit simple, il soulève plusieurs défis qui n’ont pas encore été abordés. Jusqu'à aujourd'hui, seule (Yildirimoglu-2014) propose un cadre d'affectation dynamique du trafic pour les réseaux régionaux et les modèles MFD. Ce cadre est basé sur le modèle Logit multinomial et ne traite pas explicitement des distributions de longueurs de parcours. De plus, leur structure ne considère pas que les utilisateurs sont différents les uns des autres et ont des objectifs et des préférences différents pour leurs voyages. L'objectif de cette thèse est double. Tout d'abord, l'influence du comportement des utilisateurs sur la performance globale du réseau routier d’une ville est étudiée. Cette analyse se concentre sur la vitesse moyenne du réseau et ses capacités internes et de sortie, en comparant différents modèles tenant compte des différents types de comportement des utilisateurs par rapport à l'équilibre utilisateur déterministe et stochastique. En second lieu, un cadre innovant et complet d’affectation dynamique du trafic pour les modèles multirégionaux basés sur le MFD est proposé. Ce cadre est divisé en plusieurs étapes et repose sur les connexions entre la ville et les réseaux régionaux. Dans un premier temps, des méthodes systématiques de mise à l’échelle sont proposées pour rassembler les voies régionales. Dans un deuxième temps, quatre méthodes sont discutées pour calculer les distributions de longueurs de parcours pour caractériser ces chemins régionaux. Dans la troisième étape, un modèle de chargement de réseau qui considère les distributions de longueurs de parcours explicitement calculées et l’évolution des vitesses moyennes régionales est proposé. Enfin, ce cadre d'affectation dynamique du trafic est étendu pour prendre en compte les usager qui ont une aversion au regret ou une rationalité imparfaite. Cette thèse s'inscrit dans le cadre d'un projet européen ERC intitulé MAGnUM: approche de modélisation du trafic multi-échelle et multimodal pour la gestion durable de la mobilité urbaine. / The population growth in urban areas represents an issue for transportation planning. This overload of urban transportation systems, leading to significant monetary costs and environmental issues. Policy measures are then needed to decrease the level of congestion and increase the efficiency of transportation systems. In a short term, traffic simulators might be a powerful tool that helps to design innovative solution. But, the classical traffic simulators are computationally demanding for large scale applications. Moreover, the set up of the simulation scenario is complex. An aggregated traffic modeling might be a good solution (Daganzo, 2007; Geroliminis and Daganzo, 2008). The city network is divided into regions where a well-defined Macroscopic Fundamental Diagram (MFD) regulates the traffic conditions inside each one. The MFD relates the average traffic flow and density inside a region. Despite the idea of aggregating the city network is simple, it brings several challenges that have not yet been addressed. Up to today, only Yildirimoglu and Geroliminis (2014) proposed a dynamic traffic assignment framework for regional networks and MFD models. This framework is based on the simple Multinomial Logit model and does not explicitly deal with trip length distributions. Moreover, their framework does not consider that users are different from each other and have different purposes and preferences for their travels. The goal of this PhD dissertation is to twofold. First, the influence of the users behavior on the global network performance is investigated. This analysis focus on the network mean speed and its internal and outflow capacities, comparing different models that account for different kinds of users behavior against the Deterministic and Stochastic User Equilibrium. Second, an innovative and complete dynamic traffic assignment framework for multi-regional MFD-based models is proposed. This framework is divided into several milestones and is based on the connections between the city and regional networks. In a first step, systematic scaling-up methods are proposed to gather the regional paths. In a second step, four methods are discussed to calculate the distributions of trip lengths that characterize these regional paths. In the third step, a network loading model that considers distributions of trip lengths that are explicitly calculated and the evolution of the regional mean speeds is proposed. Finally, this dynamic traffic assignment framework is extended to account for bounded rational and regret-averse users. This PhD is part of a European ERC project entitled MAGnUM: Multiscale and Multimodal Traffic Modeling Approach for Sustainable Management of Urban Mobility.

The aim of this thesis is to observe behavior of traffic flow and to verify or refute traditional so called fundamental relationships. It analyze data based on older measurements, personal measurements executed on the I/43 road, and mathematical models.There were three tools used provided by "VUT" in Brno as well as own developed tool based on cellular automat..