Ramp metering or ramp control has been developed as a traffic management strategy, to alleviate congestion on freeways. It aims to enhance freeway throughout, improve travel time reliability, and safety. Ramp metering is an effective method of freeway traffic control, which limits the number of vehicles entering the freeway with the help of a pulsing meter at on-ramp. Its philosophy is to maintain optimal freeway operation by regulating on-ramp demand to be at or under its capacity. Various methods have been proposed to calculate the metering rate that determines the number of vehicles allowed to enter the freeway from on-ramps. On basis of the operational mode, these strategies can be categorized as fixed-time or traffic-responsive. On the basis of the operational level, these strategies can be categorized as local or area-wide ramp metering. The aim of this study is to assess the effects of ramp metering on performance conditions of traffic flow at three levels: network (highway and ramps), on-ramp and highway section at upstream of on-ramp. The Shahid Kharrazi Highway in Isfahan is used in this study. In this study, the north to south bound from Jomhoori Square to Vahid Bridge is selected for development and evaluation of ramp metering. Ramp controls were developed and evaluated using Microscopic Traffic Simulation, AIMSUN NG. Microscopic traffic simulation is applied in this study as it provides a cost-effective and reliable means to evaluate performance of ramp metering strategies. Data collected from filed surveying were used for the development of the Shahid Kharrazi Highway model. After calibrating and validating of model is done, Samadyeh on-ramp is selected for implementation of ramp metering strategies. This on-ramp was controlled with fixed-time plan and ALINEA algorithm. ALINEA ramp metering algorithm is a traffic-responsive local ramp metering that uses feedback regulation to maintain target occupancy of the freeway mainline. For each ramp control, it uses one downstream mainline detector to measure the occupancy. For this purpose, first key parameters for the implementation of ALINEA including regulator parameter, target occupancy and location of downstream detectors were determined and calibrated to ensure the highest performance of the algorithm under the actual environment. Experiments show that the algorithm is best performed when the regulator parameter, target occupancy and location of downstream detectors, respectively was set at 70 veh/h, 20% and 90 m from on-ramp nose. The result from this study indicated that ramp metering significantly improved mainline traffic conditions for high demand levels (110% demand), indicating the usefulness of ramp metering only at high demands. At low demand (80% demand) ramp metering increased the mainline delay time, indicating the ineffectiveness of ramp metering at low demands. In addition, finding from this study indicated that the new highway (especially those on-ramps) should be designed so that those can be managed. Key words: ramp metering, ALINEA algorithm