Pareto-improving ramp metering strategies for reducing congestion in the morning commute

This paper presents an alternative approach to internalize congestion externality during the morning commute. We consider a linear freeway with multiple on-ramps and a downstream bottleneck and commuters accessing the freeway via different on-ramps try to arrive at work on time. Rather than charging congestion tolls as widely suggested by economists, we show that the old-fashioned engineering approach – ramp metering – can be a powerful tool to affect travelers’ departure time choice and thereby alter the congestion externality distribution among travelers. With carefully designed time-dependent metering plans, travelers from different origins can be channelized and will access the freeway bottleneck in different time periods, resulting in less total cost for the system compared to the no-metering case. The metering strategies are Pareto-improving, with travelers from the on-ramp with the highest priority having the smallest individual costs and travelers from the on-ramp with the lowest priority having their costs equal to those in the no-metering scenario. By changing the priority order of the ramps periodically, the benefit of the Pareto-improving metering strategies can be distributed evenly among all travelers. Numerical experiments show that the total user cost can be reduced by up to 40% with the proposed metering strategies. This study offers researchers and policy makers a different angle of looking at congestion externality, and the results provide an overview of the potential long term benefits that dynamic ramp metering strategies can achieve.     

Ramp metering and freeway bottleneck capacity

This study aims to determine whether ramp meters increase the capacity of active freeway bottlenecks. The traffic flow characteristics at 27 active bottlenecks in the Twin Cities have been studied for seven weeks without ramp metering and seven weeks with ramp metering. A methodology for systematically identifying active freeway bottlenecks in a metropolitan area is proposed, which relies on two occupancy threshold values and is compared to an established diagnostic method – transformed cumulative count curves. A series of hypotheses regarding the relationships between ramp metering and the capacity of active bottlenecks are developed and tested against empirical traffic data. It is found that meters increase the bottleneck capacity by postponing and sometimes eliminating bottleneck activations, accommodating higher flows during the pre-queue transition period, and increasing queue discharge flow rates after breakdown. Results also suggest that flow drops after breakdown and the percentage flow drops at various bottlenecks follow a normal distribution. The implications of these findings on the design of efficient ramp control strategies, as well as future research directions, are discussed.     

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.     

Queue length estimation at metered freeway‐to‐freeway connectors

Freeway‐to‐freeway connector metering is a cost‐effective and proven freeway management strategy for relieving recurrent congestion. However, one of the critical challenges in design and operation of freeway‐to‐freeway connector metering is the lack of up‐to‐date queue storage length design guidance. In this study, it was found that ramp queue is dynamically related to the metering rate, on‐ramp demand, and traffic flow arrival pattern. Hence, simply using an average demand cannot provide accurate queue length estimation and is also not suitable for queue storage design where the maximum or a percentile queue length is generally used. A mesoscopic queue length simulation model was developed based on the input–output method for estimating queue lengths under various demand‐to‐capacity ratio scenarios. Simulation results indicate that for under‐saturated situations, the ramp queue may exist temporally due to the random short‐term surge of traffic arrivals, and the exponential function could best capture the relationship between queue length and demand‐to‐capacity ratio. For over‐saturated situations, the ramp queue tends to prolong linearly with the demand‐to‐capacity ratio. Based on the simulation, it was recommended that queue storage length be designed as 4.3% of on‐ramp demand when demand is lower than 1200 vph or 2.3% when demand is between 1200 and 2400 vph. Copyright © 2016 John Wiley & Sons, Ltd.     

Stochasticity of freeway operational capacity and chance-constrained ramp metering

The notion of capacity is essential to the planning, design, and operations of freeway systems. However, in the practice freeway capacity is commonly referred as a theoretical/design value without consideration of operational characteristics of freeways. This is evident from the Highway Capacity Manual (HCM) 2000 in that no influence from downstream traffic is considered in the definition of freeway capacity. In contrast to this definition, in this paper, we consider the impact of downstream traffic and define freeway operational capacity as the maximum hourly rate at which vehicles can be expected to traverse a point or a uniform section of a roadway under prevailing traffic flow conditions. Therefore freeway operational capacity is not a single value with theoretical notion. Rather, it changes under different traffic flow conditions. Specifically, this concept addresses the capacity loss during congested traffic conditions. We further study the stochasticity of freeway operational capacity by examining loop detector data at three specifically selected detector stations in the Twin Cities’ area. It is found that values of freeway operational capacity under different traffic flow conditions generally fit normal distributions. In recognition of the stochastic nature of freeway capacity, we propose a new chance-constrained ramp metering strategy, in which, constant capacity value is replaced by a probabilistic one that changes dynamically depending on real-time traffic conditions and acceptable probability of risk determined by traffic engineers. We then improve the Minnesota ZONE metering algorithm by applying the stochastic chance constraints and test the improved algorithm through microscopic traffic simulation. The evaluation results demonstrate varying degrees of system improvement depending on the acceptable level of risk defined.     

Creating complex congestion patterns via multi-objective optimal freeway traffic control with application to cyber-security

This article presents a study on freeway networks instrumented with coordinated ramp metering and the ability of such control systems to produce arbitrarily complex congestion patterns within the dynamical limits of the traffic system. The developed method is used to evaluate the potential for an adversary with access to control infrastructure to enact high-level attacks on the underlying freeway system. The attacks are executed using a predictive, coordinated ramp metering controller based on finite-horizon optimal control and multi-objective optimization techniques. The efficacy of the control schemes in carrying out the prescribed attacks is determined via simulations of traffic network models based on the cell transmission model with onramps modeled as queue buffers. Freeway attacks with high-level objectives are presented on two illustrative examples: congestion-on-demand, which aims to create precise, user-specified pockets of congestion, and catch-me-if-you-can, which attempts to aid a fleeing vehicle from pursuant vehicles.     

Ramp meters on trial: Evidence from the Twin Cities metering holiday

Ramp meters in the Twin Cities have been the subject of a recent test of their effectiveness, involving turning them off for eight weeks. This paper analyzes the results with and without ramp metering for several representative freeways during the afternoon peak period. Seven performance measures: mobility, equity, productivity, consumers’ surplus, accessibility, travel time variation and travel demand responses are compared. It is found that ramp meters are particularly helpful for long trips relative to short trips. Ramp metering, while generally beneficial to freeway segments, may not improve trip travel times (including ramp delays). The reduction in travel time variation comprises another benefit from ramp meters. Non-work trips and work trips respond differently to ramp meters. The results are mixed, suggesting a more refined ramp control algorithm, which explicitly considers ramp delay, is in order.     

Genetic algorithm-based simulation optimization of the ALINEA ramp metering system: a case study in Atlanta

ABSTRACT

This paper presents a case study of the optimal ALINEA ramp metering system model of a corridor of the metro Atlanta freeway. Based on real-world traffic data, this study estimates the origin-destination matrix for the corridor. Using a stochastic simulation-based optimization framework that combines a micro-simulation model and a genetic algorithm-based optimization module, we determine the optimal parameter values of a combined ALINEA ramp metering system with a queue flush system that minimizes total vehicle travel time. We found that the performance of ramp metering with optimized parameters, which is very sensitive possibly because bottlenecks are correlated, outperforms the no control model with its optimized parameters in terms of reducing total travel time.     

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.     

Evaluation of forced flows on freeways with single‐loop detectors

This paper documents the development of a simple method for identifying and/or predicting freeway congestion using single loop detection systems. The proposed algorithm is simple and easy to incorporate into most freeway management systems. The Washington State Department of Transportation's Traffic Systems Management Center (TSMC) sponsored the original study. The investigation also led to a recommendation to replace the original TSMC definition of congestion or forced flow conditions with a more reliable indicator. Although, the TSMC has recently implemented a more advanced prediction system based on fuzzy set theory and neural networks to further identify patterns and rules for ramp metering strategies, the findings presented here continue to be constructive to freeway managers looking for quick and easy analyses that rely solely on single‐loop detection systems. The Seattle Area freeway study section used for the original study was the portion of mainline 1–5 northbound starting at the downtown Seattle Station 108 and ending at the Mountlake Terrace Station 193. Several days' worth of volume and lane‐occupancy data were collected for the afternoon time period from 2:30 p.m. to 6:30 p.m. Time intervals of 20 seconds were chosen for each data collection period. Important products of this research include the following:

• simple, and more reliable criterion for the definition of “bottleneck” or forced flow conditions than that originally used by the TSMC.
• simple, and reliable criterion for predicting impending “bottlenecks” or forced flow conditions.
• A proposed variable for improved selection of the appropriate metering rate. (Further analysis of the use of this variable for determining metering rates is recommended for future studies.

The proposed criteria are simple and easy to incorporate into current freeway management computer systems. Further investigation of freeway performance measurement using volume and occupancy data obtained from single‐loop systems is currently being performed.     

Real-time crash prediction for expressway weaving segments

Weaving segments are potential recurrent bottlenecks which affect the efficiency and safety of expressways during peak hours. Meanwhile, they are one of the most complicated segments, since on- and off-ramp traffic merges, diverges and weaves in the limited space. One effective way to improve the safety of weaving segments is to study crash likelihood using real-time crash data with the objective of, identifying hazardous conditions and reducing the risk of crashes by Intelligent Transportation Systems (ITS) traffic control. This study presents a multilevel Bayesian logistic regression model for crashes at expressway weaving segments using crash, geometric, Microwave Vehicle Detection System (MVDS) and weather data. The results show that the mainline speed at the beginning of the weaving segments, the speed difference between the beginning and the end of weaving segment, logarithm of volume have significant impacts on the crash risk of the following 5–10 min for weaving segments. The configuration is also an important factor. Weaving segment, in which there is no need for on- or off-ramp traffic to change lane, is with high crash risk because it has more traffic interactions and higher speed differences between weaving and non-weaving traffic. Meanwhile, maximum length, which measures the distance at which weaving turbulence no longer has impact, is found to be positively related to the crash risk at the 95% confidence interval. In addition to traffic and geometric factors, wet pavement surface condition significantly increases the crash ratio by 77%. The proposed model along with ITS, e.g., ramp metering, Dynamic Message Sign (DMS), and high friction surface treatment can be used to enhance the safety of weaving segments in real-time.     

Efficiency and equity properties of freeway network-wide ramp metering with AMOC

The Advanced Motorway Optimal Control (AMOC) strategy for optimal freeway network-wide ramp metering is applied to the ring-road of Amsterdam, The Netherlands, in the aim of investigating some important and interesting problems arising in ubiquitous ramp metering systems. A number of suitably chosen scenarios along with a thorough analysis, interpretation, and suitable visualization of the obtained results provide a basis for the better understanding of some complex interrelationships of competing performance criteria. More precisely, the strategy’s efficiency and equity properties as well as their trade-off are studied and their partially competitive behaviour is discussed. This trade-off is implicitly addressed by the AMOC strategy through consideration of the available ramp storage space and may be used as a tool to establish a desired policy of the system’s efficiency versus equity.     

Developing control strategies for freeway merging points under congested traffic situations using modeling and a simulation approach

This work focuses on developing a variety of strategies for alleviating congestion at freeway merging points as well as improving the safety of these points. On the Tokyo Metropolitan Expressway, traffic congestion frequently occurs at merging bottleneck sections, especially during heavy traffic demand. The Tokyo Metropolitan Expressway public corporation, generally applies different empirical strategies to increase the flow rate and decrease the accident rate at the merging sections. However, these strategies do not rely either on any behavioral characteristic of the merging traffic or on the geometric design of the merging segments. There have been only a few research publications concerned with traffic behavior and characteristics in these situations. Therefore, a three‐year extensive study has been undertaken to investigate traffic behavior and characteristics during the merging process under congested situations in order to design safer and less congested merging points as well as to apply more efficient control at these bottleneck sections. Two groups of strategies were investigated in this study. The First group was related to the traffic characteristics, and the second group to the geometric characteristics. In the first group, the control strategies related to closure of freeway and ramp lanes as well as lane‐changing maneuver restriction were investigated through a simulation program, detector data, and field experiment. In the second group, the angle of convergence of the ramp with the freeway in relation to merging capacity was analyzed using a simulation program. Results suggested the potential benefits of using proposed strategies developed in this work and can serve as initial guidance for the reduction of delay and improvement of safety under congested traffic conditions.     

Freeway ramp control using fuzzy set theory for inexact reasoning

This paper presents a fuzzy controller for freeway ramp metering, which uses rules of the form: IF “freeway condition” THEN “control action.” The controller has been designed to consider varied levels of congestion, a downstream control area, changing occupancy levels, upstream flows, and a distributed detector array in its rule base. Through fuzzy implication, the inference of each rule is used to the degree to which the condition is true. Using a dynamic simulation model of conditions0fj at the San Francisco-Oakland Bay Bridge, the action of the fuzzy controller is compared to the existing “crisp” control scheme, and an idealized controller. Tests under a variety of scenarios with different incident locations and capacity reductions show that the fuzzy controller is able to extract 40 to 100% of the possible savings in passenger-hours. In general, the fuzzy algorithm displays smooth and rapid response to incidents, and significantly reduces the minute-miles of congestion.     

Methods of dropping auxiliary lanes at freeway weaving segments

Auxiliary lanes connecting freeway entrance and exit ramps provide additional space for entering and exiting vehicles to change lanes. The method of dropping auxiliary lanes is critical in the design of freeway auxiliary lanes. This study investigates the performance of different methods of dropping auxiliary lanes. Case studies were conducted at two selected freeway segments with successive entrance or exit ramps in the City of Houston. Traffic simulation analysis results of these two case studies show that additional operational benefits can be achieved by extending an auxiliary lane beyond the freeway weaving segment. The study also found that if the weaving segment is followed by an entrance/exit ramp and this ramp has high traffic volume, it can be less operationally favorable to extend and terminate the auxiliary lane at this entrance/exit ramp location. Instead, dropping the auxiliary lane before this entrance/exit ramp represents a more operationally effective option.     

Coordinated ramp metering for freeway networks – A model-predictive hierarchical control approach

A nonlinear model-predictive hierarchical control approach is presented for coordinated ramp metering of freeway networks. The utilized hierarchical structure consists of three layers: the estimation/prediction layer, the optimization layer and the direct control layer. The previously designed optimal control tool AMOC (Advanced Motorway Optimal Control) is incorporated in the second layer while the local feedback control strategy ALINEA is used in the third layer. Simulation results are presented for the Amsterdam ring-road. The proposed approach outperforms uncoordinated local ramp metering and its efficiency approaches the one obtained by an optimal open-loop solution. It is demonstrated that metering of all on-ramps, including freeway-to-freeway intersections, with sufficient ramp storage space leads to the optimal utilization of the available infrastructure.     

A multi-class model-based control scheme for reducing congestion and emissions in freeway networks by combining ramp metering and route guidance

The paper proposes a multi-class control scheme for freeway traffic networks. This control scheme combines two control strategies, i.e. ramp metering and route guidance, in order to reduce the total time spent and the total emissions in a balanced way. In particular, the ramp metering and route guidance controllers are feedback predictive controllers, i.e. they compute the control actions not only on the basis of the measured system state, but also on the basis of the prediction of the system evolution, in terms of traffic conditions and traffic emissions. Another important feature of the controllers is that they have a multi-class nature: different classes of vehicles are considered and specific control actions are computed for each class. Since the controllers are based on a set of parameters that need to be tuned, the overall control framework also includes a module to properly determine the gains of the controllers. The simulation analysis reported in the paper shows the effectiveness of the proposed control framework and, in particular, the possibility of implementing control policies that are specific for each vehicle type.     

Convexity and robustness of dynamic traffic assignment and freeway network control

We study the use of the System Optimum (SO) Dynamic Traffic Assignment (DTA) problem to design optimal traffic flow controls for freeway networks as modeled by the Cell Transmission Model, using variable speed limit, ramp metering, and routing. We consider two optimal control problems: the DTA problem, where turning ratios are part of the control inputs, and the Freeway Network Control (FNC), where turning ratios are instead assigned exogenous parameters. It is known that relaxation of the supply and demand constraints in the cell-based formulations of the DTA problem results in a linear program. However, solutions to the relaxed problem can be infeasible with respect to traffic dynamics. Previous work has shown that such solutions can be made feasible by proper choice of ramp metering and variable speed limit control for specific traffic networks. We extend this procedure to arbitrary networks and provide insight into the structure and robustness of the proposed optimal controllers. For a network consisting only of ordinary, merge, and diverge junctions, where the cells have linear demand functions and affine supply functions with identical slopes, and the cost is the total traffic volume, we show, using the Pontryagin maximum principle, that variable speed limits are not needed in order to achieve optimality in the FNC problem, and ramp metering is sufficient. We also prove bounds on perturbation of the controlled system trajectory in terms of perturbations in initial traffic volume and exogenous inflows. These bounds, which leverage monotonicity properties of the controlled trajectory, are shown to be in close agreement with numerical simulation results.     

Increasing the capacity of an isolated merge by metering its on-ramp

Measurements taken downstream of freeway/on-ramp merges have previously shown that discharge flow diminishes when a merge becomes an isolated bottleneck. By means of observation and experiment, we show here that metering an on-ramp can recover the higher discharge flow at a merge and thereby increase the merge capacity. Detailed observations were collected at a single merge using video. These data revealed that the reductions in discharge flow are triggered by a queue that forms near the merge in the freeway shoulder lane and then spreads laterally, as drivers change lanes to maneuver around slow traffic. Our experiments show that once restrictive metering mitigated this shoulder lane queue, high outflows often returned to the median lane. High merge outflows could be restored in all freeway lanes by then relaxing the metering rate so that inflows from the on-ramp increased. Although outflows recovered in this fashion were not sustained for periods greater than 13 min, the findings are the first real evidence that ramp metering can favorably affect the capacity of an isolated merge. Furthermore, these findings point to control strategies that might generate higher outflows for more prolonged periods and increase merge capacity even more. Finally, the findings uncover details of merge operation that are essential for developing realistic theories of merging traffic.     

Behavior of the cell transmission model and effectiveness of ramp metering

The paper characterizes the behavior of the cell transmission model of a freeway, divided into N sections or cells, each with one on-ramp and one off-ramp. The state of the dynamical system is the N-dimensional vector n of vehicle densities in the N sections. A feasible stationary demand pattern induces a unique equilibrium flow in each section. However, there is an infinite set—in fact a continuum—of equilibrium states, including a unique uncongested equilibrium n^u in which free flow speed prevails in all sections, and a unique most congested equilibrium n^con. In every other equilibrium n^e one or more sections are congested, and n^u  n^e  n^con. Every equilibrium is stable and every trajectory converges to some equilibrium state.Two implications for ramp metering are explored. First, if the demand exceeds capacity and the ramps are not metered, every trajectory converges to the most congested equilibrium. Moreover, there is a ramp metering strategy that increases discharge flows and reduces total travel time compared with the no-metering strategy. Second, even when the demand is feasible but the freeway is initially congested, there is a ramp metering strategy that moves the system to the uncongested equilibrium and reduces total travel time. The two conclusions show that congestion invariably indicates wastefulness of freeway resources that ramp metering can eliminate.