Dynamic multi-ramp metering control with simultaneous perturbation stochastic approximation (SPSA)

Ramp metering was proven to be a viable form of freeway traffic control strategy, which could eliminate, or at least reduce, freeway congestion. In this study, the development of ramp metering control strategies, models, and constraints (e.g., meter locations, ramp storage capacities, lower and upper bounds of ramp metering rates) are discussed in detail. The pre-timed and demand/capacity metering control strategies were first evaluated, while the potential metered ramps were determined. A Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm is proposed to dynamically optimize multiple-ramp metering control by maximizing the total throughput subject to a number of constraints. The ramp metering rates subject to dynamic traffic conditions and capacity constraints are considered as decision variables in the SPSA algorithm. Based on the collected geometric and traffic data, a CORSIM model was developed to simulate traffic operation for the study site. The potential benefit of the dynamic multi-ramp metering control model under time varying traffic condition was simulated and evaluated. The increased total throughput and reduced total delay were observed, while the traffic conditions suitable for implementing ramp metering control were suggested. The developed dynamic multi-ramp metering control with SPSA algorithm has demonstrated its effectiveness to improve freeway operation.

Name thesis:degree_name

Doctor of Philosophy in Transportation - (Ph.D.)

Discipline thesis:degree_discipline

Executive Committee for the Interdisciplinary Program in Transportation

Year

2003

Author dc:creator

• Luo, Jiangtao

Contributors dc:contributor

• I-Jy Steven Chien
• Athanassios K. Bladikas
• Lazar Spasovic

• ramp metering
• freeway
• dynamic optimization
• traffic control
• Transportation Engineering

Repository record dc:identifier

https://digitalcommons.njit.edu/dissertations/582

OAI identifier oai:identifier

oai:digitalcommons.njit.edu:dissertations-1637