Speed-flow relationships have been established for different free-flow speeds on urban freeways. However, there have been few research efforts relating real-time traffic flow parameters and weather conditions for different levels of heavy vehicle traffic. This study aims at establishing relationships between speed and volume in freeway sections using Remote Traffic Microwave Sensor (RTMS) data as a function of weather conditions. Historical weather and RTMS detector data (i.e., volume and

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... from two highway corridors in the Istanbul metropolitan area are used for this purpose. Empirical relationships between traffic speed and volume are analyzed by weather condition (clear, rain, fog/mist/haze, or snow), surface condition (dry, wet, or icy), and percentage of heavy vehicles in the traffic mix. The findings from the analysis show that rain reduced the average vehicular speeds by 8 to 12% and the capacity by 7-8%. Moreover, wet surface conditions resulted in a reduction of average speeds by 6 to 7% and light snow affected demand leading to a significant reduction in traffic volume.