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Coordinated Feedback-Based Freeway Ramp Metering Control Strategies “C-MIXCROS and D-MIXCROS” that Take Ramp Queues into Account

Part of the Complex Networks and Dynamic Systems book series (CNDS,volume 2)

Abstract

In this paper, C-MIXCROS and D-MIXCROS, two feedback-based coordinated ramp metering strategies that explicitly consider ramp queues, are proposed. They are evaluated using both macroscopic (Rutgers Macroscopic Simulation Environment) and microscopic (PARAMICS) simulation models (on an 11-mile-long corridor of I-295 in South Jersey) under different demand conditions. In addition to the newly proposed coordinated ramp metering strategies, a well-known coordinated strategy (METALINE [Papageorgiou et al. Transport Res. 1990;24A:361–370]) and three other local strategies (ALINEA [Papageorgiou et al. Transportation research record, No. 1320, Washington, D.C.: TRB, National Research Council; 1991. p. 58–64], New Control [Kachroo and Ozbay. Feedback ramp metering in intelligent transportation systems. New York: Kluwer Academics; 2003], and MIXCROS [Kachroo and Ozbay. Feedback ramp metering in intelligent transportation systems. New York: Kluwer Academics; 2003) are also implemented using the same network and results are compared. The proportional-derivative state feedback control logic and direct regulation of on-ramp queues are employed in the derivation of this new proposed coordinated ramp metering strategy. The simulation results are consistent with the macroscopic simulation results, where D-MIXCROS and C-MIXCROS both perform more competently than all other control strategies tested for every demand scenario. The deteriorating effect of enormous on-ramp queues on the total travel time is observed especially in METALINE results; the total travel time for METALINE is approximately 22% greater compared with C-MIXCROS. MIXCROS also successfully maintains the on-ramp queues at a reasonable level for each ramp. However, because it is a local ramp metering strategy, coordinated versions of MIXCROS are observed to be more beneficial both for the ramp system and at the network level.

Keywords

  • Queue Length
  • Traffic Density
  • Total Travel Time
  • Demand Scenario
  • Freeway Section

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Correspondence to Kaan Ozbay .

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Gokasar, I., Ozbay, K., Kachroo, P. (2013). Coordinated Feedback-Based Freeway Ramp Metering Control Strategies “C-MIXCROS and D-MIXCROS” that Take Ramp Queues into Account. In: Ukkusuri, S., Ozbay, K. (eds) Advances in Dynamic Network Modeling in Complex Transportation Systems. Complex Networks and Dynamic Systems, vol 2. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6243-9_3

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