An Advanced Real-Time Ramp Metering System (ARMS): The System Concept

Details

• Creators:
  Liu, Jyh-Charn S. ; Kim, Junguk L. ; Chen, Yilong ; Hao, Ying ; Lee, Soojung ; Kim, Taeyoung ; Thomadakis, Michael
• Corporate Creators:
  Texas Transportation Institute. Texas A&M University
• Corporate Contributors:
  Texas Department of Transportation ; United States. Department of Transportation. Federal Highway Administration
• Subject/TRT Terms:
  • Ramp metering
  • Congestion management systems
  • Traffic flow
  • Optimization
  • Simulation
  • Real time control
  • Flow-Breakdown Prediction
• Publication/ Report Number:
  FHWA/TX-94/1232-24
• Resource Type:
  Tech Report
• Geographical Coverage:
  Texas ; United States
• Edition:
  January 1993 - April 1994
• Corporate Publisher:
  Texas Transportation Institute. Texas A&M University
• Abstract:
  This research report presents a three-level, highway ramp-metering control scheme. In the first level, ramp controllers distributively compute ramp metering rates based on system-wide information. The system adapts quickly to changing traffic conditions; it is modular and allows scalable and robust implementation. The 0-D prediction algorithm is adaptive and very accurate. The second level consists of an optimal, self-learning, congestion predictor algorithm that may predict all short-term traffic flow-breakdowns. The algorithm, using self-learning, utilizes sequences of traffic patterns to improve its prediction accuracy. The third level is a congestion resolution scheme which overcomes many of the drawbacks of existing techniques. It balances the congestion resolution time with the service quality of the surface streets. Simulation results show that application of the three-level control algorithm will improve the freeway and surface street service.
• Format:
  PDF
• Funding:
  0-1232
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/82192/dot_82192_DS1.pdf
• File Type:
  [PDF - 2.84 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:28038c81e3ad414264bb4548086ba2467014f4ac12486138437f095073b1816c343a8bd712dfda22589bc786651e97d86df1c6425699d4e3df38e652996bb214