Ramp-metering Algorithm Research Articles

FIELD EVALUATION OF THE FUZZY LOGIC BASED RAMP METERING ALGORITHM ACCEZZ

The ACCEZZ ramp metering algorithm is an adaptive control approach based on Fuzzy Logic. Results from its calibration and validation as well as its evaluation using a microscopic simulation show how different control strategies can improve traffic conditions especially during peak hours. To evaluate the potential of ramp metering the ramp metering software TRANSRAMP has been developed, implemented and tested at a demonstration site in Munich (Germany). Since December 1st, 2005 TRANSRAMP controls traffic at two consecutive on ramps successfully with the ACCEZZ algorithm. Data for a cross-algorithm (with ALINEA) and a cross-site evaluation will be collected until April 2006 within the European research project EURAMP.

Set of New Traffic-Responsive Ramp-Metering Algorithms and Microscopic Simulation Results

A novel switching traffic-responsive ramp-metering controller adapts to different traffic dynamics under different congestion conditions: free-flow or congested. The approach of multirate linear quadratic control with integral action is used to compensate for disturbances and to accommodate the difference between the model sampling time and the metering-rate update interval. In addition, a queue length regulator is designed to prevent the queue from exceeding the ramp storage capacity and yield improved performance over the current ad hoc queue override scheme. Subsequently, a queue length estimator is designed to provide feedback to the queue length regulator with the queue-detector speed data that are available in the field. A local ramp-metering control strategy is proposed to achieve the control goal of reducing the spatial and temporal span of the congestion, while satisfying the on-ramp storage capacity constraints, by using locally available information. Test results on a calibrated microscopic traffic simulator demonstrate the performance and effectiveness of the switching ramp-metering controller, the queue length estimator and regulator, and the overall control strategy. The total vehicle and passenger congestion delays are both reduced by 16%, and the total travel time is improved by 5.6%. As a comparison, simulation results of ALINEA are also presented.

Set of New Traffic-Responsive Ramp-Metering Algorithms and Microscopic Simulation Results

A novel switching traffic-responsive ramp-metering controller adapts to different traffic dynamics under different congestion conditions: free-flow or congested. The approach of multirate linear quadratic control with integral action is used to compensate for disturbances and to accommodate the difference between the model sampling time and the metering-rate update interval. In addition, a queue length regulator is designed to prevent the queue from exceeding the ramp storage capacity and yield improved performance over the current ad hoc queue override scheme. Subsequently, a queue length estimator is designed to provide feedback to the queue length regulator with the queue-detector speed data that are available in the field. A local ramp-metering control strategy is proposed to achieve the control goal of reducing the spatial and temporal span of the congestion, while satisfying the on-ramp storage capacity constraints, by using locally available information. Test results on a calibrated microscopic traffic simulator demonstrate the performance and effectiveness of the switching ramp-metering controller, the queue length estimator and regulator, and the overall control strategy. The total vehicle and passenger congestion delays are both reduced by 16%, and the total travel time is improved by 5.6%. As a comparison, simulation results of ALINEA are also presented.

Performance Evaluation of Adaptive Ramp-Metering Algorithms Using Microscopic Traffic Simulation Model

Adaptive ramp metering has undergone significant theoretical developments in recent years. However, the applicability and potential effectiveness of such algorithms depend on a number of complex factors that are best investigated during a planning phase prior to any decision on their implementation. The use of traffic simulation models can provide a quick and cost-effective way to evaluate the performance of such algorithms prior to implementation on the target freeway network. In this paper, a capability-enhanced PARAMICS simulation model has been used in an evaluation study of three well-known adaptive ramp-metering algorithms: ALINEA, BOTTLE- NECK, and ZONE. ALINEA is a local feedback-control algorithm, and the other two are areawide coordinated algorithms. The evaluation has been conducted in a simulation environment over a stretch of the I-405 freeway in California, under both recurrent congestion and incident scenarios. Simulation results show that adaptive ramp-metering algorithms can reduce freeway congestion effectively compared to the fixed-time control. ALINEA shows good performance under both recurrent and nonrecurrent congestion scenarios. BOTTLENECK and ZONE can be improved by replacing their native local occupancy control algorithms with ALINEA. Compared to ALINEA, the revised BOTTLENECK and ZONE algorithms using ALINEA as the local control algorithm are found to be more efficient in reducing traffic congestion than ALINEA alone. The revised BOTTLENECK algorithm performs robustly under all scenarios. The results also indicate that ramp metering becomes less effective when traffic experiences severe congestion under incident scenarios.

Macroscopic traffic flow modelling and ramp metering control using Matlab/Simulink

Computer programs to simulate traffic flow offer an opportunity to evaluate new strategies for reducing delays, congestion, fuel consumption and pollution. This paper describes a Statistical Traffic Model or STM, which is based on accepted macro-modelling concepts, such as the conservation of vehicles and the fundamental traffic diagram. In this case, the model is constructed using the well known Matlab/Simulink ™ software package, so providing an integrated approach for data processing, graphical presentation of data, control system design and macroscopic simulation in one straightforward to use, widely available environment. To illustrate the methodology, the STM is applied to a section of the M3/M27 Ramp Metering Pilot Scheme in the UK. This Highways Agency sponsored project, based in the Southampton area, utilises traffic lights at the on-ramp entrances to regulate access to the main carriageway of the motorway, in an attempt to maintain flow close to the capacity. The paper utilises the model to help design a locally-coordinated ramp metering algorithm, based on proportional-integral-plus (PIP) control methods. In this manner, the STM proves particularly valuable for the application of multi-objective optimisation techniques in the design of new traffic management systems.

Freeway ramp metering: an overview

Recurrent and nonrecurrent congestion on freeways may be alleviated if today's "spontaneous" infrastructure utilization is replaced by an orderly, controllable operation via comprehensive application of ramp metering and freeway-to-freeway control, combined with powerful optimal control techniques. This paper first explains why ramp metering can lead to a dramatic amelioration of traffic conditions on freeways. An overview of ramp metering algorithms is provided next, ranging from early fixed-time approaches to traffic-responsive regulators and to modern sophisticated nonlinear optimal control schemes. Finally, a large-scale example demonstrates the high potential of advanced ramp metering approaches.

Evaluation of ramp control algorithms using microscopic traffic simulation

Ramp metering has emerged as an effective freeway control measure to ensure efficient freeway operations. A number of algorithms have been developed in recent years to ensure an effective use of ramp metering. As the performance of ramp metering depends on various factors (e.g. traffic volume, downstream traffic conditions, queue override policy etc), these algorithms should be evaluated under a wide range of traffic conditions to check their applicability and performance and to ensure their successful implementation. In view of the expenses of and confounding effects in field testing, simulation plays an important role in the evaluation of such algorithms. This paper presents an evaluation study of two ramp metering algorithms: ALINEA and FLOW. ALINEA is a local control algorithm and FLOW is an area wide coordinated algorithm. The purpose of the study is to use microscopic simulation to evaluate systematically how the level of traffic demand, queue spillback handling policy and downstream bottleneck conditions affect the performance of the algorithms. It is believed that these variables have complex interactions with ramp metering. MITSIM microscopic traffic simulator is used to perform the empirical study. The study consists of two stages. In the first stage, key input parameters for the algorithms were identified and calibrated. The calibrated parameters were then used for the second stage, where the performance of the algorithms were compared with respect to three traffic variables mentioned above using an orthogonal fraction of experiments. Regression analysis was used to identify the impacts of some of the interactions among experimental factors on the algorithms' performance, which is not otherwise possible with a tabular analysis. These results provide insights which may be helpful for design and calibration of more efficient ramp control algorithms.

Modeling Network Travel Time Impact of Freeway Ramp Metering

Whether freeway ramp metering can reduce total travel time in a corridor of several alternative routes depends on changes in route volumes and travel times. Ramp metering effectiveness and ramp metering algorithms have been evaluated mainly on the basis of improved freeway operations. Most studies have not evaluated the impact on alternative routes because of the complexity of the problem (e.g., which routes and what lengths of routes should be studied). An analysis of ramp metering impact in a network corridor is presented, first for simple steady-state cases and then for more complex cases involving time-varying demand, upstream and downstream queueing on freeway and alternative routes, and variable ramp metering rates based on freeway conditions. Time-varying examples are solved with a dynamic traffic assignment model called DYMOD. The analysis shows that ramp metering yields total travel time savings if (a) downstream freeway capacities are sufficiently restrictive, and (b) competitive alternative routes exist to accommodate the diverted traffic. The conditions under which ramp metering can be effective is illustrated by an examination of these simplified cases, and a useful modeling approach to analyzing systemwide impact in a larger corridor is demonstrated.

Fuzzy Ramp Metering: Design Overview and Simulation Results

A fuzzy logic ramp-metering algorithm was designed to overcome the limitations of conventional ramp-metering strategies. The fuzzy controller demonstrated improved robustness, prevented heavy congestion, intelligently balanced conflicting needs, and tuned easily. The objective was to maximize total distance traveled and minimize total travel time and vehicle delay, while maintaining acceptable ramp queues. A multiple-ramp study site from the Seattle I-5 corridor was modeled and tested using the freeway simulation software, FRESIM. For five of the six testing sets, encompassing a variety of traffic conditions, the fuzzy controller outperformed the three other controllers tested.

Aid to Determining Freeway Metering Rates and Detecting Loop Errors

A recent freeway congestion prediction study for the Washington Department of Transportation (WSDOT) found that the sum of storage rates over time, SumSR(t), for a freeway section was a better variable for determining the best upstream ramp metering rates than the storage rate for time interval t, SR(t), which is the current WSDOT criterion. (Use of the SumSR(t) variable for this purpose requires that the summation be started during a period of low density flows.) Another finding was that the SumSR(t) variable was a better detector of loop “chattering” errors than WSDOT's current criterion, which misses chattering errors that occur at normal traffic volume levels. Since calculation of SumSR(t) is easily incorporated in the current WSDOT ramp metering algorithm, the writer recommends its use in futute WSDOT freeway metering schemes.

Some general results on the optimal ramp control problem

In an effort to relieve peak hour congestion on freeways, various ramp metering algorithms have been employed to regulate the inputs to freeways from entry ramps. In this paper, we consider a freeway system comprised of a freeway section and its entry/exit ramps, and formulate the ramp control problem as a dynamic optimal process to minimize the total time spent in this system. Within this framework, we are able to show when ramp metering is beneficial to the system in terms of total time savings, and when it is not, under the restriction that the controlled freeway has to serve all of its ramp demand, and the traffic flow process follows the rules prescribed by the LWR theory with a triangular flow-density relationship. We also provide solution techniques to the problem and present some preliminary numerical results and empirical validation.