Control Of Transportation Networks Research Articles

Distributed Data-Driven Control of Transportation Networks

This paper presents a data-driven control for a network of autonomous vehicles. The general scheme of cruise control is implemented for a set of vehicles defined by a nonlinear equation. Koopman operator allows representing the nonlinear system in the Koopman space (lifted space), suitable to get a linear observer that is used for distributed control instead of the nonlinear model. The proposed control simplified the control design and also allows to use a linear Model Predictive Control (MPC) in a distributed form.

A Distributed SDN Controller for Distributed IoT

Over the past decade, the Internet of Things (IoT) has undergone a paradigm shift away from centralized cloud computing towards edge computing. Hundreds of billions of things are estimated to be deployed in the rapidly advancing IoT paradigm, resulting in enormous amounts of data. Transmitting all these data to the cloud has recently proven to be a performance bottleneck, as it causes many network issues relating to latency, power consumption, security, privacy, etc. However, existing paradigms do not use edge devices for decision making. The use of distributed intelligence could strengthen the IoT in several ways by distributing decision-making tasks to edge devices within the network, rather than sending all data to a central server. In this approach, all computational tasks and data are shared among edge devices. To achieve efficient distribution of IoT intelligence and utilization of network resources, it is necessary to integrate the transport network control with distributed edge and cloud resources to provide dynamic and efficient IoT services. This challenge can be overcome by equipping an edge IoT gateway with the intelligence required to extract information from raw data and to decide whether to actuate itself or to outsource complex tasks to the cloud. Distributed intelligence refers to a collaboration between the cloud and the edge. In this context, we first introduce a distributed SDN-based architecture for IoT that enables IoT gateways to perform IoT processing dynamically at the edge of the network, based on the current state of network resources. Next, we propose an algorithm for selecting clients for the training process of Federated Learning Applications, based on the context information of the network. In the last step, we deploy Federated Learning Applications in our distributed SDN-based architecture, using the gateways to provide distributed intelligence at the edge of the network, and conduct a comprehensive and detailed evaluation of the system from several perspectives.

Management and Orchestration

This month the Management and Orchestration Series presents an article that describes the results of a multi-vendor interoperability test utilizing the Internet Engineering Task Force (IETF)-defined Abstraction and Control of Transport Networks (ACTN) framework. The article provides an overview of the ACTN Framework that is being developed in the IETF's Traffic Engineering Architecture and Signaling (TEAS) working group. The article explains how the ACTN framework is used in conjunction with several IETF Internet Drafts that provide YANG models for use with NETCONF and RESTCONF. The Management and Orchestration Series will be published again in the September timeframe.

Discovering critical intersections in a road network

A sound understanding of the importance of intersections within a road network is a key factor for the efficient and effective management and control of transport networks when traffic operations are saturated. Conventional indices (e.g. level of service, degree of saturation, capacity, or delay) reflect only the states of an intersection itself, but lack the ability to describe the influences among the intersections within a road network. This study specifically presents a novel index, the intersection rank, to evaluate the importance of an intersection within a road network; this index refers to the view of the PageRank algorithm and further considers static connection structures and dynamic influences of traffic volumes between intersections. The experiment, conducted using a simulated road network with 30 intersections, shows that the presented method has superior capability in discovering critical intersections and reveals the interrelationships between intersections. These findings can be used to discover important intersections and adjust scarce spatiotemporal resources of the road transportation system during saturated traffic operations; moreover, they will be helpful for practitioners in undertaking efficient control and management of the road network.

GIS-based models for transport network emergency management

The authors investigated the methods of structural-parametric synthesis, mathematical modeling and optimal control of transport networks from the position of the system analysis. The goals of ensuring the transport infrastructure safety with the positions of the transport network optimal load are determined especially in case of emergency situations. The paper describes the requirements for the development of a mathematical model of the transport network loading. A large number of studies on the transport network load is carried out in the environment of the “ITSGIS” intelligent transport geographic information system and was aimed at the development of the algorithm for automatic detection of emergency situations and congestion. The emergency situation types are characterized by its location, i.e. its coordinates on the electronic map. The emergency time is considered from various positions, such as time of occurrence, normative and actual time of elimination. The geofences of an emergency situation influence are divided into areas of direct and indirect emergency situation influence on transport processes and transport infrastructure objects. On the basis of the constructed models developed management methods of transport network loading and emergency situations analysis, including the collection and processing of raw data, the emergency situations determination and their characteristics, the optimal response strategy choice, the performance of management functions.

Resilient Control of Transportation Networks by Using Variable Speed Limits

We investigate the use of variable speed limits for resilient operation of transportation networks, which are modeled as dynamical flow networks under local routing decisions. In such systems, some external inflow is injected to the so-called origin nodes of the network. The total inflow arriving at each node is routed to its operational outgoing links based on their current densities of traffic. The density on each link has first-order dynamics driven by the difference of its incoming and outgoing flows. A link fails if it reaches its jam density. Such failures may propagate in the network and cause a systemic failure. We show that larger link capacities, that is, the maximum flows that can be sustained by the links, are not always better for preventing systemic failures under local routing. Accordingly, we propose the use of variable speed limits to operate the links below their capacities, when necessary, to compensate for the lack of global information and coordination in routing decisions. We show that systemic failures under feasible external inflows can always be averted through proper selection of speed limits if the routing decisions are sufficiently responsive to local congestion and the network is initially uncongested. This is an attractive feature as it provides a practical alternative to building more physical capacity or altering routing decisions that are determined by social behavior.

Critical links detection in stochastic networks: application to the transport networks

PurposeThe purpose of this paper is to study a multiple-origin-multiple-destination variant of dynamic critical nodes detection problem (DCNDP) and dynamic critical links detection problem (DCLDP) in stochastic networks. DCNDP and DCLDP consist of identifying the subset of nodes and links, respectively, whose deletion maximizes the stochastic shortest paths between all origins–destinations pairs, in the graph modeling the transport network. The identification of such nodes (or links) helps to better control the road traffic and predict the necessary measures to avoid congestion.Design/methodology/approachA Markovian decision process is used to model the shortest path problem under dynamic traffic conditions. Effective algorithms to determine the critical nodes (links) while considering the dynamicity of the traffic network are provided. Also, sensitivity analysis toward capacity reduction for critical links is studied. Moreover, the complexity of the underlying algorithms is analyzed and the computational efficiency resulting from the decomposition operation of the network into communities is highlighted.FindingsThe numerical results demonstrate that the use of dynamic shortest path (time dependency) as a metric has a significant impact on the identification of critical nodes/links and the experiments conducted on real world networks highlight the importance of sensitive links to dynamically detect critical links and elaborate smart transport plans.Research limitations/implicationsThe research in this paper also revealed several challenges, which call for future investigations. First, the authors have restricted our experimentation to a small network where the only focus is on the model behavior, in the absence of historical data. The authors intend to extend this study to very large network using real data. Second, the authors have considered only congestion to assess network’s criticality; future research on this topic may include other factors, mainly vulnerability.Practical implicationsTaking into consideration the dynamic and stochastic nature in problem modeling enables to be effective tools for real-time control of transportation networks. This leads to design optimized smart transport plans particularly in disaster management, to improve the emergency evacuation effeciency.Originality/valueThe paper provides a novel approach to solve critical nodes/links detection problems. In contrast to the majority of research works in the literature, the proposed model considers dynamicity and betweenness while taking into account the stochastic aspect of transport networks. This enables the approach to guide the traffic and analyze transport networks mainly under disaster conditions in which networks become highly dynamic.

Management and orchestration

This month the Management and Orchestration Series presents an article that describes the results of a multi-vendor interoperability test utilizing the Internet Engineering Task Force (IETF)-defined Abstraction and Control of Transport Networks (ACTN) framework. The article provides an overview of the ACTN Framework that is being developed in the IETF's Traffic Engineering Architecture and Signaling (TEAS) working group. The article explains how the ACTN framework is used in conjunction with several IETF Internet Drafts that provide YANG models for use with NETCONF and RESTCONF. The Management and Orchestration Series will be published again in the September timeframe.

ACTN Transport Multi-Vendor Interoperability Testing

We describe the results of the first multi-vendor interoperability testing following the IETF-defined ACTN framework and YANG model standards for transport SDN. ACTN is a scalable, hierarchical architecture enabling practical multi-domain, multi-layer, and multi-vendor transport network control integration through the use of standard YANG models defining controller northbound interfaces. A large variety of carrier use cases and required control functionality was shown to be enabled strictly through use of these standard models, as implemented independently by two participating vendors and operated in a Tier One carrier lab environment. The demonstrated use cases are discussed in detail, and other use cases, for which ACTN and the IETF YANG models are thought to be well-suited -- notably including IP + Optical control cases -- are discussed.

Emerging transport SDN architecture and use cases

SDN and virtualization promise to simplify transport network control, while adding management flexibility and allowing the rapid development of new services by enabling programmatic control of transport networks and equipment. A consensus transport SDN (T-SDN) architecture using standards- based system inter-component interfaces further enables flexible composition of functionally unified systems from among vendor-diverse software and hardware components. In this article we discuss the high-level reference T-SDN architecture emerging from early experience, standards, and related industry activities, with attention paid to critical standards-based system interface methodologies. We examine key T-SDN use cases including service bandwidth on demand, virtual transport network services, and multi-layer control convergence and resource optimization.

Optimal Control of Scalar Conservation Laws Using Linear/Quadratic Programming: Application to Transportation Networks

This article presents a new optimal control framework for transportation networks in which the state is modeled by a first order scalar conservation law. Using an equivalent formulation based on a Hamilton-Jacobi (H-J) equation and the commonly used triangular fundamental diagram, we pose the problem of controlling the state of the system on a network link, in a finite horizon, as a Linear Program (LP). We then show that this framework can be extended to an arbitrary transportation network, resulting in an LP or a Quadratic Program. Unlike many previously investigated transportation network control schemes, this method yields a globally optimal solution and is capable of handling shocks (i.e., discontinuities in the state of the system). As it leverages the intrinsic properties of the H-J equation used to model the state of the system, it does not require any approximation, unlike classical methods that are based on discretizations of the model. The computational efficiency of the method is illustrated on a transportation network.

MULTI-AGENT MODEL PREDICTIVE CONTROL FOR TRANSPORTATION NETWORKS WITH CONTINUOUS AND DISCRETE ELEMENTS

For several reasons, control of transportation networks like road traffic networks, power transmission networks, water distribution networks, etc. has to be done using a multi-agent control approach. We consider a multi-agent control approach in which each control agent uses Model Predictive Control (MPC) to determine its actions. Each control agent uses a model of its subnetwork and communication with its neighboring control agents to come to agreement on the evolution of interconnections and to determine optimal local inputs and states. The challenge that is addressed in this paper comes from the situation that arises when the models that the agents use contain both continuous and discrete elements, instead of one of the two exclusively. We propose an approach that deals with this hybrid behavior and results in agreement between the agents with respect to the evolution of interconnections and that moreover provides integer inputs to obtain these evolutions.

The private user network interface - a GMPLS-compliant signaling interface for overlay-based multilayer networks

Feature Issue on Next-Generation WDM Network Design and Routing (WDMN). To address the integration of [IP/MPLS (multiprotocol label-switching)] packet and (optical) transport networks, the Optical Internetworking Forum (OIF) has defined a user-to-network interface (UNI) for overlay networks: the OIF UNI version 1.0, also referred to as the Public UNI. However, since its implementation agreement specification, it has become clear that this UNI--based on OIF-specific extensions to the generalized MPLS (GMPLS) protocols--will not be able to meet the future requirements of some operational environments. Hence a flexible, extensible, and fully GMPLS-compliant UNI is being defined at the Internet Engineering Task Force (IETF): the Private UNI (aka GMPLS for overlay networks). The Private UNI enhances the interaction between the packet and transport network control planes of a multilayer network architecture. This interface is particularly suitable for a control-plane interconnection model in which the equipment belongs to a common administrative entity (i.e., a single carrier environment). Signaling sessions through the Private UNI are used to invoke two main services that require constructive coordination between the network layers: provisioning and network recovery. Here we present the Private UNI specific GMPLS resource reservation protocol-traffic engineering (RSVP-TE) extensions in support of these services in IP/MPLS over SONET/SDH (synchronous optical network/synchronous digital hierarchy) GMPLS multilayer networks and illustrate how Private UNI signaling enhances coordination in multilayer network recovery.

Optimal Location of Traffic Counting Points for Transport Network Control

An iterative two-stage procedure is proposed that first derives the complete traffic flow vector on a transport network and then produces a reliable estimate of the Origin/Destination (O/D) trip matrix. The procedure is based on the measured flows provided by a minimal-cost set of traffic sensors. These are located on the network by solving a suitable combinatorial optimization model through a number of heuristics that achieve good performances. It is shown that solving the sensor location problem may significantly improve the accuracy of common O/D estimation procedures.