Local Ramp Metering Research Articles

Real-Time Arterial-Friendly Ramp Metering System

To balance the benefits between the freeway and arterial users and also to prevent on-ramp queue spillbacks, the authors have developed an arterial-friendly local ramp metering control (AF-ramp) system for time-of-day operations during recurrent congestion. This study presents the real-time version of the AF-ramp (named RAF-ramp) system, with a lane-group-based macroscopic traffic module for predicting traffic state and for executing control strategies, aiming at maximizing the total throughput from the control area, comprising the ramp meter and nearby local intersection signals. Recognizing the discrepancy in the dynamic nature between ramp traffic and arterial flows, the RAF-ramp system with its embedded traffic state prediction and monitoring mechanism can trigger the concurrent optimization of both controls when justified to do so, or only dynamically adjust the ramp metering rate under the pre-optimized local signal environment. The results of extensive simulation experiments have confirmed that the proposed system outperforms the widely-applied real-time ramp control model, ALINEA/Q, under various experimental traffic scenarios, because the produced control strategies can effectively utilize the freeway’s weaving capacity and also best coordinate neighboring intersections’ signals to maximize the entire network’s performance. Such a real-time arterial-friendly ramp metering system, addressing both the time-varying freeway dynamics and the concerns of local traffic users, may well serve as an effective tool for contending with bottlenecks at freeway interchanges.

Arterial-Friendly Local Ramp Metering Control Strategy

To prevent local streets being blocked by overflowing on-ramp queues, a standard practice of ramp metering control is to restrain its function when a series of preset conditions are identified by on-ramp queue detectors. Such a trade-off between potential ramp queue spillback and the restraint resulting from the operation of metering control may often fail to either effectively mitigate bottlenecks caused by on-ramp waving or convince arterial users and local traffic agencies of the need for ramp metering operations. This study, therefore, presents an arterial-friendly local ramp metering system (named AF-ramp) that can achieve the target metering rate to produce optimal freeway conditions without ramp queues spilling back onto local streets. This is achieved by concurrently optimizing the signal plans for those intersections that send turning flows to the ramp. At this stage, this system has been developed for time-of-day control. It could also serve as the base module for extending to real-time control, or multi-ramp coordinated operations. The AF-ramp model, with its ability to optimize the arterial signals concurrently with the ramp metering rate, can ensure the best use of the capacity of local intersections and prevent any gridlock caused by overflows from on-ramp queue spillback or arterial turning traffic. With extensive simulation experiments, the evaluation results confirmed the AF-ramp model’s effectiveness in improving traffic conditions on both the freeway and its neighboring arterial links at the same time. This study has also introduced the real-time extension of the proposed model and a framework of a transition from the time-of-day control to fully responsive real-time operations.

A linear-quadratic-integral regulator for local ramp metering in the case of distant downstream bottlenecks

ABSTRACT This work develops and investigates the performance of a new control law, specifically a Linear-Quadratic Regulator augmented with integral action (LQI), for the local ramp metering control problem when bottlenecks are located many kilometers (up to 5 km) downstream of the metered on-ramp. LQI makes use of measurements all along the stretch extending from the controllable on-ramp to the bottleneck location, being therefore capable to improve the stability and robustness properties of the control loop, compared to alternative approaches (PI regulators) that employ measurements only from the bottleneck location. Simulation results reveal that: i) the proposed methodology handles efficiently the local ramp metering task in case of very distant downstream bottlenecks; and, ii) LQI is much less sensitive compared to other previously proposed control strategies.

Set-based multi-objective control of metered ramps at ring road junctions

ABSTRACTA set-theoretical approach is presented for a multi-objective control design of the local ramp metering problem. Two control objectives are specified: first, the optimization of traffic performance, by the minimization of total time spent. Second, the emission factor of needs to be minimized. The optimal state for traffic emission, however, lies in the unstable domain of the dynamic system. To dissolve this inconsistency, the control problem is formalized for the multi-objective optimization problem by using set-theoretical methods. For this purpose, the non-linear model METANET is rewritten in a shifted coordinate frame with a parameter-varying, polytopic representation. Bounds on state-, input- and disturbance variables are expressed by convex polytopes. These sets are then used for the design of an interpolated controller that is capable of improving traffic conditions according to the prescribed multi-objective criteria.

Traffic Model and On‐Ramp Metering Strategy under Foggy Weather Conditions Using T‐S Fuzzy Systems

Foggy weather seriously deteriorates the performance of freeway systems, particularly regarding traffic safety and efficiency. General macroscopic traffic models have difficulty reflecting the characteristics of a freeway under foggy weather conditions. In the present study, a macroscopic traffic model using a correction factor under foggy weather conditions is therefore proposed, which is regulated according to the different levels of visibility and curve radius of the freeway using the Takagi–Sugeno (T‐S) model. Based on the proposed traffic model, a local ramp metering strategy with density correction under foggy weather conditions is proposed to improve traffic safety. The proposed local ramp metering strategy regulates the on‐ramp flow using the T‐S model according to the mainstream density, speed, and visibility. The correction factors are determined based on the parameters of the consequent part in the T‐S model, which are optimized using the particle swarm optimization algorithm. The sum of the mean absolute percentage error of the mainstream traffic density and speed is used to evaluate the proposed traffic model. The real‐time crash‐risk prediction model, which reflects the degree of traffic safety, is used to evaluate the proposed local ramp metering strategy. Simulations using VISSIM and MATLAB show that the proposed traffic model is suitable under foggy weather conditions and that the proposed local ramp metering strategy achieves a better performance in reducing fog‐related crashes.

Evaluating the combined effect of ramp metering and variable speed limits on the French A25 motorway

Abstract Despite the large body of literature on active traffic management (ATM) and post hoc evaluation, few are the studies assessing the impact of a combination of ATM strategies implemented in the field. In this paper, we present and evaluate the innovative implementation of a speed regulation scheme combined with local ramp metering. The evaluation is based on field data and the assessment criteria include travel time, travel time variability, capacity and level of service (LOS) under three regimes: (i) no control, (ii) ramp metering, and (iii) ramp metering combined with variable speed limits. Our findings confirm that ramp metering is beneficial to users and suggest that the combination of ATM measures further extends these benefits. However, travel time savings, travel time reliability improvement, and LOS gains are limited to the regulated section and do not affect downstream sections.

Ramp metering for flow maximisation and emission reduction – a set-based multi-objective design approach

A set-theoretical approach is presented for a multi-objective control design of the local ramp metering problem. Two control objectives are specified: first, the optimization of traffic performance, by the minimization of total time spent.Second, the emission factor of CO2 is minimized. The optimal state for traffic emission however lies in the unstable domain of the system. To resolve this inconsistency, the control problem is formalized in a set-theoretical context. For this purpose, the nonlinear METANET model is rewritten in a shifted coordinate frame in a parameter-varying, polytopic representation. Bounds on state-, input- and disturbance variables are expressed by convex polytopes. These sets are then used for the design of an interpolated H∞ controller that is capable of improving traffic conditions according to the prescribed multi-objective criteria.

Assessing Need for Systemwide Ramp Metering Installation Warrants

Warrants for ramp metering installation have been developed by a number of U.S. states. These warrants are generally simple and are based on the traffic, geometry, and safety conditions in the immediate vicinity of each ramp (local conditions). However, advanced applications of ramp metering use system-based metering algorithms that involve metering a number of on-ramps to address system bottlenecks. These algorithms have been proved to perform better compared with local ramp metering algorithms. This situation creates a disconnect between existing agency metering warrants to install the meters and the subsequent management and operations of the ramp meters. This study focused on assessing the need for system warrants in addition to local warrants for ramp metering installation to prevent traffic breakdown at bottleneck locations. A linear programming formulation combined with consideration of the stochasticity of bottleneck capacity was used to select the ramps to be metered on the basis of the system bottlenecks. The study found that the selection of these ramps for metering—in addition to those justified by local warrants—could delay the breakdown at the system bottleneck location and improve the performance of the freeway main line. Another important benefit of selecting ramps for metering based on system operations was its distribution of on-ramp delays because of metering of more ramps and thus to a reduction in the delay experienced on the ramps selected with the existing warrants that were based on local conditions.

Local Ramp Metering Strategy ALINEA: Microscopic Simulation Based Evaluation Study on Istanbul Freeways

Abstract: Freeway networks are designed to provide a flexible flow of vehicles and uninterrupted routes especially in the metropolitan areas where the traffic volumes are considerably high. However; when the traffic volumes reach the highway capacity, speed differentials occur leading to phenomenon of congestion which either can be recurrent in peak hours or nonrecurrent in case of having an incident on the highway. Congestions are considered a case of matter as the freeway network performance is adversely affected in terms of reducing the speed, increasing the travel time, and increasing the vehicle emissions due to increase the fuel consumption. Also the distraction during congestion period, can increase the probability of accidents occurrence, where all drivers try to pass the congested segment of the freeway. For instance the structural solutions for congestion has become inefficient for economic, urban and environmental considerations. Thus, since 1960s the trend have been changed to control the link traffic and optimize its capacity by using coordinated and integrated surveillance and control strategies. For the recent decades ramp metering strategies are noticed to be an effective approach for controlling and managing the freeway traffic. This paper depicting a microscopic simulation based evaluation case study for local ramp metering strategy ALINEA on a segment of D-100 freeway in Istanbul using the microscopic simulator VISSIM integrated with MATLAB.

A self-learning system for local ramp metering with queue management

ABSTRACTThis paper presents the design and evaluation process of a self-learning system for local ramp metering control. This system is developed on the basis of reinforcement learning (RL) and can deal with the problem of on-ramp queue management through a continuous learning process. A general framework of the system design including the definition of RL elements and an algorithm that can accomplish the learning process is proposed. Simulation tests are carried out to evaluate the performance of the new system. In terms of the total time spent by road users, the new system can achieve a 30% reduction from the situation of no control, a result which is competitive with the widely accepted algorithm ALINEA. Meanwhile, simulation results show that the new system can keep on-ramp queues strictly under a series of pre-specified constraints, which proves its capability of managing on-ramp queues.

Will a higher free-flow speed lead us to a less congested freeway?

An approach based on cell transmission model (CTM) is proposed to estimate the impact of variable free-flow speeds (FFS) on the performance of a freeway system. Based on the basic CTM, four typical freeway control strategies consisting of non control, local ramp metering, coordinated ramp metering and global control are first formulated. Then the method of adjusting model parameters to the changed free-flow speeds is presented. Among the adjustments, an experimental function based on Fan and Seibold (2014) is proposed to change the jam density. Several useful measures are defined to estimate and compare the performances of different freeways. The following three main observations are obtained from numerical experiments. (a) With the gradually increasing FFS, the throughput of freeway will increase at the beginning and then change to decrease. (b) With the increasing FFS, the average delay of vehicles will decrease at the beginning and then change to increase. (c) A series of free-flow speeds associate with the best performance of freeway. These observations are theoretically analyzed through investigating the location and capacity of bottleneck. Study shows that in general the actual bottleneck capacity will increase at the beginning and then change to decrease with the continually increasing FFS. In view of the positive correlation between traffic delay and bottleneck capacity, the theoretical analysis confirms the numerical observations. The findings of this study can deepen the understanding of freeway systems and help management agents adopt proper measures to improve the performance of the whole system.

Literature Review of Advancements in Adaptive Ramp Metering

Over a period spanning more than 30 years, several ramp metering algorithms have been developed to improve the operation of freeways. Many of these algorithms were deployed in several regions of the world, and field evaluations have shown their significance to improve traffic conditions on freeways and ramps. Previous reviews of ramp metering algorithms focused more on the research outcomes and evaluations of traditional metering algorithms developed in the early stage of ramp metering research. The purpose of this paper is to cover the more recent developments in ramp metering in relation to the traditional metering strategies. Several local and coordinated ramp metering algorithms were reviewed. In summary, Asservissement Linéaire d’Entrée Autoroutière (ALINEA) was found to be the most widely deployed local ramp metering strategy. The algorithm is simple and implementation costs less than other strategies. It also guarantees the targeted performance goals provided that the on-ramp has sufficient storage. Several extensions were proposed in the literature to fine-tune its performance. Among the coordinated metering strategies, zone based metering is simple to implement and easy to re-configure. System-wide adaptive ramp metering (SWARM) algorithm is more sensitive to calibrate for accurate prediction of traffic states. Heuristic ramp-metering coordination (HERO) algorithm can be useful if both local and coordinated control are desired particularly if the local control is using ALINEA. Fuzzy logic based algorithms are gaining popularity because of the simplicity and the fast re-configuration capability. Advanced real time metering system (ARMS) seems theoretically promising because of its proactive nature to prevent congestion; however, its performance is highly dependent upon accurate predictions. Finally, some guidelines were proposed for future research to develop new proposals and to extend the existing algorithms for guaranteed performance solutions.

Set‐theoretic analysis of the isolated ramp metering problem

SummaryAnalysis of ramp metering, as an effective freeway traffic control solution, is focused in the paper. The studied traffic control problem is discussed in a set‐theoretic context in order to quantitatively characterize its effectivenes. The notions of maximal robust controlled invariant set, as well as t‐step robust controllable set are defined and used for analyzing the ramp metering problem independently of the control policy applied. Algorithms are developed to compute these sets, with special attention to their practical interpretations. Numerical examples with graphical representation of the proposed methodology are given to examine local ramp metering and conclude implications to control strategies. Copyright © 2015 John Wiley & Sons, Ltd.

Local ramp metering with distant downstream bottlenecks: A comparative study

The well-known feedback ramp metering algorithm ALINEA can be applied for local ramp metering or included as a key component in a coordinated ramp metering system. ALINEA uses real-time occupancy measurements from the ramp flow merging area that may be at most a few hundred meters downstream of the metered on-ramp nose. In many practical cases, however, bottlenecks with smaller capacities than the merging area may exist further downstream, which suggests using measurements from those downstream bottlenecks. Recent theoretical and simulation studies indicate that ALINEA may lead to poorly damped closed-loop behavior in this case, but PI-ALINEA, a suitable Proportional-Integral (PI) extension of ALINEA, can lead to satisfactory control performance. This paper addresses the same local ramp-metering problem in the presence of far-downstream bottlenecks, with a particular focus on the employment of PI-ALINEA to tackle three distinct cases of bottleneck that may often be encountered in practice: (1) an uphill case; (2) a lane-drop case; and (3) an un-controlled downstream on-ramp case. Extensive simulation studies are conducted on the basis of a macroscopic traffic flow model to show that ALINEA is not capable of carrying out ramp metering in these bottleneck cases, while PI-ALINEA operates satisfactorily in all cases. A field application example of PI-ALINEA is also reported with regard to a real case of far downstream bottlenecks. With its control parameters appropriately tuned beforehand, PI-ALINEA is found to be universally applicable, with little fine-tuning required for field applications.

Ramp Metering Control Based on the Q-Learning Algorithm

Abstract Modern urban highways are under the influence of increased traffic demand and cannot fulfill the desired level of service anymore. In most of the cases there is no space available for any infrastructure building. Solutions from the domain of intelligent transport systems are used, such as ramp metering. To cope with the significant daily changes of the traffic demand, various approaches with autonomic properties like self-learning are applied for ramp metering. One of these approaches is reinforced learning. In this paper the Q-Learning algorithm is applied to learn the local ramp metering control law in a simulation environment, implemented in a VISSIM microscopic simulator. The approach proposed is tested in simulations with emphasis on the mainstream speed and travel time, using a typical on-ramp configuration.

Coordinated Ramp Metering Based on On-Ramp Saturation Time Synchronization

In this paper, a coordinated ramp-metering approach is proposed; the approach is based on the synchronization of the time it takes for an on-ramp to run out of space. The time that congestion and the associated capacity drop can be prevented at a freeway bottleneck by means of ramp metering depends on the available ramp space for temporarily storing the vehicles. For a single on-ramp, the available space and thus the metering time at the bottleneck are often limited. By means of coordination, upstream storage space can be used to prevent a breakdown for a longer period of time. To accomplish that aim, upstream ramps need to reduce their inflow into the mainstream with respect to their own metering task. The extent to which upstream inflow reductions are effectively used to extend the metering time at the bottleneck is determined by the order and timing at which the coordinated ramps run out of space. The proposed approach aims at always saturating the more upstream-located ramps before more downstream-located ones; that is, the ramps run out of space in the downstream direction to make sure that all realized assistance is used by the ramp that is metering at the bottleneck. By means of a simulation test case, the functioning of the algorithm is demonstrated and compared with a no-control scenario, local ramp metering, and an alternative coordination algorithm that aims at filling the ramps equally. Both coordination approaches strongly improve the network performance with respect to local ramp metering, but the proposed coordination approach is able to postpone the breakdown for a longer period of time.

Local Ramp Metering in the Presence of a Distant Downstream Bottleneck: Theoretical Analysis and Simulation Study

The well-known feedback ramp metering algorithm ALINEA can be applied for local ramp metering or used as a key component in a coordinated ramp metering system. ALINEA uses real-time occupancy measurements from the ramp-flow merging area that may be at most few hundred meters downstream of the metered on-ramp nose. In many practical cases, however, bottlenecks with smaller capacity than the merging area may exist further downstream for various reasons, which suggests using measurements from those further downstream bottlenecks rather than from the merging area. This paper addresses the local ramp metering problem in such a downstream bottleneck case. Theoretical analysis indicates that ALINEA may lead to a poorly damped closed-loop behavior in this case, but PI-ALINEA, which is a suitable proportional-integral (PI) extension of ALINEA, can lead to satisfactory control performance. The stability of the closed-loop ramp metering system with PI-ALINEA is rigorously proved by Lyapunov stability arguments. The root locus method is also employed to analyze the linearized closed-loop system performance of ALINEA and PI-ALINEA with and without a downstream bottleneck to provide insights on both controllers' performance. Simulation studies are conducted using a macroscopic traffic flow model to demonstrate that the ramp metering performance of ALINEA indeed deteriorates in the distant downstream bottleneck case, whereas a significant improvement is obtained using PI-ALINEA. Moreover, with its control parameters appropriately tuned, PI-ALINEA is found to be universally applicable to a range of distances between the on-ramp and downstream bottlenecks. This indicates that little fine-tuning would be necessary in field applications.

Improved bottleneck approach for heuristic systemwide responsive ramp metering on congested freeways

Ramp metering has been shown to be an efficient and direct measure of alleviating congestion caused by many factors, and many algorithms have been developed and implemented in the real world. Based on the conventional Bottleneck approach, an improved Bottleneck heuristic coordinated metering algorithm is proposed in this paper for managing the ramp meters so as to solve or mitigate the mainline congestion issue caused by factors such as freeway traffic incidents. In this approach, first, the local ramp metering rate is determined through the conventional lookup table approach, and then using density instead of volume as the control variable, a Proportional-Integral (PI) controller is designed to compute the system/coordinated metering rate; finally, the final metering rate is selected using the conventional minimum or maximum rule depending on the comparison between the target and current traffic densities. Taking the ramp system of Nanjing-Hangzhou Freeway as an example, the proposed improved Bottleneck algorithm is implemented in a simulated environment, and the results confirmed the effectiveness of the improved Bottleneck algorithm.

Incident parameter scheduled freeway traffic control - a ramp meter approach

A novel model based local ramp metering method is presented in the paper by means of incident scheduled freeway traffic control solution. First, second order macroscopic freeway model is used with appropriate incident parametrization to describe eventual and unattended traffic variation caused by off-nominal traffic conditions (e.g. accidents). These traffic anomalies are captured by adequate model parameters, i.e. incident parameters that can be on-line estimated. The paper is motivated by incident scheduled ramp-meter solution to encounter real-time incident parameter information. The main idea is to use local freeway control solution triggered by available incident parameter values. The proposed approach is local in the sense of considering only non-coordinated ramp meter solution, first. Furthermore, we apply locally optimal (linearized) control solution to satisfy throughput maximization objective. The formal controller synthesis involves parameters to correct, compensate the effect of incidents. The proposed method is evaluated and compared to other existing approach by using simulation environment.

Evaluation of HERO-Coordinated Ramp Metering Installation at M1 and M3 Freeways in Queensland, Australia

The recently developed traffic-responsive feedback control strategy HERO (heuristic ramp metering coordination), which coordinates local ramp-metering actions in freeway networks, was implemented on the M1 and M3 freeways in Queensland, Australia. HERO employs an extended version of the feedback regulator ALINEA at the local level; it outperforms uncoordinated local ramp metering and approaches the efficiency of sophisticated optimal control schemes. HERO has been implemented by the Department of Transport and Main Roads of the State of Queensland at six on-ramps of the M1 and M3 freeways. The results show significant improvements in traffic throughput and travel times compared with the previously used fixed-rate ramp-metering system. A rapid economic benefit analysis determined a benefit–cost ratio of 13.8:1 at a 7% discount rate and, therefore, an extremely strong economic merit for the implementation of HERO. The economic payback period for the capital expenditure on this pilot is approximately 4 months.