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.
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References
Bogenberger K, May AD. Advanced coordinated traffic responsive ramp metering strategies. In: California PATH Working Paper, UCB-ITS-PWP-99–19, 1999.
Bhouri N, Haj-Salem H, Kauppila J. Isolated versus coordinated ramp metering: Field evaluation results of travel time reliability and traffic impact. Transport Res C 2011. Elsevier (Available On-Line, 2011). doi:10.1016/j.trc.2011.11.001.
Chu L, Liu HX, Recker W, Zhang HM. Development of a simulation laboratory for evaluating ramp metering algorithms. In: UCI-ITS-WP-01–23, 2001.
Hasan M, Jha M, Ben-Akiva M. Evaluation Of ramp control algorithms using microscopic traffic simulation. Transport Res C 2002;10(3):229–256.
Hou Z.S., Xu J.X., Yan J.W, An iterative learning approach for density control of freeway traffic flow via ramp metering, Transportation Research Part C, (16) 71–97, 2008.
Kachroo P, Ozbay K. Feedback ramp metering in intelligent transportation systems. New York: Kluwer Academic/Plenum Publishers; 2003.
Kotsialos A, Kosmatopoulos E, Papageorgiou M. Current status of ramp metering. In: European Ramp Metering Project, IST-2002–23110, 2004.
Jacobsen L, Henry K, Mahyar O. Real-time metering algorithm for centralized control. Transport Res Rec TRB 1989;1232. pp. 17–26.
Lipp L., Corcoran L., and Hickman G, Benefits of central computer control for the Denver ramp metering system, Transportation Research Board Record 1320, January 1991.
Liu J.C., Kim J., Chen Y., Hao Y., Lee S., Kim T. and Thomadakis M., An advanced real time metering system (ARMS): the system concept, Texas Department of Transportation Report Number 1232–24, 1993.
Masher DP, Ross DW, Wong PJ, Tuan PL, Zeidler S, Peracek S. Guidelines for design and operating of ramp control systems. In: Stanford Research Institute Report NCHRP 3–22, SRI Project 3340, Menid Park, CA: SRI; 1975.
May, A. D., Traffic Flow Fundamentals, Prentice-Hall, 1990.
Meldrum D. and Taylor, C. Freeway traffic data prediction using artificial neural networks and development of a Fuzzy Logic Ramp Metering Algorithm, Final Technical Report, Washington State Department of Transportation Report No. WA-RD 365.1, Washington, 1995.
Ozbay K, Yasar I, Kachroo P. Comprehensive evaluation of feedback based freeway ramp metering strategy by using microscopic simulation: taking ramp queues into account. In: Transportation Research Record, No. 1867, TRB. Washington, D.C.: National Research Council; 2004. pp. 89–96.
Papageorgiou M. Modelling and real-time control of traffic flow on the southern part of Boulevard Peripherique in Paris. Internal report. INRETS-DART, Arcueil, France, 1988.
Papageorgiou M, Blossville J-M, Hadj-Salem H. Modelling and real-time control of traffic flow on the southern part of Boulevard Peripherique in Paris, Part II: Coordinated on-ramp metering. Transport Res 1990;24A:361–370.
Papageorgiou M, Habib HS, Blosseville J-M. ALINEA: A local feedback control law for on-ramp metering. In: Transportation Research Record, No. 1320, TRB. Washington, D.C.: National Research Council; 1991. pp. 58–64.
Papageorgiou M and Kotsialos A. Freeway Ramp metering: An overview. IEEE Transactions on Intelligent Transportation Systems 2002;3(4): 271–281.
Paesani G., Kerr J., Perovich P. and Khosravi E., System wide adaptive ramp metering in southern California, ITS America 7th Annual Meeting, June 1997.
Stephanedes Y, Implementation of on-line Zone Control Strategies for optimal ramp metering in the Minneapolis Ring Road, 7th International Conference on Road Traffic Monitoring and Control, 1994.
Wei C.H. and Wu K.Y., Applying an artificial neural network model to freeway ramp metering control, Transportation Planning Journal, Vol. 25 No. 3, 1996.
Yasar, I. Modeling and PARAMICS based evaluation of new local freeway ramp metering strategy that takes into account ramp queues, M.S. Thesis, Rutgers University 2003.
Yin Y, Liu H, Benouar H. A note on equity of ramp metering. In: IEEE intelligent transportation systems conference, Washington, D.C., USA, October 3–6, 2004.
Yoshino T., Sasaki T and Hasegawa T, The traffic control system on the Hanshin Expressway, Interfaces Magazine, Jan./Feb. 1995.
Zhang HM, Recker WW. On optimal freeway ramp control policies for congested traffic corridors. Transport Res B Methodological 1999;33(6):417–436.
Zhang M, Kim T, Nie X, Jin W, Chu L, Recker W. Evaluation of on-ramp control algorithms. In: California PATH Research Report, UCB-ITS-PRR-2001–36, December 2001.
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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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