Traffic-responsive Urban Control Research Articles

On the evaluation and selection of network-level traffic control policies: Perimeter control, TUC, and their combination

Perimeter control (PC) of urban traffic networks can be effective in increasing network-wide efficiency. PC operates on the border of a protected region of a traffic network. Most studies thus far considered fixed-time plans for the inner part of these regions. A few studies have shown that combining PC with locally actuated or decentralized traffic control systems may have positive effects on traffic performance, including better-defined Network Macroscopic Fundamental Diagrams (NMFDs), increased network throughput, and reduced delays. The Traffic-responsive Urban Control (TUC) is a real-time network-wide traffic control system with particular design characteristics, such as the balancing of link’s occupancies and an inherent gating feature. These characteristics suggest that TUC may enhance the traffic network performance when combined with PC whilst improving the resulting NMFDs and network throughput and delays. In this work, we investigate the effect of feedback perimeter control (FPC), TUC, and their combination on the NMFD and on the traffic conditions of general traffic and public transport in the microsimulation of a realistic model of the Christchurch Central Business District in New Zealand. We perform a thorough investigation of practical aspects of both control strategies and their combination, including parameter tuning and infrastructure requirements, and how they may affect the control system choice. Results show higher throughput and less hysteresis on the NMFDs, particularly when TUC is involved. PC provides benefits concentrated in the protected region which can greatly benefit public transportation if there is an overlap with the transit network. The combination of TUC and FPC boosts network-wide throughput.

Semi-Decentralized Traffic-Responsive Urban Control

Semi-Decentralized Traffic-Responsive Urban Control

Decentralized store-and-forward based strategies for the signal control problem in large-scale congested urban road networks

Signal control strategies for congested urban road networks designed in a centralized framework require many communication links, serious processing power, and infrastructure for the centralized coordination. As a result, strategies based on a centralized framework are not scalable. The use of decentralized signal control strategies for large-scale urban traffic networks is a solution to this problem, since it allows for the implementation of such strategies on networks whose centralized solution is not easily scalable. This paper addresses the problem of designing a decentralized traffic-responsive signal control solution, proposing two methods based on different formulations of the store-and-forward model: (i) the Decentralized Traffic-responsive Urban Control (DTUC) method; and (ii) the Decentralized Decoupled Traffic-responsive Urban Control (D2TUC). The decentralized configuration is such that each intersection is associated with one computational unit, with limited computational power and memory, which controls the traffic signals of the incoming links. Sufficient conditions for the controllability of the considered store-and-forward models are also presented. Both methods are validated resorting to numerical simulations of the urban traffic network of Chania, Greece, for two demand scenarios, and their performance is compared with the performance of the Traffic-responsive Urban Control (TUC) centralized strategy. One of the proposed decentralized methods, D2TUC, is shown to match the performance of TUC.

Centralised versus decentralised signal control of large‐scale urban road networks in real time: a simulation study

Recently, signal control strategies with decentralised logic have been developed to tackle the traffic congestion problems of urban road networks. Such strategies aim at network-wide traffic flow efficiency improvement via local actions, thus low design effort and infrastructure investment. This study presents, compares, and evaluates two such innovative approaches: the job scheduling algorithm comprising the local control component of the scalable urban traffic control (SURTRAC) system and the max- or back-pressure algorithm. The approaches are also compared against traffic-responsive urban control (TUC), a well-established strategy with centralised logic. Evaluation is based on the AIMSUN simulation model of the city centre of Chania, Greece. The study results indicate that the TUC and max-pressure retain performance independently of the prevailing traffic conditions, while also being computationally simpler than job scheduling. Both decentralised approaches require frequent (high-resolution) and relatively accurate measurements; on the other hand, TUC, although less demanding in this respect, calls for communication lines between the junction controllers and the central computer. Finally, compared with both decentralised approaches, the TUC provides a signal plan sequence with less excessive differences between each other, thus fewer disturbances to the common network users. Nevertheless, for more comprehensive conclusions, more investigations, including field trials, would be needed.

Simulation investigations of the coordinated traffic-responsive signal control strategy TUC with actuation at the local junction level

PurposeTUC (Traffic-responsive Urban Control), a strategy aiming at providing coordinated traffic-responsive signal control in large-scale urban networks, has demonstrated high efficiency, especially under saturated conditions. Nevertheless, as TUC adopts common cycle times for all junctions at any time, some green time waste may occur at links with low or strongly varying alternative demand, which could be mitigated by enabling local actuation. It is the aim of this paper to investigate potential benefits to TUC performance emerging from such local actuation.MethodsActuation may be performed in various ways: by relocating unused green time to stages serving high demand; or by preserving TUC-ordered offsets; or by combining as much as possible both of these features. To study and compare the performance and efficiency of these alternative ways to actuation under realistic traffic conditions, the AIMSUN microscopic simulation model of the road network of the city center of Chania, Greece, was used.ResultsSimulation investigations indicated relocating unused green time to stages serving high demand as the most promising way towards a TUC-coordinated locally-actuated control scheme. However, improvements over the TUC strategy by adopting this approach to actuation were moderate.ConclusionAs the simulation results may be due to the signal control setup at the particular network under study and/or the examined demand scenarios, further investigations, including tests with other road networks and/or demand patterns are necessary before reaching any final conclusions concerning the best way to locally actuate the TUC-decided signal control plans.

Iterative learning approach for traffic signal control of urban road networks

In this study, the authors apply iterative learning control (ILC) theory to address the urban traffic signal control problem in a macroscopic level traffic environment. The original urban traffic signal control problem is first formulated into an output regulating and disturbance rejection problem, and the ILC approach is applied to deal with this class of control problem using the repeatability feature of traffic flow. Then, the ILC strategy is further integrated with the traffic-responsive urban control framework to cope with the random disturbances of traffic conditions in iteration cycle. Theoretical analysis shows that the proposed ILC-based traffic signal control methods can guarantee the asymptotic convergence of the link occupancies to the desired ones. The main advantage of the proposed approaches is that they require less prior modelling knowledge in the control system design. The effectiveness of the proposed methods is further verified by extensive simulations.

A Semi-decentralized Control Strategy for Urban Traffic

We present in this article a semi-decentralized approach for urban traffic control, based on the TUC (Traffic responsive Urban Control) strategy. We assume that the control is centralized as in the TUC strategy, but we introduce a contention time window inside the cycle time, where antagonistic stages alternate a priority rule. The priority rule is set by applying green colours for given stages and yellow colours for antagonistic ones, in such a way that the stages with green colour have priority over the ones with yellow colour. The idea of introducing this time window is to reduce the red time inside the cycle, and by that, increase the capacity of the network junctions. In practice, the priority rule could be applied using vehicle-to-vehicle (v2v) or vehicle-to-infrastructure (v2i) communications. The vehicles having the priority pass almost normally through the junction, while the others reduce their speed and yield the way. We propose a model for the dynamics and the control of such a system. The model is still formulated as a linear quadratic problem, for which the feedback control law is calculated off-line, and applied in real time. The model is implemented using the Simulation of Urban MObility (SUMO) tool in a small regular (American-like) network configuration. The results are presented and compared to the classical TUC strategy.

Simulation and Evaluation of a Public Transport Priority Methodology

The development of methodologies for bus priority at traffic signals is a research field that continues to grow since the need to improve public transport (PT) is nowadays higher compared to the previous decades. Several ways have been used to attract people to use PT means. These attempts can be distinguished in two basic categories: facility-design-based measures and signal-control-based measures. In this paper, a signal-control-based methodology is presented and implemented in a microscopic simulation environment emulating the network of Chania, Greece, with realistic traffic conditions. The control objective is to minimize the average delay time for the buses without creating major disturbances to the rest of the network. For this reason, apart from a fixed-time strategy combined with public transport priority (PTP), the traffic-responsive urban control (TUC) strategy with PTP is implemented in order to reduce the delays also for the private vehicles as well.

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.

A Hybrid Strategy for Real-Time Traffic Signal Control of Urban Road Networks

The recently developed traffic signal control strategy known as traffic-responsive urban control (TUC) requires availability of a fixed signal plan that is sufficiently efficient under undersaturated traffic conditions. To drop this requirement, the well-known Webster procedure for fixed-signal control derivation at isolated junctions is appropriately employed for real-time operation based on measured flows. It is demonstrated via simulation experiments and field application that the following hold: 1) The developed real-time demand-based approach is a viable real-time signal control strategy for undersaturated traffic conditions. 2) It can indeed be used within TUC to drop the requirement for a prespecified fixed signal plan. 3) It may, under certain conditions, contribute to more efficient results, compared with the original TUC method.

A rolling-horizon quadratic-programming approach to the signal control problem in large-scale congested urban road networks

The paper investigates the efficiency of a recently developed signal control methodology, which offers a computationally feasible technique for real-time network-wide signal control in large-scale urban traffic networks and is applicable also under congested traffic conditions. In this methodology, the traffic flow process is modeled by use of the store-and-forward modeling paradigm, and the problem of network-wide signal control (including all constraints) is formulated as a quadratic-programming problem that aims at minimizing and balancing the link queues so as to minimize the risk of queue spillback. For the application of the proposed methodology in real time, the corresponding optimization algorithm is embedded in a rolling-horizon (model-predictive) control scheme. The control strategy’s efficiency and real-time feasibility is demonstrated and compared with the Linear-Quadratic approach taken by the signal control strategy TUC (Traffic-responsive Urban Control) as well as with optimized fixed-control settings via their simulation-based application to the road network of the city centre of Chania, Greece, under a number of different demand scenarios. The comparative evaluation is based on various criteria and tools including the recently proposed fundamental diagram for urban network traffic.

An approach for traffic signal control using RFID sensors

The Korean government is building several futuristic cities, ubiquitous City (u-City), with the latest information technology (IT) infrastructure and "ubiquitous" environment. In the "u-City", Intelligent Transportation System (ITS) will be one of the important services. This study proposed a traffic responsive urban traffic control system applicable in those u-City, using RFID (Radio Frequency Identification) technology to get traffic information. And, we proposed a predictive control model using the real time traffic information achieved from the proposed system. A simulation example is provided to demonstrate the applicability of the proposed system and model.

Adaptive Fine-Tuning of Nonlinear Control Systems With Application to the Urban Traffic Control Strategy TUC

Practical large-scale nonlinear control systems require an intensive and time-consuming effort for the fine-tuning of their control parameters in order to achieve a satisfactory performance. In most cases, the fine-tuning process may take years and is performed by experienced personnel. The purpose of this paper is to introduce and analyze a systematic approach for the automatic fine-tuning of the control parameters of practical large-scale nonlinear control systems and investigate its efficiency when applied to the recently developed urban traffic control strategy traffic-responsive urban control. The proposed approach is based on a concept similar to the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm. The difference between the SPSA algorithm and the proposed approach is that, SPSA employs an approximation of the gradient of an appropriate objective function using only the most recent fine-tuning experiments, while in the proposed approach the approximation of the gradient is performed by using a linear-in-the-parameters approximator that incorporates information of a user-specified time-window of the past experiments. Mathematical analysis of the proposed approach establishes its convergence properties and that SPSA can be regarded as a special case of the proposed approach. Simulation results using the traffic network of the city of Chania, Greece-a typical urban traffic network containing all possible varieties of complex junction staging-demonstrate the efficiency of the proposed approach.

PREDICTIVE CONTROL FOR URBAN TRAFFIC NETWORKS: INITIAL EVALUATION

The paper proposes a control method for urban traffic networks (UTN) through a modified approach of a traffic-responsive urban control (TUC) strategy. TUC uses a store-and-forward traffic flow model and the linear-quadratic theory to efficiently compute network-wide control signals, at the cost of sub-optimality for not considering constrains explicitly. In order to attain an improved controller a model predictive control (MPC) approach is designed. Simulated results of a sample network are shown for fixed time control, TUC, and TUC-MPC strategies. The results are also compared through a mean queue criterion. Finally, conclusions are drawn and future work is outlined.

Application and Evaluation of the Signal Traffic Control Strategy TUC in Chania

The article presents results of a field implementation and evaluation of the traffic-responsive signal control strategy Traffic-responsive Urban Control (TUC) in two junctions of the urban network of Chania, Greece. 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 coordinated network-wide signal control that is particularly suitable for saturated traffic conditions. The presented results, although limited in space (two junctions) and time of evaluation, are promising for the particular site and for the control of urban networks in general as they indicate a superior performance of TUC compared to an established signal control strategy.

Field Evaluation of the Signal Control Strategy TUC at Three Urban Traffic Networks

TUC (Traffic-responsive Urban Control), a new generation, network-wide, traffic-responsive urban signal control strategy was developed originally in 1998, providing only split control. TUC had been implemented successfully in two small urban traffic networks and has been extensively tested - through simulation experiments - in many different urban traffic networks, where it was found to outperform optimized fixed time signal plans. Based on the initial success of TUC, the European Commission funded the research project SMART NETS (Signal MAnagement in Real Time for urban traffic NETworkS), whose main objectives were (a) the development of the cycle, offset and public transport priority control modules of TUC, and (b) the implementation of TUC in three different urban traffic networks (Chania, Greece; Munich, Germany; and Southampton, U.K.) and the evaluation/comparison of its performance with the three state-of-the-art strategies in place at each network (TASS, BALANCE and SCOOT, respectively). This paper reports on the evaluation/comparison results from the three networks. The main conclusions drawn from the evaluation/comparison results are that TUC is an easy-to-implement, inter-operable, easily transferable traffic control strategy that can provide a very efficient performance (that is better, or, at least, similar to the ones achieved by long-standing strategies that were very well fine-tuned over the years in the specific networks) with a minimum effort of fine-tuning. The implementation of TUC can result in very significant time and fuel savings, especially in traffic networks with no or poorly performing traffic control systems.

Application of the Extended Traffic Signal Control Strategy TUC to the Southampton Urban Road Network

The paper outlines the objectives and approach along with simulation results of the recent extensions of the traffic signal control strategy TUC (Traffic-responsive Urban Control). Based on well-known methods of the Automatic Control theory, TUC allows for the traffic-responsive coordinated signal control of large-scale urban networks aimed to be particularly efficient under saturated traffic conditions. Simulation investigations of the extended TUC application in a large part of the urban network of Southampton, UK, by use of the METACOR microscopic simulator, demonstrate the efficiency of the new signal control strategy.

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.

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 TUC's first field implementation and evaluation are also presented. Finally, summarising conclusions are drawn and future work is outlined.

Integrated Traffic-Responsive Urban Corridor Control Strategy in Glasgow, Scotland: Application and Evaluation

The new integrated traffic-responsive urban corridor control strategy IN-TUC (integrated traffic-responsive urban control) is presented. IN-TUC was developed and applied to the M8 corridor network in Glasgow, Scotland, within the European Telematics Applications in Transport project Telematics Applications in Bavaria, Scotland, and Others. The aim of the strategy, which is built on the well-known methods of the automatic control and optimization theories, is to provide, at suitably defined constant control intervals, traffic-responsive settings for the various control elements included in a corridor network area. The results of the preliminary simulation investigations as well as the results of the field implementation and evaluation of the strategy seem promising both for the particular site and for integrated corridor control systems in general.