In this study, novel techniques are presented addressing the challenges of stereo matching algorithms for surveillance and vehicle control. For this purpose, one of the most efficient local stereo matching techniques, namely permeability filter, is modified in terms of road plane geometry and temporal consistency in order to take the major challenges of such a scenario into account. Relaxing smoothness assumption of the permeability filter along vertical axis enables extraction of road geometry with high accuracy, even for the cases where ground plane does not contain sufficient textural information. On the other hand, temporal smoothness is enforced by transferring reliable depth assignments against illumination changes, reflections and instant occlusions. According to the extensive experiments on a recent challenging stereo video dataset, the proposed modifications provide reliable disparity maps under severe challenges and low texture distribution, improving scene analyses for surveillance related applications. Although improvements are illustrated for a specific local stereo matching algorithm, the presented specifications and modifications can be applied for the other similar stereo algorithms as well.