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Cambridge Centre for Smart Infrastructure and Construction

Transforming infrastructure through smarter information
A GIS-based infrastructure management system to increase resilience of terrestrial transportation networks

Modern society is increasingly dependent on transportation networks. The ability of our transport systems to function during adverse conditions and quickly recover to acceptable levels of service after an extreme event is fundamental to the wellbeing of citizens and strength of the economy.

The SAFEWAY project

The SAFEWAY project, a GIS-Based Infrastructure Management System for Optimised Response to Extreme Events on Terrestrial Transport Networks, aims to address the ability of transport systems to function during adverse conditions and quickly recover to acceptable levels of service after extreme events. SAFEWAY develops a transversal solution mainly focused on terrestrial transport modes, including both roads and railway infrastructure networks. Several of the SAFEWAY modules (mainly monitoring and risk prediction) can also be applied to other transport modes such as maritime. 

The main objective of the project is to design, validate and implement holistic methods, strategies, tools and technical interventions to significantly increase the resilience of inland transport infrastructure by reducing risk vulnerability and strengthening network systems to extreme events. The University of Cambridge is one of 15 partners collaborating on the project, which is being coordinated by the University of Vigo, Spain.

Challenges addressed

SAFEWAY project tools and interventions will be deployed for critical hazards, both natural and man-made, including: wildfires in Portugal; floods, which currently account for half of climate hazards across Europe; land displacements in the UK, Spain, the Netherlands and Portugal; and seismic-related events in the Iberian Peninsula and Italy. Resilience to man-made hazards such as terrorism, vandalism, accidents, and negligence will be secured by mitigating their impacts with real-time mobility advice, such as TomTom real-time traffic management. SAFEWAY also employs innovative socio-technical elements of psychology and risk tolerance for communities at local, regional and European level, for both natural and man-made hazards.
SAFEWAY’s objectives will address and strengthen the four criteria for a resilient infrastructure: robustness, resourcefulness, rapid recovery and redundancy.

Optimum balance

Senior Lecturer in Industrial Systems at the Institute for Manufacturing and CSIC Investigator, Dr Ajith Parlikad, is leading collaborative research to develop predictive models for critical infrastructure assets that consider measured structural performance and trends observed in large databases to estimate the risks of future infrastructure damage, shutdown and deterioration. Projections of second, thirdorder, and long-term consequences will also be assessed. The University of Cambridge team will be involved in the development of a robust decision support framework for terrestrial transportation infrastructure management by considering diverse types of risks related to natural and man-made extreme events and balancing stakeholders’ demands and optimising priorities over asset types. The objective is to identify the optimum balance between long-term risk minimisation and available financial resources to find the optimum resilience.
SAFEWAY is funded by the EU Horizon 2020 ‘Smart, green and integrated transport’ work programme which is aimed at achieving a European transport system that is resilient, resource-efficient, climate-and-environmentally-friendly, safe and seamless for the benefit of all citizens, the economy and society.
"SAFEWAY offers tangible innovation potential for industry. The new knowledge and solutions that arise from SAFEWAY methodologies, innovation and research projects will enhance the work of CSIC that fosters accelerated industrial adoption through collaboration with industry partners." Dr Ajith Kumar Parlikad, Head of Asset Management Group, Institute for Manufacturing, University of Cambridge and CSIC Investigator
CSIC Team: Dr Georgios Hadjidemetriou, Dr Ajith Parlikad
Read more about this project here