This paper develops two genetic fuzzy logic controller-based ramp metering strategies (GFLC-RM): isolated and integrated. The isolated strategy (GFLC-RMIS) uses mainline traveling speed and on-ramp queue length as state variables, metering rate as control variable. Based on GFLC-RM IS and considering the effects of upstream metering traffic, the integrated strategy (GFLC-RMIT) further incorporates the metering rate of upstream ramp as an additional state variable. For comparison, two conventional ramp metering strategies: pre-timed optimal ramp metering (GOP-RM) strategy and fuzzy logic controller-based ramp metering (FLC-RM) strategy are also proposed. These strategies are validated by both exemplified and field cases. In comparing to the strategy of without metering, a consistent result of these two cases can be found that GFLC-RMIT outperforms, followed by GFLC-RMIS, FLC-RM, and GOP-RM. The performances of proposed GFLC-RM strategies have been proven.