An automatic tuning strategy for local fuzzy logic ramp metering algorithm using Particle Swarm Optimization (PSO)

Freeway systems are becoming more congested each day. One contribution to freeway traffic congestion comprises platoons of on-ramp traffic merging into freeway mainlines. As a relatively low-cost countermeasure to the problem, ramp meters are being deployed in both directions of an 11-mile section of I-95 in Miami-Dade County, Florida. The local Fuzzy Logic (FL) ramp metering algorithm implemented in Seattle, Washington, has been selected for deployment. The FL ramp metering algorithm is powered by the Fuzzy Logic Controller (FLC). The FLC depends on a series of parameters that can significantly alter the behavior of the controller, thus affecting the performance of ramp meters. However, the most suitable values for these parameters are often difficult to determine, as they vary with current traffic conditions. Thus, for optimum performance, the parameter values must be fine-tuned. This research presents a new method of fine tuning the FLC parameters using Particle Swarm Optimization (PSO). PSO attempts to optimize several important parameters of the FLC. The objective function of the optimization model incorporates the METANET macroscopic traffic flow model to minimize delay time, subject to the constraints of reasonable ranges of ramp metering rates and FLC parameters. To further improve the performance, a short-term traffic forecasting module using a discrete Kalman filter was incorporated to predict the downstream freeway mainline occupancy. This helps to detect the presence of downstream bottlenecks. The CORSIM microscopic simulation model was selected as the platform to evaluate the performance of the proposed PSO tuning strategy. The ramp-metering algorithm incorporating the tuning strategy was implemented using CORSIM's run-time extension (RTE) and was tested on the aforementioned I-95 corridor. The performance of the FLC with PSO tuning was compared with the performance of the existing FLC without PSO tuning. The results show that the FLC with PSO tuning outperforms the existing FL metering, fixed-time metering, and existing conditions without metering in terms of total travel time savings, average speed, and system-wide throughput.

Mechanism of Superoxide Mediated Regulation of Particle Uptake and Exocytosis by a GPI-anchored Superoxide Dismutase C in Dictyostelium

Dictyostelium discoideum is a simple model organism that can be used to study endocytic pathways such as phagocytosis and macropinocytosis because of its homology to cells of the mammalian innate immune system, namely macrophages and neutrophils. Consequently, Dictyostelium can also be used to study the process of exocytosis. In our laboratory, we generated Dictyostelium cells lacking superoxide dismutase SodC. Our data suggest that cells that lack SodC are defective in macropinocytosis and exocytosis when compared to wild type cells. In this study I describe a regulatory mechanism of macropinocytosis by SodC via regulation of RasG, which in turn controls PI3K activation and thus macropinocytosis. Our results show that proper metabolism of superoxide is critical for efficient particle uptake, for the proper trafficking of internalized particles, and a timely exocytosis of fluid uptake in Dictyostelium cells.