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Evaluation of On-ramp Control Algorithms

Author

Listed:
  • Zhang, Michael
  • Kim, Taewan
  • Nie, Xiaojian
  • Jin, Wenlong
  • Chu, Lianyu
  • Recker, Will

Abstract

The control of a traffic corridor, which consists of two major component - freeway system control and arterial street system control, aims to improve flows on both freeway and arterial streets, and has been demonstrated as an effective means to increase the level of service of a corridor system during peak periods. Ramp metering, or ramp control, has been considered to be a very important component of corridor traffic control. Ramp metering is the application of control devices such as metering signals to limit the number of vehicles entering a freeway. The fundamental philosophy of ramp metering is that the corridor can maintain its optimal operation by regulating the freeway demand to be under its capacity. Maintaining the optimal operation of the corridor would provide congestion avoidance and accordingly travel time savings.

Suggested Citation

  • Zhang, Michael & Kim, Taewan & Nie, Xiaojian & Jin, Wenlong & Chu, Lianyu & Recker, Will, 2001. "Evaluation of On-ramp Control Algorithms," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt83n4g2rq, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt83n4g2rq
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    Cited by:

    1. Nima Dadashzadeh & Murat Ergun, 2019. "An Integrated Variable Speed Limit and ALINEA Ramp Metering Model in the Presence of High Bus Volume," Sustainability, MDPI, vol. 11(22), pages 1-26, November.
    2. Toan, Trinh Dinh & Wong, Yiik Diew & Lam, Soi Hoi & Meng, Meng, 2022. "Developing a fuzzy-based decision-making procedure for traffic control in expressway congestion management," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    3. Jacob, Celine & Abdulhai, Baher, 2010. "Machine learning for multi-jurisdictional optimal traffic corridor control," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(2), pages 53-64, February.
    4. Kerner, Boris S., 2005. "Control of spatiotemporal congested traffic patterns at highway bottlenecks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(2), pages 565-601.
    5. Zhang, Michael & Ma, Jingtao, 2008. "Developing Calibration Tools for Microscopic Traffic Simulation Final Report Part 1: Overview Methods and Guidelines on Project Scoping and Data Collection," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3hh8f7nz, Institute of Transportation Studies, UC Berkeley.

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    Keywords

    Engineering;

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