ProZEnt - Multicriteria probabilistic prediction of pavement condition / Final report published

Worldwide, deterministic methods are predominantly used for forecasting the pavement condition. The methods are comparatively easy to apply and provide solid results. From the users' point of view, however, there are also critical voices and the desire to update the condition more realistically on the basis of several condition measurements or for previously defined clusters.

In the "ProZEnt" project, a new practice-oriented method for probabilistic state prediction was developed together with the TU Darmstadt and Infrastructure Management Consultants GmbH (IMC). The new method represents an important building block on the way to risk-based maintenance management and takes into account the measurement results of several past condition campaigns.

After an extensive research of the methods currently used in different disciplines, a suitable probabilistic evaluation method was selected. The methodology was implemented prototypically and applied exemplarily to the data basis provided by the countries Germany, Austria and Switzerland.

The prognosis model makes it possible to forecast the condition of selected surface features, taking into account the uncertainties contained in the input variables. In doing so, it is possible to make statements about the object level as well as the network level.

Project promoter
Österreichische Forschungsförderungsgesellschaft (FFG) 

Time
October 2018 - May 2021

Research Consortium
Technische Universität Darmstadt - Institut für Straßenwesen
Heller Ingenieurgesellschaft mbH
Infrastructure Management Consultants (IMC) GmbH (Schweiz)

Schlussbericht