GIS-based infrastructure management system for optimized response to extreme events on terrestrial transport networks.

SAFEWAY leads to significantly improved resilience of transport infrastructures, developing a holistic toolset with transversal application to anticipate and mitigate the effects extreme events at all modes of disaster cycle.

According to European TEN-T guidelines, due consideration must be given to the risk assessments and adaptation measures during infrastructure planning, in order to improve resilience to disasters. SAFEWAY's main aim is to design, validate and implement holistic methods, strategies, tools and technical interventions to significantly increase the resilience of inland transport infrastructure. SAFEWAY leads to significantly improved resilience of transport infrastructures by developing a holistic toolset with transversal application to anticipate and mitigate the effects extreme events at all modes of disaster cycle:

• "Preparation": the pillar of the SAFEWAY approach is settled in a substantial improvement of prediction, monitoring and decision tools that will contribute to the anticipation, prevention and preparation of critical European transport infrastructures for the damaging impacts of extreme events,
• "Response and Recovery": the incorporation of SAFEWAY Big Data and Smart ICT into emergency plans, as well as the real-time optimised communication with operators and end users (via crowdsourcing and social media) will contribute to the recovery on a short-term scale; the solutions adopted in the pre- and peri-event have a direct and crucial effect in recovery on a long-term scale.
• "Mitigation": improving precision in the adoption of mitigation actions by impact analysis of the different scenarios together with new construction systems and smart materials that will contribute to the resistance & absorption of the damage impact.

Within these dimensions, SAFEWAY will:

• implement novel technologies that provide a new multiscale monitoring approach by combining existing remote-sensing technologies to anticipate the impact of extreme events;
• use crowdsourcing and exploit social media infrastructure to monitor human response during and immediately after a natural or man-made extreme event;
• develop the framework for decision-making considering the above-mentioned factors for both single mode transportation (road and railway) as well as in a multimodal context; this framework will balance stakeholder's demands and optimise priorities (short-term and long-term) in assets' treatment, on the basis of predictive models that account for climate change projections, and prognosis regarding population, structural and traffic conditions;
• integrate this multidisciplinary approach through a modular cloud-based ICT platform that provides optimal interfacing among the different components of SAFEWAY's resilience solution. SAFEWAY cloud-based ICT Platform is designed to fully support robust decision-making for Infrastructure Management by integrating:
• metrics of infrastructural physical condition and its environment that may anticipate the infrastructure response before the occurrence of external hazards;
• effective and dynamic predictive models that consider several actions and their impacts;
• Life Cycle Assessment (LCA) based on mitigation measures and dynamic traffic restoration solutions; and
• measures ensuring the safety of users addressing physical, psychological and behavioural dimensions.

​Partners of the project are: University of Vigo (Spain - Coordinator), Norwegian Geotechnical Institute, The University of Cambridge (UK), Insitu Engineering (Spain), DEMO Consultants (The Netherlands), University of Minho (Portugal), Planetek Italia (Italy), Infrastructure Management Consultants (Switzerland), Ferrovial Agroman (Spain), Infraestruturas de Portugal, Network Rail (UK), BeTR (The Netherlands), Innovactory (The Netherlands), TØI (Norway), Texas A&M Transportation Institute (Texas, USA).

Planetek is involved in the design of the multi-scale infrastructure monitoring techniques, obtained by merging geospatial data of different nature (e.g. satellite and terrestrial mobile mapping systems). Various technologies are applied, like big data (to optimally handle the huge amount of information), deep learning and machine learning techniques (to automatically feed the information models of the infrastructure).

Planetek is also involved in the Demonstration Case 3, corresponding to the North Sea – Mediterranean corridor, that will be carried-out in the London-Manchester rail network including 337 km railway, 1.235 bridges, 13 tunnels, 846 retaining walls and 28 stations. The end user of the use case is Network Rail Infrastructure Ltd., the owner and operator of most of the rail infrastructure in Great Britain (England, Scotland and Wales).

This research project has received funding from the European Union's Innovation and Networks Executive Agency (INEA), within the H2020-MG7.1-2017 call, under Grant Agreement nº 769255.

Further information on www.safeway-project.eu