#	Pagina
attuale pagina	/open-h2020/projects/209711/results.html

Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - SAFE-10-T (Safety of Transport Infrastructure on the TEN-T Network)

Teaser

Summary

Transport infrastructure managers are tasked with ongoing maintenance activities, as well as long-term investment decisions regarding the upgrade and replacement of infrastructure assets. Decisions about where to implement investments are problematic due to the size and complexity of transport networks, and the vast quantity of infrastructure assets. A combination of ageing infrastructure, more frequent extreme weather events and increasing transport demand has led to a significant increase in the occurrence of asset failures along transport networks.

Current systems for managing transport infrastructure assets are heavily reliant on visual inspection, meaning that decision making is based on qualitative rather than quantitative data and, therefore, is highly subjective. To support reliable decision making based on quantitative data, the SAFE-10-T project is developing a global risk framework that will form the basis of an online Decision Support Tool (DST) to support decision-making in relation to the management of transport infrastructure along the European TEN-T network. The DST will consider the multi-modality of road, rail and inland waterway networks in terms of transport disruption due to asset failures. End-users will be able to assess the impact of interventions for infrastructure assets, including bridges, tunnels and earthworks and novel machine learning applications are being developed both at asset and network levels to provide real-time safety assessments for critical infrastructure assets. The targeted end-users are government authorities and infrastructure owners that will use the DST to make strategic investment decisions regarding transport infrastructure.

The project directly aligns with the objective of the European Union to increase safety levels across all transport modes, recognising that budgets are limited and that there are growing demands on infrastructure assets arising from increasing traffic levels and more frequent extreme weather events due to climate change. The project will exploit the increase in the availability of asset monitoring data, arising from recent developments in remote monitoring technologies through the development of novel algorithms that enable infrastructure assets to become â€˜smartâ€™ by communicating their current condition. To do so, novel machine learning applications will be developed that use remotely monitored data to provide advanced real-time safety assessments of critical transport infrastructure assets. The ultimate objective of the SAFE-10-T project is to take advantage of the proliferation of transport network data currently available (through linked open data sources, smartphones, advanced vehicles, etc.) by implementing data analytic techniques that support transport infrastructure safety management.

Work performed

The SAFE-10-T project has completed 18 months of research activities and is now midway through the project. The following sections provide a summary of the research activities undertaken in each of the technical work packages:

WP1 - Monitoring and Modelling

WP1 is focused on the development of advanced safety assessment models for transport infrastructure assets. The project is developing probabilistic methods for the safety analysis for bridges, tunnels and earthworks, and is exploring novel machine learning applications for real-time condition monitoring of these assets. This WP has also explored methods of resilience assessment for transport networks, which is summarised in D1.1 \'Probabilistic Consideration Resilience\'.

WP2 - Network Analysis

The activities undertaken in WP2 to date have focused on determining current and future demand for road, rail and inland waterway transport along the TEN-T network. D2.1 \'Report on User Demand Analysis\' has been published, which reviews existing transport demand studies and describes a methodology to evaluate current and future user demand for transport services. A series of online surveys have been developed for the purposes of data collection, which are available on the project website and social media profiles. Additionally, a series of dedicated stakeholder meetings are being organised to gather data in relation to transport demand and user requirements. Significant progress has also been made in this WP in relation to the development of a European-scale, multi-modal traffic analysis simulation model.

WP3 - Global Safety Framework

WP3 is focused on the development of the DST that is underpinned by a global safety framework, which will support decision making regarding the management of transport infrastructure along the European TEN-T network. These decisions primarily relate to medium- to long-term interventions on road, rail and inland waterway transport infrastructure, to increase safety and to maximise network capacity. This work package is also developing machine learning algorithms and is providing a big data platform to support multiple data sources and to process large datasets in real time.

WP4 - Demonstration Projects

WP4 is applying the methodologies and tools developed in the SAFE-10-T project to three demo sites as follows:

1. Port of Rotterdam, the Netherlands
2. Port of Rijeka, Croatia
3. Severn River Crossing, United Kingdom.

The SAFE-10-T project has conducted various dissemination activities during the first 18 months of the project to maximise the impact, including a stakeholder workshop, as well as engagement with infrastructure managers and owners. The target audience of the project includes road, rail and inland waterway infrastructure managers and owners, industry professionals, policy makers, researchers, standards bodies, as well as transport users.

Final results

Novel methods are being developed in the project to evaluate the safety of individual critical infrastructure assets, including bridges, tunnels and earthworks that incorporate monitoring data. The aim is to determine the probability of failure for individual assets, which will provide a key input into the global risk framework.

A multi-modal traffic model is being developed to quantify the consequences of asset failure in terms of transport disruption at network level. Both freight and passenger traffic will be considered across road, rail and inland waterway transport modes within the traffic model. As such, the model will facilitate the analysis of the consequences of the failure of an asset along one network mode on another mode type.

The safety models for individual infrastructure assets, as well as the network traffic model, will feed into a global risk framework that will analyse the impact of asset failures in terms of traffic disruption and safety impacts. The global risk framework will be incorporated within the DST, which can be used to support decision-making regarding the management of infrastructure assets and will ultimately support increased safety and network capacity along the TEN-T network.