On optimal freeway local ramp metering using fuzzy logic control with particle swarm optimisation

Abstract

In this study, the problem of optimal freeway local ramp metering is address by using fuzzy logic control (FLC)-based ramp metering. The objective of optimal freeway local ramp metering is to minimise a weighted total-time spent-(WTTS)-based cost function, which measures the performance of freeway local ramp metering in terms of the WTTS by vehicles on both the freeway mainstream and on-ramp link. A simple and efficient local ramp metering algorithm based on Takagi-Sugeno type FLC algorithm is proposed. The input membership functions of the FLC controller are predefined, and human expert knowledge on freeway traffic flow behaviours is utilised to reduce the size of fuzzy rule base. The consequent parameters are fine-tuned by particle swarm optimisation and microscopic traffic simulations. Simulation studies with PARAMICS traffic simulation platform show the potential of the proposed approach in obtaining the optimal freeway local ramp metering strategies to strike a balance between traffic conditions on the mainstream and the on-ramp link.