Nonlinear optimal control applied to coordinated ramp metering

The goal of this paper is to describe a generic approach to the problem of optimal coordinated ramp metering control in large-scale motorway networks. In this approach, the traffic flow process is macroscopically modeled by use of a second-order macroscopic traffic flow model. The overall problem of coordinated ramp metering is formulated as a constrained discrete-time nonlinear optimal control problem, and a feasible-direction nonlinear optimization algorithm is employed for its numerical solution. The control strategy's efficiency is demonstrated through its application to the 32-km Amsterdam ring road. A number of adequately chosen scenarios along with a thorough analysis, interpretation, and suitable visualization of the obtained results provides a basis for the better understanding of some complex interrelationships of partially conflicting performance criteria. More precisely, the strategy's efficiency and equity properties as well as their tradeoff are studied and their partially competitive behavior is discussed. The results of the presented approach are very promising and demonstrate the efficiency of the optimal control methodology for motorway traffic control problems

Local Freeway Ramp Metering using Self-Adjusted Fuzzy Controller

A self-adjusted fuzzy local ramp metering strategy is proposed to keep the mainline traffic state and the on-ramp queue length at reasonable levels. The fuzzy ramp metering strategy (FRMS) takes the following variables as inputs: error between desired density and measured density, change-in-error and on-ramp queue length. On-ramp metering flow is decided by these variables. It is difficult to construct fuzzy rules for a three-dimension inputs fuzzy controller based on expert knowledge, so the proposed FRMS generates fuzzy control rules by an analytic expression with correction factors. The correction factors reflect the weights upon linguistic variables of inputs and can be regulated according to actual traffic state of mainline and on-ramp. The proposed FRMS not only simplifies the process of rules definition for a multi-dimension fuzzy controller, but also has function of self-adjusted control rules. To examine the proposed FRMS, a freeway stretch in Los Angeles is simulated with distributed models. The proposed FRMS is also compared with an existing T-S FRMS and PI-ALINEA in the simulation experiments which cover different on-ramp inflow scenarios. Simulation results show the proposed FRMS provides improved adaptation to various scenarios and superiority in striking a balance between the mainline and on-ramp performances

Ramp metering review

3200037E, Finnra Report

A self-learning motorway traffic control system for ramp metering

Self-learning systems have attracted increasing attention in the ramp metering domain in recent years. These systems are based on reinforcement learning (RL) and can learn to control motorway traffic adaptively. However, RL-based ramp metering systems are still in their early stages and have shown limitations regarding their design and evaluation. This research aims to develop a new RL-based system (known as RAS) for ramp metering to overcome these limitations. A general framework for designing a RL-based system is proposed in this research. It contains the definition of three RL elements in a ramp metering scenario and a system structure which brings together all modules to accomplish the reinforcement learning process. Under this framework, two control algorithms for both single- and multi-objective problems are developed. In addition, to evaluate the proposed system, a software platform combining the new system and a traffic flow model is developed in the research. Based on the platform developed, a systematic evaluation is carried out through a series of simulation-based experiments. By comparing with a widely used control strategy, ALINEA, the proposed system, RAS, has shown its effectiveness in learning the optimal control actions for different control objectives in both hypothetical and real motorway networks. It is found that RAS outperforms ALINEA on improving traffic efficiency in the situation with severe congestion and on maintaining user equity when multiple on-ramps are included in the motorway network. Moreover, this research has been extended to use indirect learning technology to deal with incident-induced congestion. Tests for this extension to the work are carried out based on the platform developed and a commercial software package, AIMSUN, which have shown the potential of the extended system in tackling incident-induced congestion

Freeway Traffic Density and On-Ramp Queue Control via ILC Approach

A new queue length information fused iterative learning control approach (QLIF-ILC) is presented for freeway traffic ramp metering to achieve a better performance by utilizing the error information of the on-ramp queue length. The QLIF-ILC consists of two parts, where the iterative feedforward part updates the control input signal by learning from the past control data in previous trials, and the current feedback part utilizes the tracking error of the current learning iteration to stabilize the controlled plant. These two parts are combined in a complementary manner to enhance the robustness of the proposed QLIF-ILC. A systematic approach is developed to analyze the convergence and robustness of the proposed learning scheme. The simulation results are further given to demonstrate the effectiveness of the proposed QLIF-ILC

Evaluation of the efficiency of mainline and ramp metering in highway traffic management

Text in English; Abstract: English and TurkishIncludes bibliographical references (leaves 70-72)xi, 72 leavesIn the study, the effects of the mainline and ramp control theories on the highway traffic flow are investigate. In order to eliminate to alleviate the traffic congestion problem, which has become a problem in high-population cities, the mainline and ramp controls are considered as a solution, and control networks are emphasized. Examples of applications and results in the world are given. The applicability of the methods to be used by examining the previous studies was first examined on a general model and then on a selected highway network. In the models prepared, vehicle speeds, travel times, flow (volume) concepts, and relationships between them are mentioned. In addition, general information about highway management was also provided before. Control models were examined with the Microscopic Simulation Program, the purpose and types of models applied were compared. The traffic simulation model of the region between K-8 and K-11 on the O-2 highway from Asia to Europe has been created and the effects created by the control have been examined by applying both ramp and mainline metering. Analysis results; It has been observed that the control of ramp and mainline scenarios provides benefits compared to uncontrolled situations. Among the benefits provided; when the analysis of the basic model and mainline metering is applied, it is seen that there is an increase of 20.76% in travel times and an increase of 19.78% in vehicle speeds. Nevertheless, the implications of these control scenarios should be thoroughly investigated. Simulation results show that Ramp Metering (RM) and Mainline Metering (MM) controls can be an effective method in the management of highway-highway connections. In this regard, it is recommended that the control strategies mentioned in intensive highway-to-highway participations be tested in real life in order to increase efficiency.Hazırlanan çalışmada ana yol ve katılım kontrol teorilerinin otoyol trafik akımı üzerindeki etkileri araştırılmıştır. Yüksek nüfuslu şehirlerde bir problem haline gelen trafik tıkanıklığı sorunu, geçiş sırasında oluşan tıkanıklığın ortadan kaldırılması ya da hafifletilmesi amacıyla ana yol ve katılım kontrolleri bir çözüm olarak görülmekte olup kontrol şebekeleri üzerinde durulmuştur. Dünyadaki uygulamalar ve sonuçlarından örnekler verilmiştir. Önceki çalışmalar incelenerek kullanılacak metotların uygulanabilirliği öncelikle genel bir model üzerinde sonrasında da seçilmiş bir otoyol ağı üzerinden uygulanarak incelenmiştir. Hazırlanan modellerde yol ağı ile ilgili araç hızlarına, seyahat sürelerine, akım (hacim) kavramlarına ve aralarındaki ilişkilere değinilmiştir. Ayrıca otoyol yönetimi ile ilgili genel bilgiler de öncesinde sunulmuştur. Kontrol modelleri Mikroskobik Simülasyon Programı ile incelenmiş, amacı, uygulanan model çeşitleri kıyaslamalı olarak anlatılmıştır. Asya Avrupa yönünde O-2 otoyolunda K-8 ile K-11 arasında kalan bölgenin trafik benzetim modeli oluşturulmuş ve hem katılım hem de ana yol kontrolü uygulaması yapılarak, kontrolün yarattığı etkiler incelenmiştir. Analiz sonuçları katılım ve ana yol senaryolarının kontrolünün, kontrolsüz durumlara göre fayda sağladığı görülmüştür. Sağlanan faydalar arasında temel model ve ana yol kontrolünün uygulandığı analizler karşılaştırıldığında; ana yol kontrolünün seyahat sürelerinde % 20,76 kazanç ve araç hızlarında ki % 19,78'lik yükseliş sağladığı görülmektedir. Bununla birlikte, bahsi geçen kontrol senaryoları uygulandığında doğuracağı sonuçlar kapsamlı bir şekilde araştırılmalıdır. Yapılan simülasyon sonuçları katılım (RM) ve anayol (MM) kontrollerinin Otoyol-otoyol bağlantılarının yönetiminde etkili bir yöntem olabileceğini göstermektedir. Bu doğrultuda, verimlilik artışı sağlamak üzere yoğun otoyol-otoyol katılımlarında bahsi geçen kontrol stratejilerinin etkinliğinin gerçek hayatta da sınanması önerilmektedir

On Learning based Parameter Calibration and Ramp Metering of freeway Traffic Systems

Ph.DDOCTOR OF PHILOSOPH