John Hourdakis and Panos G. Michalopoulos
Department of Civil Engineering, University of Minnesota.

NGSIM Meeting of Future Transport Modeling, Tucson, Arizona, September 2001.

INTRODUCTION

As the sophistication of traffic detection and control hardware increases, the need to improve freeway ramp control logic becomes evident, especially in view of increasing ATMS systems deployment. Since each freeway has its own characteristics, selecting the most effective control strategy and calibrating its parameters prior to implementation is problematic. A combination of these factors suggests the need for a systematic methodology for selecting and adapting the most appropriate control scheme for a particular situation. More often than not the ramp control strategies deployed were customized empirically and fine-tuned over a period of time. Even though empirical solutions can be effective, there is no assurance that they are the best for a particular freeway, while they take time to be fine-tuned and their deviation from optimality is unknown. Simulation is an obvious tool to shortcut the process but this rarely occurs in practice. Furthermore, simulators are at best designed to implement only a particular control strategy. Thus a flexible and uniform practical tool for selecting the best control strategy and optimizing it or developing and testing new concepts is currently lacking.

In this paper a computer-aided approach is presented for testing, calibrating and evaluating any ramp control strategy desired for a particular freeway section or system including adjacent arterials (corridors). The methodology employs a versatile, easy to use microscopic simulator, which was selected after evaluating the most widely used ones. The selection criteria included ease of use, versatility, code availability and documentation, performance, and proven effectiveness through extensive employment in real projects. The simulator was enhanced to include an interface that allows integration of any user specified ramp control scheme. Enhancements were also made to automatically collect and feed demand patterns to the simulator. The entire simulation, database, and control logic package can be effectively used to estimate parameters and compare/evaluate ramp control strategies iteratively. New control strategies can also be implemented, tested, and calibrated by the user with relative ease.

As a “test case“ application, the ramp control logic developed by the Minnesota Department of Transportation (MnDOT) was implemented on a 24-km southbound segment of I-35W in Minneapolis and compared with the no-control alternative. In this manner the benefits of this ramp control strategy are quantified and presented. Improvements to the control strategy as well as testing of others are being planned with this methodology.

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