The condition of the land transport infrastructure has a big societal and economic relevance, since constraints result in disruptions of service. The demand for surface transport will significantly increase in the next years. Given budget restrictions, a substantial enlargement of the road/rail network in the next decades is doubtful. Besides, the aging infrastructure will require more maintenance interventions which infer normal traffic operation. Therefore, the only way to increase infrastructure capacity for the increased transportation demand is to optimise the performance of the existing infrastructure. This is precisely the goal tackled by INFRALERT.

INFRALERT aims to develop an expert-based information system to support and automate infrastructure management from measurement to maintenance. This includes the collection, storage and analysis of inspection data, the determination of maintenance tasks necessary to keep the performance of the infrastructure system in optimal condition, and the optimal planning of interventions.
The major challenges of INFRALERT are:

  • Developing the information technologies and standard procedures applicable to linear transport systems in general.
  • Developing expert-based toolkits built on artificial intelligence and optimization techniques to support decision making in maintenance planning, renewal and new construction.
  • Integrating all previous models and tools in a cloud-based framework compatible with existing asset management systems.

The main outcomes of INFRALERT will be:

a) Ensuring service reliability and safety by minimising incidences and failures of decaying assets
b) Keeping and increasing the availability by optimising operational maintenance interventions and strategic long-term decisions on new construction
c) Ensuring the operability under traffic disruptions due to interventions.

The INFRALERT developments will be demonstrated in two real-world pilots chosen for their potential for replication: a railway network in Sweden and a road network in Portugal. In both cases, extensive data from auscultation campaigns are available since some years ago. The empirical development of the whole project will be based on these pilot cases.
In addition to technical development and demonstration, INFRALERT will ensure the widest impact possible through an ambitious dissemination and exploitation strategy. This includes workshops, newsletters, a website and clustering with related projects. The project team will be supported by an External Advisory Boards, composed by experts from the infrastructure community.