This dissertation studies a series of freeway and arterial traffic modeling, estimation and control methodologies. First, it investigates the Link-Node Cell Transmission Model's (LN-CTM's) ability to model arterial traffic. The LN-CTM is a modification of the cell transmission model developed by Daganzo. The investigation utilizes traffic data collected on an arterial segment in Los Angeles, California, and a link-node cell transmission model, with some adaptations to the arterial traffic, is constructed for the studied location. The simulated flow and the simulation travel time were compared with field measurements to evaluate the modeling accuracy. Second, an algorithm for estimating turning proportions is proposed in this dissertation. The knowledge about turning proportions at street intersections is a frequent input for traffic models, but it is often difficult to measure directly. Compared with previous estimation methods used to solve this problem, the proposed method can be used with only half the detectors employed in the conventional complete detector configuration. The proposed method formulates the estimation problem as a constrained least squares problem, and a recursive solving procedure is given. A simulation study was carried out to demonstrate the accuracy and efficiency of the proposed algorithm. In addition to addressing arterial traffic modeling and estimation problems, this dissertation also studies a freeway traffic control strategy and a freeway and arterial coordinated control strategy. It presents a coordinated control strategy of variable speed limits (VSL) and ramp metering to address freeway congestion caused by weaving effects. In this strategy, variable speed limits are designed to maximize the bottleneck flow, and ramp metering is designed to minimize travel time in a model predictive control frame work. A microscopic simulation based on the I-80 at Emeryville, California was built to evaluate the strategy, and the results showed that the traffic performance was significantly improved . Following the freeway control study, this dissertation discusses the coordinated control of freeways and arterials. In current practice, traffic controls on freeways and on arterials are independent. In order to coordinate these two systems for better performance, a control strategy covering the freeway ramp metering and the signal control at the adjacent intersection is developed. This control strategy uses upstream ALINEA, which is a well-known control algorithm, for ramp metering to locally maximize freeway throughput. For the intersection signal control, the proposed control strategy distributes green splits by taking into account both the available on-ramp space and the demands of all intersection movements. A microscopic simulation of traffic in an arterial intersection with flow discharge to a freeway on-ramp, which is calibrated using the data collected at San Jose, California, is created to evaluate the performance of the proposed control strategy. The results showed that the proposed strategy can reduce intersection delay by 8%, compared to the current field-implemented control strategy. Transportation mobility can be improved not only by traffic management strategies, but also through the deployment of advanced vehicle technologies. This dissertation also investigates the impact of Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) on highway capacity. A freeway microscopic traffic simulation model is constructed to evaluate how the freeway lane flow capacity change under different penetration rates of vehicles equipped with either ACC or CACC system. This simulation model is based on a calibrated driver behavioral model and the vehicle dynamics of the ACC and CACC systems. The model also utilizes data collected from a real experiment in which drivers' selections of time gaps are recorded. The simulation shows that highway capacity can be significantly increased when the CACC vehicles reach a moderate to high market penetration, as compared to both regular manually driven vehicles and vehicles equipped with only ACC.

This monograph provides an extended overview of modelling and control approaches for freeway traffic systems, moving from the early methods to the most recent scientific results and field implementations. The concepts of green traffic systems and smart mobility are addressed in the book, since a modern freeway traffic management system should be designed to be sustainable. Future perspectives on freeway traffic control are also analysed and discussed with reference to the most recent technological advancements The most widespread modelling and control techniques for freeway traffic systems are treated with mathematical rigour, but also discussed with reference to their performance assessment and to the expected impact of their practical usage in real traffic systems. In order to make the book accessible to readers of different backgrounds, some fundamental aspects of traffic theory as well as some basic control concepts, useful for better understanding the addressed topics, are provided in the book. This monograph can be used as a textbook for courses on transport engineering, traffic management and control. It is also addressed to experts working in traffic monitoring and control areas and to researchers, technicians and practitioners of both transportation and control engineering. The authors’ systematic vision of traffic modelling and control methods developed over decades makes the book a valuable survey resource for freeway traffic managers, freeway stakeholders and transportation public authorities with professional interests in freeway traffic systems. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

In this thesis, a modified second-order continuum model is used to describe the traffic behaviour along highways. The model is identified and verified using several sets of traffic measurements collected from a major highway in metropolitan Toronto, Canada. A robust nonlinear sliding mode observer is developed to generate estimates of average velocity and density for a segment of a highway within a corridor, given loop detector measurements at the end-points of the segment. The sliding mode approach has several advantages over other estimation techniques such as the Kalman Filtering including proof of estimate convergence and simplified computations. However, the primary advantage is the robustness of the observer with respect to unmodelled dynamics and disturbances. Unmodelled dynamics are associated with the traffic factors whose effects cannot be captured (properly) in the traffic flow models, e.g., road geometry and weather conditions. On the other hand, model disturbances such as unavailable (not measured) traffic flow at a ramp or measurements provided by a faulty detector can also create unpredictable traffic states. Based on the presented traffic model, a systematic design procedure is developed to make the observer robust with respect to the modelling uncertainties and unavailable traffic states. Simulation and experimental results show the effectiveness of the proposed observer in estimating the states of a highway traffic system. Moreover, a new decentralized state feedback linearizing controller for ramp metering using variable structure control is presented. The main aim is to develop a robust controller to locally stabilize freeway traffic despite the presence of disturbances and modelling errors. Simulation results show that the proposed controller provides improved performance in achieving the design objectives over other existing ramp control strategies such as neural network and linear feedback controllers.

The authors have developed a methodology for control of nonlinear systems in the presence of long delays, with large and rapid variation in the actuation or sensing path, or in the presence of long delays affecting the internal state of a system. In addition to control synthesis, they introduce tools to quantify the performance and the robustness properties of the designs provided in the book. The book is based on the concept of predictor feedback and infinite-dimensional backstepping transformation for linear systems and the authors guide the reader from the basic ideas of the concept?with constant delays only on the input?all the way through to nonlinear systems with state-dependent delays on the input as well as on system states. Readers will find the book useful because the authors provide elegant and systematic treatments of long-standing problems in delay systems, such as systems with state-dependent delays that arise in many applications. In addition, the authors give all control designs by explicit formulae, making the book especially useful for engineers who have faced delay-related challenges and are concerned with actual implementations and they accompany all control designs with Lyapunov-based analysis for establishing stability and performance guarantees.