Konstantinos Aboudolas

A MULTIVARIABLE REGULATOR APPROACH TO TRAFFIC-RESPONSIVE NETWORK-WIDE SIGNAL CONTROL

The paper presents the design approach, the objectives, the development, the advantages, and some application results of the traffic-responsive urban control (TUC) strategy. Based on a store-and-forward modelling of the urban network traffic and using the linear-quadratic regulator theory, the design of TUC leads to a multivariable regulator for traffic-responsive co-ordinated network-wide signal control that is particularly suitable also for saturated traffic conditions. Simulation investigations demonstrate the efficiency of the proposed approach. Results of TUCs first field implementation and evaluation are also presented. Finally, summarising conclusions are drawn and future work is outlined.

Extensions and New Applications of the Traffic-Responsive Urban Control Strategy: Coordinated Signal Control for Urban Networks

The objectives, approach, advantages, and some application results of recent extensions of the traffic-responsive urban control (TUC) strategy are presented. Based on well-known methods of the automatic control theory, TUC allows for traffic-responsive coordinated signal control of large-scale urban networks that is particularly efficient under saturated traffic conditions. The first version of the TUC strategy controlled only the green splits. After initial development and the first field implementations and evaluations, TUC was expanded to perform real-time cycle and offset control, and to allow for public transport priority. Simulation investigations of the extended TUC application in parts of the urban networks of Tel Aviv and Jerusalem, Israel, by use of the AIMSUN microscopic simulator demonstrate the high efficiency of the new signal control strategy.

Adaptive Performance Optimization for Large-Scale Traffic Control Systems

In this paper, we study the problem of optimizing (fine-tuning) the design parameters of large-scale traffic control systems that are composed of distinct and mutually interacting modules. This problem usually requires a considerable amount of human effort and time to devote to the successful deployment and operation of traffic control systems due to the lack of an automated well-established systematic approach. We investigate the adaptive fine-tuning algorithm for determining the set of design parameters of two distinct mutually interacting modules of the traffic-responsive urban control (TUC) strategy, i.e., split and cycle, for the large-scale urban road network of the city of Chania, Greece. Simulation results are presented, demonstrating that the network performance in terms of the daily mean speed, which is attained by the proposed adaptive optimization methodology, is significantly better than the original TUC system in the case in which the aforementioned design parameters are manually fine-tuned to virtual perfection by the system operators.

Control and Optimization Methods for Traffic Signal Control in Large-scale Congested Urban Road Networks

The problem of designing real-time traffic signal control strategies for large-scale congested urban road networks via suitable application of control and optimization methods is considered. Three alternative methodologies are proposed, all based on the store-and-forward modeling (SFM) paradigm. The first methodology results in a linear multivariable feedback regulator derived through the formulation of the problem as a linear-quadratic (LQ) optimal control problem. The second methodology leads to an open-loop constrained quadratic optimal control problem whose numerical solution is achieved via quadratic-programming (QP). Finally, the third methodology leads to an open-loop constrained nonlinear optimal control problem whose numerical solution is effectuated by use of a feasible-direction algorithm. A simulation-based investigation of the signal control problem for a large-scale urban network using these methodologies is presented. Results demonstrate the efficiency and real-time feasibility of the developed generic control methods.

Cost Effective Real-Time Traffic Signal Control Using the TUC Strategy

Many reasons have been mentioned for the less than expected deployment of adaptive urban traffic control systems [6], among which the high cost of installation and maintenance is one of the most cited. This is particularly true for mid-sized cities (with less than 500 000 inhabitants) in developing countries which cannot afford the systems provided by the major vendors of urban traffic control (UTC) software.

Nonlinear control of large scale complex systems using convex optimization tools and self-adaptation

Based on recent advances on convex design for Large-Scale Control Systems (LSCSs) and robust and efficient LSCS self-tuning/adaptation, a methodology is proposed in this paper which aims at providing an integrated LSCS-design, applicable to large-scale systems of arbitrary scale, heterogeneity and complexity and capable of: 1) Providing stable, efficient and arbitrarily-close-to-optimal LSCS performance; 2) Being able to incorporate a variety of constraints, including limited control constraints as well as constraints that are nonlinear functions of the system controls and states; 3) Being intrinsically self-tunable, able to rapidly and efficiently optimize LSCS performance when short-, medium- or long-time variations affect the large-scale system; 4) Achieving the above, while being scalable and modular. The purpose of the present paper is to provide the main features of the proposed control design methodology.

Investigation of a city-scale three-dimensional Macroscopic Fundamental Diagram for bi-modal urban traffic

Recent research has demonstrated that the Macroscopic Fundamental Diagram (MFD) is reliable and practical tool for modeling traffic dynamics and network performance in single-mode (cars only) urban road networks. In this paper, we first extend the modeling of the single-mode MFD to a bi-modal (bus and cars) one. Based on simulated data, we develop a three-dimensional MFD (3D-MFD) relating the accumulation of cars and buses, and the total circulating flow in the network. We propose an exponential function to capture the shape of the 3D-MFD, which shows a good fit to the data. We also propose an elegant estimation for passenger car equivalent of buses (PCU), which has a physical meaning and depends on the bi-modal traffic in the network. Moreover, we analyze a 3D-MFD for passenger network flows and derive its analytical function. Finally, we investigate an MFD for networks with dedicated bus lanes and the relationship between the shape of the MFD and the operational characteristics of buses. The output of this paper is an extended 3D-MFD model that can be used to (i) monitor traffic performance and, (ii) develop various traffic management strategies in bi-modal urban road networks, such as redistribution of urban space among different modes, perimeter control, and bus priority strategies.

Perimeter and boundary flow control for heterogeneous transportation networks

In this paper, we macroscopically describe the traffic dynamics in heterogeneous transportation networks by utilizing the Macroscopic Fundamental Diagram (MFD) for urban networks a widely observed relation between network-wide mean flow and density of vehicles. A generic mathematical model for multi-reservoir networks with well-defined MFDs for each reservoir is presented first. Then, an optimal control methodology is employed for the design of perimeter and boundary flow control strategies that aim at distributing the accumulation in each reservoir as homogeneously as possible, and maintaining the rate of vehicles that are allowed to enter each reservoir around a desired point, while the systems throughput is maximized. Perimeter control occurs at the periphery of the network while boundary control occurs at the inter-transfers between neighborhood reservoirs. Based on this control methodology, control actions may be computed in real-time through a linear multivariable integral feedback regulator (LQI). To this end, the heterogeneous network of Downtown San Francisco is partitioned into three homogeneous reservoirs that exhibit well-defined MFDs. These MFDs are then used to design and compare the proposed LQI regulator with a pre-timed signal control plan and a bang-bang controller. Finally, the impact of the control actions to the network is demonstrated via simulation by the use of the corresponding MFDs and other performance measures.

Nonlinear Control of Large Scale complex Systems using Convex Control Design tools

Based on recent advances on convex design for Large-Scale Control Systems (LSCSs) and robust and efficient LSCS self-tuning/adaptation, a methodology is proposed in this paper which aims at providing an integrated LSCS-design, applicable to large-scale systems of arbitrary scale, heterogeneity and complexity and capable of: 1) Providing stable, efficient and arbitrarily-close-to-optimal LSCS performance; 2) Being able to incorporate a variety of constraints, including limited control constraints as well as constraints that are nonlinear functions of the system controls and outputs (sensor measurements); 3) Being intrinsically self-tunable, able to rapidly and efficiently optimize LSCS performance when short-, medium- or long-time variations affect the large-scale system; 4) Achieving the above, while being scalable and modular. The purpose of the present paper is to provide the main features of the proposed control design methodology.