The quality and reliability of road infrastructure and its equipment play a major role in road safety. This is especially true if we are interested in autonomous vehicle traffic. Markings line are detected by camera. This option needs an accurate maintenance strategy. In that way, their retroreflection luminance is measured for evaluating their degradation. A line is replaced according to the yearly inspection. The consensus strategy is to define a degradation models of markings based on a regression method. Such models provide a prediction of failure occurrences and a preventive replacement is engaged before this instant. This paper proposes alternatively a systematic age-based replacement by strategic areas. In previous study, an Agglomerative Hierarchical Clustering identifies markings with the same degradation model. The feedback database is strongly censored because the exact failure time isn't observed. To deal with this drawback, an WEM Algoritm was proposed to determine a Weibull model. For each strategic area, a cost function can therefore be defined according to both maintenance costs and the associated Weibull model. The optimum replacement period was finally defined as the minimum point of the cost function. The French National Road 4 (NR4) brocken centerline illustrates this approach. Segmented into five clusters, each one admits its own optimum replacement step. The proposed replacement strategy is generic its application is not limited to our case study.