In response to an impending demand growth at an existing reactive managed lane system and to provide a timely and more effective temporary hard shoulder activation, this paper presents the development of short-term prediction models. A lane-oriented attribute—namely, the left-lane flow distribution ratio—is introduced to ameliorate the system by capturing the forthcoming stream dynamics and reconfiguring it to be proactive. To assess the impact on the network's performance of implementing a system for hard shoulder running, an exploratory analysis was performed on the basis of data acquired by seven radar sensors located every 500 m along a Swiss freeway section that was not affected by incoming or exiting traffic. A locally weighted regression was employed to provide more accurate insight into traffic behavior by comparing observations derived during the regular operation of the system and a period in which it was suspended, with respect to seasonality patterns. To describe the impending stream motion by examining different time–volume clusters (off-peak and peak hours), 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 findings of this research with regard to the impact on operations.