Periodic Reporting for period 3 - SAFEWAY (GIS-BASED INFRASTRUCTURE MANAGEMENT SYSTEM FOR OPTIMIZED RESPONSE TO EXTREME EVENTS OF TERRESTRIAL TRANSPORT NETWORKS)
Okres sprawozdawczy: 2021-03-01 do 2022-02-28
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 by reducing risk vulnerability and strengthening network systems to extreme events.
The key to achieve this aim is SAFEWAY ICT Platform capable of handling the three dimensions of the disaster management cycle: i) substantial improvement of prediction, monitoring and decision tools that will contribute to the anticipation, prevention and preparation of critical European infrastructures; ii) the incorporation of SAFEWAY Big Data and Smart ICT into emergency plans, as well as the real-time optimized communication with operators and end users (via crowdsourcing and social media); iii) adoption of mitigation actions by impact analysis of the different scenarios together with new construction systems and smart materials.
As main conclusions, SAFEWAY has contributed with new methods and innovative ICT tools and services that are integrated into a management platform which has been validated in 4 European operational environments. These validations show a potential improvement of resilience of transport infrastructure in terms of reduction of maintenance costs along assets life cycle of at least 20% and improvement in mobility of at least 20%.
The key to achieve this aim is SAFEWAY ICT Platform capable of handling the three dimensions of the disaster management cycle: i) substantial improvement of prediction, monitoring and decision tools that will contribute to the anticipation, prevention and preparation of critical European infrastructures; ii) the incorporation of SAFEWAY Big Data and Smart ICT into emergency plans, as well as the real-time optimized communication with operators and end users (via crowdsourcing and social media); iii) adoption of mitigation actions by impact analysis of the different scenarios together with new construction systems and smart materials.
As main conclusions, SAFEWAY has contributed with new methods and innovative ICT tools and services that are integrated into a management platform which has been validated in 4 European operational environments. These validations show a potential improvement of resilience of transport infrastructure in terms of reduction of maintenance costs along assets life cycle of at least 20% and improvement in mobility of at least 20%.
During the implementation of the SAFEWAY project several solutions contributing to improve the resilience of transport infrastructure to extreme events were developed.
WP 2 has identified risk factors affecting hazard and vulnerability and provided an integration of hazard inventories, databases and maps as well as tools for quantification of their impacts. Critical hazards (natural and human-made) and plausible failure modes have been identified. Guidance for assessment of the probability and severity of service disruption, by using structural and functional vulnerability functions, has also been provided.
In WP3, an analysis of remote sensing technologies that contribute to more efficient monitoring of critical assets. These include satellite technologies and terrestrial technologies to obtain geometrical and radiometric data from the studied environments with high accuracy. After having a clear vision of which specific technologies can contribute to the monitoring requirements of operators' owners, several monitoring scenarios have been defined and clear data acquisition protocols have been proposed.
Crowdsourcing methods for gathering data regarding vehicle parameters were developed in WP4. Interface definition was formulated on extracting floating car data for area wide road network monitoring. Also, a web service was designed for designating restriction zones by the traffic management operator in order to influence planned car routes so that such areas are avoided.
The development of performance predictive models for critical infrastructure assets was conducted in WP5. Deterministic models were used for predicting the deterioration of infrastructure components. Stochastic models were also used for predicting the future condition, and to overcome the lack of inspection records. Additionally, work was developed for the infrastructure risk-based models, consisting of the production of hotspot-maps for wildfires and floods situation and consideration of fragility curves for different assets. Impact assessment at regional scale, i.e. assessment of probability of failure modes leading to reduced mobility was also conducted considering a mesoscopic traffic model.
WP6 concentrated on developing of a robust, resilience-based decision support framework for terrestrial transportation. The first task was to establish a general value system regarding network resilience, based on monetized direct and indirect consequences of inadequate asset performance due to hazards and/or man-made events. The current asset management practice for quality assessment of road/rail infrastructure and the state-of-the-art research on the Key Performance indicators (KPIs) were investigated.
The SAFEWAY IT platform was developed under WP7, which comprised all the task to compile the databases, models, and services developed in the aforementioned WPs.
An additional WP8 was focused in reconsideration of resilience in a longer term. This included: i) an effective Emergency Plan Guideline for linear infrastructures; ii) a wide identification of adaptation needs after evaluating the performance of each of the critical assets when facing each of the hazards that could have an impact of them and, iii) novel laboratory research, related to the characterization and study of Shape Memory Steels (SMS) and Optical Fiber Sensors.
Considering the wide range of solutions with potential for valorization and/or exploitation, a Business and Exploitation Plan has developed that includes the identification of 22 tangible results, from which 12 were classified as key exploitable results whose exploitation strategy is currently under development by the corresponding owner partner.
WP 2 has identified risk factors affecting hazard and vulnerability and provided an integration of hazard inventories, databases and maps as well as tools for quantification of their impacts. Critical hazards (natural and human-made) and plausible failure modes have been identified. Guidance for assessment of the probability and severity of service disruption, by using structural and functional vulnerability functions, has also been provided.
In WP3, an analysis of remote sensing technologies that contribute to more efficient monitoring of critical assets. These include satellite technologies and terrestrial technologies to obtain geometrical and radiometric data from the studied environments with high accuracy. After having a clear vision of which specific technologies can contribute to the monitoring requirements of operators' owners, several monitoring scenarios have been defined and clear data acquisition protocols have been proposed.
Crowdsourcing methods for gathering data regarding vehicle parameters were developed in WP4. Interface definition was formulated on extracting floating car data for area wide road network monitoring. Also, a web service was designed for designating restriction zones by the traffic management operator in order to influence planned car routes so that such areas are avoided.
The development of performance predictive models for critical infrastructure assets was conducted in WP5. Deterministic models were used for predicting the deterioration of infrastructure components. Stochastic models were also used for predicting the future condition, and to overcome the lack of inspection records. Additionally, work was developed for the infrastructure risk-based models, consisting of the production of hotspot-maps for wildfires and floods situation and consideration of fragility curves for different assets. Impact assessment at regional scale, i.e. assessment of probability of failure modes leading to reduced mobility was also conducted considering a mesoscopic traffic model.
WP6 concentrated on developing of a robust, resilience-based decision support framework for terrestrial transportation. The first task was to establish a general value system regarding network resilience, based on monetized direct and indirect consequences of inadequate asset performance due to hazards and/or man-made events. The current asset management practice for quality assessment of road/rail infrastructure and the state-of-the-art research on the Key Performance indicators (KPIs) were investigated.
The SAFEWAY IT platform was developed under WP7, which comprised all the task to compile the databases, models, and services developed in the aforementioned WPs.
An additional WP8 was focused in reconsideration of resilience in a longer term. This included: i) an effective Emergency Plan Guideline for linear infrastructures; ii) a wide identification of adaptation needs after evaluating the performance of each of the critical assets when facing each of the hazards that could have an impact of them and, iii) novel laboratory research, related to the characterization and study of Shape Memory Steels (SMS) and Optical Fiber Sensors.
Considering the wide range of solutions with potential for valorization and/or exploitation, a Business and Exploitation Plan has developed that includes the identification of 22 tangible results, from which 12 were classified as key exploitable results whose exploitation strategy is currently under development by the corresponding owner partner.
The research nature of the project promoted the development of several methods progressing beyond the state of the art. The main remarkable results in this regard refer to a risk-based framework for assessment of the probability and severity of infrastructure malfunctioning due to extreme events. The framework encompasses risk identification, assessment of hazard, exposure, vulnerability and impacts. Recommendations of modelling variables and failure modes are provided for natural and human-made hazards as well as strategies for developing vulnerability functions and their application in consequence assessment. The stochastic predictive model developed using collaborative Gaussian Process Regression represents a progress beyond the state of the art, as it overcomes the lack of enough inspection data. The second set of methodologies refer to the concept of Building Information Modelling (BIM) that in the beginning, was used specifically for buildings; nowadays, its use is broader and it can also be referred to any infrastructure and so it is sometimes called Infrastructure Information Modelling (IIM). To this concern, SAFEWAY is delivering tools to create information models of the transportation network and its assets. This is performed according to the latest Open Standards developed by the international community. The relevance of these and other results was proven through the production of more than 60 peer-reviewed journal papers. It is important to remark also that the 5 SMEs taking part in SAFEWAY have developed IT solutions with market updates, valorizing thus the EC investment in resilience of transport infrastructure.