Responding to an impending demand growth at an existing reactive managed lane system, and in order to provide a timely and more effective temporary hard shoulder activation, short-term prediction models are developed. A lane-oriented attribute, namely the left lane flow distribution ratio (LLFDR), is introduced, aiming to ameliorate the system by capturing the forthcoming stream dynamics and reconfiguring it to proactive. To assess the impact of its implementation to the network's performance, an exploratory analysis was effectuated based on data acquired by seven radar sensors located every 500 m, along a Swiss freeway section that is not affected from incoming or exiting traffic. A locally weighted regression is employed to provide a more accurate insight of the traffic behaviour, comparing observations derived during the regular operation of the system and a period that it was suspended, with respect to seasonality patterns. To describe the impending stream motion by examining different time-volume clusters (off-peak and rush-hour), two prediction models were specified according to the time range. The preliminary results of the study for several prediction horizons, demonstrate an acceptable prediction uncertainty. The hard shoulder activation prediction confirms the analysis of the operation impact findings of this research.