Globally optimal solutions to the on-ramp metering problem - Part 1

Gomes, Guilherme Ferreira; Horowitz, Roberto

doi:10.1109/itsc.2004.1398952

Cited by 7 publications

(5 citation statements)

References 16 publications

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“…Most of the gradient optimization methods lead to openloop solutions [2], [3], [4]. The Model Predictive Control procedure to coordinate both variable speed limits and ramp metering was presented in [5].…”

Section: Introductionmentioning

confidence: 99%

Analysis and design of equilibrium points for the Cell-Transmission Traffic Model

Pisarski

Canudas‐de‐Wit

2012

2012 American Control Conference (ACC)

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Section: Introductionmentioning

confidence: 99%

Analysis and design of equilibrium points for the Cell-Transmission Traffic Model

Pisarski

Canudas‐de‐Wit

2012

2012 American Control Conference (ACC)

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“…The 14-mile (23 km) I-210W test segment was divided into 41 cells, adapted from a 40-cell partition that was designed by Gabriel Gomes for use in the optimization work of (18,19) A CTM simulator was developed in C. Its main inputs include the freeway geometry, model parameters, initial condition, time-series demand profiles at each entrance, and the simulation time step (default is 10 seconds for the 41-cell partition) (8). Most of the traffic data used in the model calibration was obtained from the Performance Measurement System (PeMS) (20), developed by researchers at U.C.…”

Section: Freeway Representation and Traffic Datamentioning

confidence: 99%

Piecewise-Linearized Cell Transmission Model and Parameter Calibration Methodology

Muñoz

Sun

Horowitz

et al. 2006

Transportation Research Record

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This paper concerns the development of macroscopic freeway traffic models and parameter calibration methodologies that are computationally efficient and suitable for use in real-time traffic monitoring and control applications. Toward the fulfillment of these objectives, a macroscopic traffic model, the Switching-Mode Model (SMM), is presented, which is a piecewise linearized version of Daganzo's Cell Transmission Model (CTM). The observability and controllability properties of the SMM modes are reviewed, since these properties are of fundamental importance in the design of traffic estimators and on-ramp metering controllers. A semi-automated method has been developed for calibrating the CTM and SMM parameters. In this method, a least-squares data fitting approach is applied to loop detector data to determine free-flow speeds, congestion-wave speeds, and jam densities for specified subsections of a freeway. Bottleneck capacities are estimated from measured mainline and onramp flows. The calibration method was tested using loop detector data from an approximately 14-mile (23 km) section of Interstate 210 West (I-210W) in southern California. Traffic data sources were the Performance Measurement System (PeMS), and a set of manually-counted ramp volumes provided by Caltrans District 7. Parameters were first calibrated for a short (2 mi (3 km)) subsection of I-210W and tested on both the SMM and CTM, which were shown to perform similarly to one another. The calibration method was then extended to the full 14-mi section, and the parameters were tested with the CTM. The CTM was able to reproduce observed bottleneck locations and the general behavior of traffic congestion, yielding approximately 2% average error in predicted total travel time.

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“…For example, the desired mainline density profiles and the desired queue lengths need to be defined. Gomes and Horowitz (18,19) have formulated a linear program that minimizes the so-called generalized total travel time with explicit queue length constraints. This linear program is based on a modified version of the cell transmission model and produces a set of mainline densities, time-of-day ramp-metering rates and queue lengths as the solution, using the predicted traffic demands.…”

Section: A Localized Ramp-metering Strategymentioning

confidence: 99%

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

Sun

Horowitz

2006

Transportation Research Record: Journal of the Transportation R

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In this paper, we present a novel switching traffic-responsive ramp-metering controller that adapts to the different traffic dynamics under different congestion conditions-free-flow or congested. The approach of multirate linear quadratic control with integral action (LQI) is employed 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 currently used ad hoc "queue-override" scheme. Subsequently, a queue length estimator is designed to provide feedback to the queue length regulator, using 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, 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%, while the Total Travel Time is improved by 5.6%. As a comparison, simulation results of ALINEA are also presented.

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Globally optimal solutions to the on-ramp metering problem - Part 1

Cited by 7 publications

References 16 publications

Analysis and design of equilibrium points for the Cell-Transmission Traffic Model

Analysis and design of equilibrium points for the Cell-Transmission Traffic Model

Piecewise-Linearized Cell Transmission Model and Parameter Calibration Methodology

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

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