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The merging process from an acceleration lane to the through lane of a motorway is an important aspect at interchanges, both in terms of safety and operating conditions. Several studies have demonstrated that the merging zones of interchanges are the main sources of interference between through and entering vehicles. In this context, incorrectly assessed gaps and headways can lead to severe crashes and traffic delays at interchanges. This study investigates the effectiveness of different countermeasures to improve the safety of merging zones and the ability of through drivers to adopt safe headways to vehicles entering from the motorway on-ramp. Four different countermeasures were tested in a driving simulator study: i) a gap metering signalization, consisting of a Variable Message Sign (VMS) and new pavement markings; ii) a static symbol projected on the vehicle’s windshield by means of a Head-Up Display (HUD) that informed the driver to maintain safe headways to the entering vehicle; iii) a dynamic symbol based on Augmented Reality (AR) technology, built into connected vehicle technology, that provided additional visual information to the driver about his current headway to the entering vehicle; iv) the AR system was also tested with an additional audio warning. The driving behavior of forty-four drivers under the four different configurations based on the tested countermeasures was then compared to the driving behavior recorded under a configuration without any countermeasures (baseline condition). The results revealed significant positive effects of all the countermeasures, especially of the AR systems that helped through drivers to adjust their headway to the entering vehicle and thus the most effective solution for improving the safety of the merging zone. This study confirmed the great potential of AR and connected vehicle technologies to improve general safety conditions on the road network, especially in risky situations and difficult maneuvers.

Infrastructure networks are crucial elements to ensure the sustainability of the current development model in which the movement of people and goods is essential. On the other hand, transport assets are increasingly exposed to several issues, including climatic conditions changing, vulnerability and exposure to natural hazards such as hydraulic, geomorphological, landslides and seismic phenomena, which can affect the structural integrity causing damages and deteriorations. The context is made even more serious by the degradation of materials and the progressive ageing of infrastructure, often accelerated by environmental conditions and inadequate, or not always effective, maintenance actions. This requires the investigation of novel methods for the large-scale detection of network-scale linear infrastructures, and simultaneously, of detail to diagnose causes and determine the priorities for the most effective countermeasures. The proposed solution is based on a Data-Fusion approach, merging data coming from multi-source and multi-scale data, to enhance the interpretation process in a holistic sense. The information comes from spaceborne Multi-temporal SAR Interferometry, complemented by more detailed aerial data, detected by UAVs and Ground Based Non-Destructive Testing Methods, including laser scanner surveys for resolution and digital integrability, high-resolution camera measurements assisted by artificial intelligence for the surface degradation and from prospecting data collected by Ground Penetrating Radar technology. All these data can be simultaneously analyzed into a comprehensive digital platform, providing a useful tool to support operators and public bodies to prioritize maintenance actions. The digital platform can be investigated also using augmented reality tools, capable of generating and reproducing the Digital Twin of the inspected infrastructure into a real environment. This allows any monitoring evaluation through a diagnostic technique that integrates spatial, aerial, ground-based and geophysical surveys, allowing navigation within the infrastructure. Potential applications are numerous, ranging from mapping of wide areas affected by potential criticality to the definition of the main vulnerabilities related to the seismic and hydraulic risks, the analysis of land changes surrounding the assets following extreme natural events, and the reconstruction of historical deformative trends of roads, railways and bridges through the interpretation of SAR data. Acknowledgments This research is supported by the Italian Ministry of Education, University, and Research under the National Project “EXTRA TN”, PRIN2017, Prot. 20179BP4SM. In addition, this research is supported by the Project “MLAZIO” funded by Lazio Region (Italy).

One of the main priorities for road administrations and stakeholders is the management and monitoring of critical infrastructures, especially transportation infrastructures. In this context, Building Information Modeling (BIM) can be one of the more effective methodologies to be used to optimize the management process. In Italy, several laws and regulations have been issued, making the use of BIM procedures mandatory for the design of new infrastructures and emphasizing its role in the management of existing civil works [1, 2].Monitoring operations of transportation infrastructures are generally conducted by on-site surveys. Non-Destructive Testing methods (i.e., GPR, LiDAR, Laser Profilometer, InSAR, etc.) have been used to perform these inspections as their outputs have been proven to be effective in determining the conditions of the infrastructure and its assets [3]. Moreover, BIM methodology could prove a valuable tool to manage the data provided by these surveys, as it consists in the creation of digital models capable of containing information related to the object that they are representing. These models can be used to store over time the different information obtained by the NDT surveys to carry out integrated analysis on the conditions of the infrastructure [4].This study aims to analyze a potential BIM process capable of integrating different NDT surveys’ outputs, to generate an informative digital model of an infrastructure and its assets. The proposed methodology is then able to merge the data provided by the inspections, which is typically obtained by different operators and comes in different file formats, in a single BIM model. The main goal of the research is to provide a process to optimize the management procedures of transportation infrastructures, by creating digital models capable of reducing the problems typically associated with the monitoring and maintenance of these critical civil works. By merging different information in a single environment and relying on survey data that are commonly analyzed separately, an integrated analysis of the infrastructure can be carried out and data loss can be reduced.The study was developed by relying on real data, obtained from on-site surveys carried out over Italian infrastructures. As different outputs have been collected, BIM models of different assets of the analyzed infrastructures were defined. Preliminary results have shown that the proposed methodology can be a viable tool for optimizing the management process of these critical civil works.AcknowledgementsThe research is supported by the Italian Ministry of Education, University and Research under the National Project “Extended resilience analysis of transport networks (EXTRA TN): Towards a simultaneously space, aerial and ground sensed infrastructure for risks prevention”, PRIN 2017. Prot. 20179BP4SM.References[1] MIT, 2018. Ministero delle Infrastrutture e dei Trasporti, D. Lgs 109/2018[2] MIT, 2021. Ministero delle Infrastrutture e dei Trasporti, D.M. 312/2021[3] D’Amico F. et al., 2020. Integration of InSAR and GPR Techniques for Monitoring Transition Areas in Railway Bridges. NDT&E Int[4] D’Amico, F. et al., 2022. Integrating Non-Destructive Surveys into a Preliminary BIM-Oriented Digital Model for Possible Future Application in Road Pavements Management. Infrastructures 7, no. 1

Background: Several studies have been conducted by combining the benefits of eye-tracking systems with driving simulators to simultaneously investigate driving behavior and the potential source of distraction. However, little effort has been made in terms of eye-tracking validation in the driving simulator environment. Objective: The overall aim of this study is to validate an eye-tracking system within the context of a driving simulation environment by considering a specific urban context application. Methods: A field survey and a driving simulation experiment were conducted for a case study in Rome, Italy. The selected real road sections and events were reproduced on the driving simulator system. An eye-tracking system was used to record eye movements both on a real vehicle and the simulator. The eye movements of 14 participants in the field survey and 18 participants in the driving simulation tests, as well as their driving performances, were collected while approaching an urban intersection in relation to two specific road events: i) the presence of a speed limit sign and ii) the presence of a crossing pedestrian. Results: Eye tracker parameters and driving performances were compared between the real driving tests and driving simulator experiments in order to validate the eye-tracking system. It was validated for both events in terms of duration and distance of the eye fixation. Conclusion: The results demonstrated that an eye-tracking system is an effective tool for studies and applications in a virtual reality environment.

When drivers approach a signalized intersection at the start of the yellow signal, they might be reluctant to decide whether to stop or go through the intersection due to the dilemma zone (DZ), with the consequent risk of improper behaviors that can lead to rear-end collisions and right-angle crashes. The main goal of this research is to analyze the driver's behavior at the onset of the yellow signal and to identify the most effective countermeasures for the resolution of the dilemma zone in order to improve the safety and efficiency of urban signalized intersections. A driving simulator study was carried out, and three different countermeasures were specifically designed and tested: Green Signal Countdown Timers (GSCT) (C1); a new scheme of vertical and horizontal warning signs (C2); and an in-vehicle advanced driving assistance system that uses Augmented Reality (AR) and connected vehicle technologies (C3). Forty-six volunteers took part in the experiments, driving the same scenario four times (three with countermeasures and one as a baseline condition). The results demonstrated that with countermeasure C1, the length of the DZ increased with respect to the baseline condition; moreover, the stop/go drivers’ decisions were found to be more inconsistent, increasing the potential risk of rear-end crashes. Conversely, countermeasures C2 and C3 resulted in a reduction of DZ length (-30.5% and 21.6%, respectively); in addition, C2 was found to be the one that recorded the greatest consistency of drivers’ decision-making behaviors, while C3 provided the drivers with timely and personalized early-stop warnings and recorded fewer wrong behaviors. Based on the results of this study, C2 and C3 countermeasures might be a good way to improve safety and operations at urban signalized intersections and cut down on the number of drivers who aren't sure what to do when the yellow light comes on.

The monitoring of the structural integrity of road and transport infrastructures, and in particular of bridges and viaducts, has now become a priority issue, emphasized by the progressive decay of the characteristics of building materials, and deterioration of the works, which can cause damage and collapses with dramatic consequences. Following recent bridge collapses, including the "Polcevera Bridge"in Genoa, Italy, the Ministry of Infrastructures and Sustainable Mobility (MIMS) issued in 2020 specific Guidelines on the classification and risk management, safety assessment and monitoring of existing bridges. In this context, the creation of information catalogues for the mapping of structures and the implementation of innovative procedures for monitoring, appear to be a crucial step for public bodies and managing bodies end of assessing the state of the civil structures such as bridges and identifying the priorities maintenance actions. To date, monitoring operations of bridges are typically conducted through visual inspections, coring and punctual measurements carried out by specialized operators and, more rarely, through the use of Non-Destructive Technologies (NDT). On the other hand, in recent years, satellite radar remote sensing techniques have always been applied much more effectively at monitoring infrastructures, civil works, bridges and viaducts. Among the modern techniques, Multi-Temporal Satellite Radar Interferometry (MT-InSAR) is currently established as a reliable tool for control and monitoring of deformation phenomena of the soil and large-scale infrastructures, capable of returning information with millimetre accuracy. Moreover, the knowledge about structural materials, structural elements and defect state of the bridge collected by onsite inspection, is crucial to verify the stability to actual traffic and dynamic loads, not expected in the design phases. This work reports a methodology useful for evaluating the viaducts and bridges stability at the network-scale level, proposing a multi-level monitoring protocol from the integration of information from different sources and technologies, including ground-based, structural and remote sensing information. The activities are carried out as a part of the "MLAZIO"project, approved and supported by the Lazio Region. The first phase of this project involves the creation of a vector database for bridges mapping and localization, and the development of an informatic catalogue for the management of works, also including a view of the geo-eGovernment of the infrastructures. Such a system is developed on a platform interoperable in a Geographical Information System (GIS), already prepared for the expected integrations in the later stages of the project, which includes on-site inspections, NDTs ground-based and satellite remote sensing investigations. This project aims to create a reliable and effective methodology for the risk assessment and management of existent bridges. This study paves the way for optimizing the planning procedures of the interventions of ordinary and extraordinary maintenance activities by developing a prototype for the development of a Bridge Management System (BMS) at a regional level, increasing the resilience of the investigated infrastructures and bridges.

Monitoring of critical civil engineering infrastructures, and especially viaducts and bridges, has become a priority nowadays as the ageing of construction materials may cause damages and collapses with dramatic consequences. Following recent bridge collapses, specific guidelines on risk classification and management, safety assessment and monitoring of existing bridges have been issued in Italy, by the Minister of Infrastructure as a mandatory code [1]. Accordingly, several laws and regulations have been issued on the same topic, emphasizing the crucial role of BIM-based procedures for the design and management of civil infrastructures [2, 3]. Within this context, monitoring operations are generally conducted by on-site inspections and specialized operators, and rarely by high-frequency ground-based Non-Destructive Testing methods (NDTs). Furthermore, the implementation of satellite-based remote sensing techniques, have been increasingly and effectively used for the monitoring of bridges in the last few years [4]. Generally, these crucial pieces of information are analyzed separately, and the implementation of a multi-scale and multi-source interoperable BIM platform is still an open challenge [5].This study aims at investigating the potential of an interoperable and upgradeable BIM platform supplemented by non-destructive survey data, such as Mobile Laser Scanner (MLS), Ground Penetrating Radar (GPR) and Satellite Remote Sensing Information (i.e. InSAR). The main goal of the research is to contribute to the state-of-the-art knowledge on BIM applications, by testing an infrastructure management platform aiming at reducing the limits typically associated to the separate observation of these assessments, to the advantage of an integrated analysis including both the design information and the routinely updated results of monitoring activities.The activities were conducted in the framework of the Project “M.LAZIO”, approved by the Lazio Region, with the aim to develop an informative BIM platform of the investigated bridges interoperable within a Geographic Information System (GIS). As on-site surveys are carried out , a preliminary multi-source database of information is created, to be operated as the starting point for the integration process and the development of the infrastructure management platform. Preliminary results have shown promising viability of the data management model for supporting asset managers in the various management phases, thereby proving this methodology to be worthy for implementation in infrastructure integrated monitoring plans.AcknowledgementsThis research is supported by the Project “M.LAZIO”, accepted and funded by the Lazio Region, Italy. Funding from MIUR, in the frame of the “Departments of Excellence Initiative 2018–2022”, attributed to the Department of Engineering of Roma Tre University, is acknowledged.References[1] MIT, 2020. Ministero delle Infrastrutture e dei Trasporti, DM 578/2020[2] EU, 2014. Directive 2014/24/EU of the European Parliament and of the Council of 26 February 2014 on public procurement and repealing Directive 2004/18/EC.[3] MIMS, 2021. Ministero delle Infrastrutture e della Mobilità Sostenibile, DM 312/2021[4] Gagliardi, V. et al., “Bridge monitoring and assessment by high-resolution satellite remote sensing technologies”. In SPIE Future Sensing Technologies; https://doi.org/10.1117/12.2579700[5] D'Amico F. et al., "A novel BIM approach for supporting technical decision-making process in transport infrastructure management", Proc. SPIE 11863; https://doi.org/10.1117/12.2600140

Maintenance of airport runways is crucial to comply with strict safety requirements for airport operations and air traffic management [1]. Therefore, monitoring pavement surface defects and irregularities with a high temporal frequency, accuracy and spatial density of information becomes strategic in airport asset management [2-3]. In this context, Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques are gaining momentum in the assessment and health monitoring of infrastructure assets, proving their viability for the long-term evaluation of ground scatterers. However, the implementation of C-band SAR data as a routine tool in Airport Pavement Management Systems (APMSs) for the accurate measurement of differential displacements on runways is still an open challenge [4]. This research aims to demonstrate the viability of using medium-resolution (C-band) SAR products and their contribution to improve current maintenance strategies in case of localised foundation settlements in airport runways. To this purpose, Sentinel-1A SAR products, available through the European Space Agency (ESA) Copernicus Program, were acquired and processed to monitor displacements on “Runway n.3” of the “L. Da Vinci International Airport” in Fiumicino, Rome, Italy.A geostatistical study is performed for exploring the spatial data structure and for the interpolation of the Sentinel-1A SAR data in correspondence of ground control points.The analysis provided ample information on the spatial continuity of the Sentinel 1 data, also in comparison with the high-resolution COSMO-SkyMed and the ground-based topographic levelling data, taken as the benchmark.Furthermore, a comparison between the MT-InSAR outcomes from the Sentinel-1A SAR data, interpolated by means of Ordinary Kriging, and the ground-truth topographic levelling data demonstrated the accuracy of the Sentinel 1 data. Results support the effectiveness of using medium-resolution InSAR data as a continuous and long-term routine monitoring tool for millimetre-scale displacements in airport runways. Outcomes of this study can pave the way for the development of more efficient and sustainable maintenance strategies for inclusion in next-generation APMSs. Acknowledgments and fundings: The authors acknowledge the European Space Agency (ESA), for providing the Sentinel 1 SAR products for the development of this research. The COSMO-SkyMed Products—©ASI (Italian Space Agency)- are delivered by ASI under the license to use.This research falls within the National Project “EXTRA TN”, PRIN 2017, supported by MIUR. The authors acknowledge funding from the MIUR, in the frame of the “Departments of Excellence Initiative 2018–2022”, attributed to the Department of Engineering of Roma Tre University References[1]Gagliardi V., Bianchini Ciampoli L., D'Amico F., Tosti F., Alani A. and Benedetto A. “A Novel Geo-Statistical Approach for Transport Infrastructure Network Monitoring by Persistent Scatterer Interferometry (PSI)”. In: 2020 IEEE Radar Conference, Florence, Italy, 2020, pp. 1-6[2]Gagliardi V, Bianchini Ciampoli L, Trevisani S, D’Amico F, Alani AM, Benedetto A, Tosti F. "Testing Sentinel-1 SAR Interferometry Data for Airport Runway Monitoring: A Geostatistical Analysis". 2021; 21(17):5769. https://doi.org/10.3390/s21175769[3]Gao, M.; Gong, H.; Chen, B.; Zhou, C.; Chen, W.; Liang, Y.; Shi, M.; Si, Y. "InSAR time-series investigation of long-term ground displacement at Beijing Capital International Airport, China". Tectonophysics 2016, 691, 271–281.[4]Department of Transportation Federal Aviation Administration (FAA), Advisory Circular 150/5320-6F, Airport Pavement Design and Evaluation, 2016

Maintenance and rehabilitation policies represent a task of paramount importance for managers and administrators of railway networks to maintain the highest standards of transport safety while limiting as much as possible the costs of maintenance operations.To this effect, high-productivity survey methods become crucial as they allow for timely recognition of the quality of the asset elements, among which the ballast layers are the most likely to undergo rapid deterioration processes. Particularly, Ground Penetrating Radar (GPR) has received positive feedback from researchers and professionals due to the capability of detecting signs of deterioration within ballasted trackbeds that are not recognizable by a visual inspection at the surface, through high-productivity surveys. On the other hand, satellite-based surveys are nowadays being increasingly applied to the monitoring of transport assets. Techniques such as Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) allows evaluating potential deformations suffered by railway sections and their surroundings by analyzing phase changes between multiple images of the same area acquired at progressive times. For both of these techniques, despite the wide recognition by the field-related scientific literature, survey protocols and data processing standards for the detection and classification of the quality of ballast layers are still missing. In addition, procedures of integration and data fusion between GPR and InSAR datasets are still very rare.The present study aims at demonstrating the viability of the integration between these two survey methodologies for a more comprehensive assessment of the condition of ballasted track-beds over a railway stretch. Particularly, a traditional railway section going from Cava de’ Tirreni to Salerno, Campania (Italy), was subject to both GPR and MT-InSAR inspections. An ad hoc experimental setup was realized to fix horn antennas with different central frequencies to an actual inspection convoy that surveyed the railway stretch in both the travel directions. Time-frequency methods were applied to the data to detect subsections of the railway affected by the poor quality of ballast (i.e. high rate of fouling). In parallel, a two-years MT-InSAR analysis was conducted to evaluate possible deformations that occurred to the railway line in the period before the GPR test. In addition, results from both the analyses were compared to the reports from visual inspections as provided by the railway manager.The results of the surveys confirm the high potential of GPR in detecting the fouling condition of the ballast layers at various stages of severity. The integration of this information to the outcomes of InSAR analysis allows for identifying whether the deterioration of the track-beds is related to poorly bearing subgrades or rather to excessive stresses between the aggregates resulting in their fragmentation.AcknowledgmentsThis research is supported by the Italian Ministry of Education, University, and Research under the National Project “EXTRA TN”, PRIN2017, Prot. 20179BP4SM. Funding from MIUR, in the frame of the“Departments of Excellence Initiative 2018–2022”, attributed to the Department of Engineering of Roma Tre University, is acknowledged. The authors would also like to express their gratitude to RFI S.p.a. in the person of Eng. Pasquale Ferraro for the valuable support to the tests.

Globally, cyclists account for 3% of all road traffic deaths, with the highest percentage occurring in Europe (8%) where the bicycle is considered a true alternative mode of transport. Among the causes of crashes are vehicles overtaking cyclists, especially on rural roads. In this study, a new application of augmented reality (AR) warnings for connected vehicles is tested by means of a driving simulator. The overall objective of the study consists in assessing the effectiveness of three proposed AR systems in improving the safety of interactions between vehicles and cyclists, especially during overtaking maneuvers. The AR systems were tested on a sample of 46 drivers and provided them with additional virtual visual information aimed at improving the driver’s risk perception and assessment of safe distance from a cyclist. The virtual warning configurations were: (i) a yellow safety zone around the cyclist; (ii) a color-changing safety zone that changes from red to green when the driver has safe lateral space to overtake the cyclist; (iii) the same color-changing security zone but with an additional acoustic warning. The AR warnings were found to be quite effective as they helped drivers overtake cyclists more safely. With AR warnings (especially with the additional audio), it was found that drivers adopted longer distances from cyclists and entered the oncoming lane less frequently, thus lowering the risk of collision with cyclists as well as the risk of head-on collision with oncoming vehicles.

Advances in data processing and the availability of larger SAR datasets from high-resolution (X-Band) satellite missions have consolidated the use of the Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technique in the near-real-time assessment of bridges and the health monitoring of transport infrastructures. This research aims to investigate the viability of a novel non-destructive health-monitoring approach based on satellite remote sensing and ground based techniques for structural assessment of bridges and the prevention of damages related to structural subsidence. To this purpose, high-resolution X-Band SAR products were acquired and processed by MT-InSAR technique. Analyses were developed to identify and monitor the structural displacements of the historical "Ponte Sisto" masonry bridge located in Rome, Italy, crossing the Tiber River. To this extent, the historical time-series of deformations were processed by Persistent Scatterers (PSs) relevant to critical structural elements of the bridge (i.e., bridge piers and arcs). On the other hand, an on-site Ground Penetrating Radar investigation was directly conducted over the masonry bridge. More specifically, several frequencies were implemented for this purpose, with the aim to investigate the condition of the layers of the superstructures at different propagation lengths. A novel data interpretation approach is proposed based on the selection of several PS data-points with coherent deformation trends and location on the bridge, and the analysis of the B-Scan obtained by GPR investigations. The outcomes of this study demonstrate how multi-temporal InSAR remote sensing techniques can be applied to complement non-destructive ground-based analyses (e.g., ground-penetrating radars), paving the way for future integrated approaches for monitoring of infrastructure assets

Monitoring of bridges and viaducts has become a priority for asset owners due to progressive infrastructure ageing and its impact on safety and management costs. Advancement in data processing and interpretation methods and the accessibility of Synthetic Aperture Radar (SAR) datasets from different satellite missions have contributed to raise interest for use of near-real-time bridge assessment methods. In this context, the Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) space-borne monitoring technique has proven to be effective for detection of cumulative surface displacements with a millimetre accuracy [1-3].This research aims to investigate the viability of using satellite remote sensing for structural assessment of the Rochester Bridge in Rochester, Kent, UK. To this purpose, high-resolution SAR datasets are used as the reference information and complemented by additional data from different sensing technologies (e.g., medium-resolution SAR datasets and ground-based (GB) non-destructive testing (NDT)). In detail, high-resolution SAR products of the COSMO-SkyMed (CSK) mission (2017-2019) provided by the Italian Space Agency (ASI) in the framework of the Project “Motib - ID 742”, approved by ASI, are processed using a MT-InSAR approach.The method allowed to identify several Persistent Scatterers (PSs) – which have been associated to different structural elements (e.g., the bridges piers) over the four main bridge decks – and monitor bridge displacements during the observation time. The outcomes of this study demonstrate that information from the use of high-resolution InSAR data can be successfully integrated to datasets of different resolution, scale and source technology. Compared to stand-alone technologies, a main advantage of the proposed approach is in the provision of a fully-comprehensive (i.e., surface and subsurface) and dense array of information with a larger spatial coverage and a higher time acquisition frequency. This results in a more effective identification and monitoring of decays at reduced costs, paving the way for implementation into next generation Bridge Management Systems (BMSs).Acknowledgements: This research is supported by the Italian Ministry of Education, University and Research under the National Project “EXTRA TN”, PRIN2017, Prot. 20179BP4SM. Funding from MIUR, in the frame of the“Departments of Excellence Initiative 2018–2022”,attributed to the Department of Engineering of Roma Tre University, is acknowledged.Authors would also like to acknowledge the Rochester Bridge Trust for supporting research discussed in this paper. The COSMO-SkyMed (CSK) products - ©ASI- are provided by the Italian Space Agency (ASI) under a license to use in the framework of the Project “ASI Open-Call - Motib (ID 742)” approved by ASI.References[1] Gagliardi V., Bianchini Ciampoli L., D'Amico F., Alani A. M., Tosti F., Battagliere M. L., Benedetto A., “Bridge monitoring and assessment by high-resolution satellite remote sensing technologies”, Proc. SPIE 11525, SPIE Future Sensing Technologies. 2020. doi: 1117/12.2579700[2] Jung, J.; Kim, D.-j.; Palanisamy Vadivel, S.K.; Yun, S.-H. "Long-Term Deflection Monitoring for Bridges Using X and C-Band Time-Series SAR Interferometry". Remote Sens. 2019[3] Gagliardi V., Bianchini Ciampoli L., D'Amico F., Tosti F., Alani A. and Benedetto A. “A Novel Geo-Statistical Approach for Transport Infrastructure Network Monitoring by Persistent Scatterer Interferometry (PSI)”. In: 2020 IEEE Radar Conference, Florence, Italy, 2020, pp. 1-6, doi: 10.1109/RadarConf2043947.2020.9266336

Advances in data processing and the availability of larger SAR datasets from various high-resolution (X-Band) satellite missions have consolidated the use of the Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) technique in the near-real-time assessment of bridges and the health monitoring of transport infrastructures. This research aims to investigate the viability of a novel non-destructive health-monitoring approach based on sat-ellite remote sensing techniques for structural assessment of bridges and the prevention of damage by structural subsidence. To this purpose, commercial high-resolution TerraSAR-X (TSX) products of the German Aerospace Cen-tre (DLR) provided by the European Space Agency (ESA), were acquired and processed by MT-InSAR technique. Analyses were developed to identify and monitor the structural displacements of the historical “Ponte Sisto” masonry bridge located in Rome, Italy, crossing the Tiber River. To this extent, the historical time-series of deformations were processed by Persistent Scatterers (PSs) relevant to critical structural elements of the bridge (i.e., bridge piers and arcs). A novel data interpretation approach is proposed based on the se-lection of several PS data-points with coherent deformation trends and loca-tion on the bridge. The outcomes of this study demonstrate that multi-temporal InSAR remote sensing techniques can be applied to complement non-destructive ground-based analyses (e.g., ground-penetrating radars, laser scanners, accelerometers), paving the way for future integrated approaches in the smart monitoring of infrastructure assets.

Eye-tracking has been widely used for decades in vision research, language, and usability. In the area of road engineering, the eye-tracking system has been used both for on-field and in driving simulation studies. The overall advantage of using an eye-tracker is that different parameters regarding eye-movement towards visible stimuli in the environment can be measured, such as eye-fixations and saccades. Several studies have been developed by combining the benefits of the eye-tracking system with driving simulators to simultaneously investigate driving behaviour and the potential source of distraction. However, little effort has been spent in terms of eye-tracking validation in the driving simulator environment. To fill this gap, both a field survey and a driving simulation experiment have been developed for a case study located in Rome, Italy. The selected road sections and events have been reproduced on the fixed-based driving simulator system at the Department of Engineering of Roma Tre University. A Tobii glasses eye-tracking system has been used to record the eye movements both on board of a real vehicle and on the simulator. The eye movements of 14 participants in the field survey and 18 participants in the driving simulation tests, as well as their driving performances (speeds, accelerations, trajectories), have been investigated while approaching an urban intersection and in relation to two specific road events, both static and dynamic: i) the presence of a speed limit sign and ii) the presence of a crossing pedestrian. Eye tracker parameters and driving performances were compared between the real driving tests and driving simulator experiments in order to validate the eye-tracking system. Specifically, the eye-tracking system has been validated for both the events in terms of duration and distance of the eye fixation. Therefore, the results demonstrate that the eye-tracking system stands as an effective tool for studies and applications in a virtual reality environment.

At the onset of the yellow phase of signalized intersections, the approaching drivers may hesitate to decide to go or stop due to the dilemma zone (DZ). The drivers who decide to pass through the intersection might occur in red light violations and right-angle crashes, while some others might stop suddenly and prematurely with the subsequent risk of rear-end collisions. This study is aimed at analyzing the driver's behavior at the onset of the yellow signal, and identifying the most effective safety countermeasure for the resolution of the dilemma zone in order to help drivers in their stop/go decisions and reduce the risk of crashes. To achieve this objective, a driving simulator study was carried out and the effects of the following countermeasures were tested on a signalized intersection of an urban scenario: i) Green Signal Countdown Timers GSCT (C1); ii) newly developed horizontal marking and vertical warning sign (C2); iii) an in-vehicle advanced driving assistance system based on augmented reality and connected vehicle technologies (C3). The results revealed that the most effective countermeasure was C3 which provided the drivers with prompt and personalized suggestions based on their actual speed; in fact, a major reduction of Red Light Running (RLR) and length of the dilemma zone were recorded. C2 resulted in a significant reduction of the dilemma zone with the greatest consistency in driver decision-making behaviors. Finally, using C1 it was observed an unnecessary increase in early stopping rates with a reduction of the intersection efficiency.

Monitoring of critical civil engineering infrastructures, and especially viaducts and bridges, has become a priority. Specific guidelines on risk classification and management, safety assessment and monitoring of existing bridges have been issued in Italy. Several laws and regulations have been issued on the same topic, emphasizing the crucial role of BIM-based procedures for the design and management of civil infrastructures. This study aims at examining the potential of an interoperable and upgradeable BIM platform supplemented by non-destructive survey data, such as Mobile Laser Scanner (MLS), Ground Penetrating Radar (GPR) and satellite-based information. The main goal of the work is to implement an infrastructure management platform that aims at reducing the limits associated to the separate observation of these assessments and to provide a more efficient way to store data regarding the status of bridges and viaducts, to the advantage of an integrated analysis. This work aims to develop an informative BIM platform of the investigated bridges, interoperable within a Geographic Information System (GIS) database. As on-site surveys are carried out, a preliminary multi-source database of information is created. Preliminary results have shown promising viability of the data management model for supporting asset managers in the various management phases.

Continuous monitoring of critical infrastructures is crucial to prevent catastrophic events such as collapse of viaducts and prioritising maintenance interventions. However, developing effective monitoring approaches must rely on the collection of a variety of information, such as the time series of structural deformations. In this context, various ground-based non-destructive testing (NDT) methods have been used in monitoring the structural integrity of transport infrastructures. However, these require routine and systematic application at the network level over long periods of time to build up a solid database of information, involving many efforts from stakeholders and asset owners in the sector. To this effect, satellite-based remote sensing techniques, such as the Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR), have gained momentum due to the provision of accurate cumulative structural displacements in bridges. Although the application of the InSAR monitoring technique is established, this is limited to the high required time for the interpretation of the data with high spatial and temporal density. This research aims to demonstrate the viability of the MT-InSAR techniques for the structural assessment of bridges and the monitoring of damage by structural subsidence, using high-resolution SAR datasets, integrated with complementary Ground-Based (GB) information. To this purpose, high-resolution SAR dataset of the COSMO-SkyMed (CSK) mission provided by the Italian Space Agency (ASI), were acquired and processed in the framework of the ASI-Open Call approved Project “MoTiB” (ID 742). In particular, a Persistent Scatterer Interferometry (PSI) analysis is applied to identify and monitoring the structural displacements at the Rochester Bridge, in Rochester, Kent, UK. In order to explore the viability of Machine Learning algorithms in detecting critical situations in the monitoring phases, an Unsupervised ML Clustering approach, which generates homogeneous and well-separated clusters, is implemented. Each PS data-point is located to specific cluster groups, based on the deformation-trend and the values of displacements of the historical time-series. This research paves the way for the development of a novel interpretation approach relying on the integration between remote-sensing technologies and on-site surveys to improve upon current maintenance strategies for bridges and transport assets.

Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) techniques are gaining momentum in the assessment and health monitoring of infrastructure assets. Amongst others, the Persistent Scatterers Interferometry (PSI) technique has proven to be viable for the long-term evaluation of ground scatterers. However, its effectiveness as a routine tool for certain critical application areas, such as the assessment of millimetre-scale differential displacements in airport runways, is still debated. This research aims to demonstrate the viability of using medium-resolution Copernicus ESA Sentinel-1A (C-Band) SAR products and their contribution to improve current maintenance strategies in case of localised foundation settlements in airport runways. To this purpose, “Runway n.3” of the “Leonardo Da Vinci International Airport” in Fiumicino, Rome, Italy was investigated as an explanatory case study, in view of historical geotechnical settlements affecting the runway area. In this context, a geostatistical study is developed for the exploratory spatial data analysis and the interpolation of the Sentinel-1A SAR data. The geostatistical analysis provided ample information on the spatial continuity of the Sentinel 1 data in comparison with the high-resolution COSMO-SkyMed data and the ground-based topographic levelling data. Furthermore, a comparison between the PSI outcomes from the Sentinel-1A SAR data—interpolated through Ordinary Kriging—and the ground-truth topographic levelling data demonstrated the high accuracy of the Sentinel 1 data. This is proven by the high values of the correlation coefficient (r = 0.94), the multiple R-squared coefficient (R2 = 0.88) and the Slope value (0.96). The results of this study clearly support the effectiveness of using Sentinel-1A SAR data as a continuous and long-term routine monitoring tool for millimetre-scale displacements in airport runways, paving the way for the development of more efficient and sustainable maintenance strategies for inclusion in next generation Airport Pavement Management Systems (APMSs).

The European Directive 2014/24/EU and its recent Italian transposition law DM 560/2017 encourage an extensive use of BIM-based practices in transport infrastructure design. Therefore, a shift from the traditional design approach towards a shared and highly integrated model, capable of including the various design phases along with economic, operational and environmental concerns, is observed. In such a framework, this work evaluates the benefits returning from the integration between geospatially-referenced data and the BIM models for a more aware design approach. The major aim of this study is to underline the potential of an interoperable and shared model supplemented by GIS data, in minimizing or definitely removing the possible conflicts that typically arise between the infrastructure design and environmental constraints. Particularly, thanks to both the simultaneous assessment of each environmental component and the evaluation of the different project configurations, this methodology can provide an integrated technical/environmental overview of the design. As a result, it allows for immediately verifying the project to comply with the national minimum environmental criteria, which are mandatory for contractors according to the Italian environmental law n° 221/2015 and the new Italian Public Procurement Code. The proposed approach was finally tested on an airport infrastructure. Preliminary results have shown viability of the data management model for supporting designer’s choices in the various project phases, thereby proving this methodology to be worthy for implementation in infrastructure design procedures.

Multi-temporal Interferometric Synthetic Aperture Radar (InSAR) is a space-borne monitoring technique able to detect cumulative surface displacements with a millimetre accuracy within the line of sight (LOS) of the radar sensor. Several developments in the processing methods and an increase in the availability of SAR data sets from different satellite missions have proven the viability of this technique in the near-real-time assessment of bridges and the health monitoring of transport infrastructure. This research aims to demonstrate the potential of satellite-based remote sensing techniques in developing an innovative health-monitoring method for structural assessment of bridges and the prevention of subsidence damage, using high-resolution SAR data sets and complementary ground-based (GB) non-destructive testing (NDT) techniques. To this purpose, high-resolution COSMO-SkyMed (CSK) products provided by the Italian Space Agency (ASI) were acquired and processed. A multitemporal InSAR analysis was developed to identify and monitor the structural displacements of the Rochester Bridge, located in Rochester, Kent, U.K. This bridge is composed by four separate bridge decks carrying the A2 Road, a railway, and a service-bridge carrying service pipes and cable. The outcomes of this study demonstrate how multitemporal InSAR remote sensing techniques can be synergistically applied to complement the traditional GB analyses (e.g., ground penetrating radar, laser scanner, and accelerometers) and information on river bridges (e.g., river levels from monitoring stations). This can provide an extended spatial coverage and an effective identification and monitoring of defects and decays at reduced costs, compared to traditional monitoring techniques. © ASCE.All right reserved.

Bridges and viaducts are exposed to a variety of threats that can affect their operations and structural integrity [1]. Recent unexpected collapses and failures of bridges underline the need for effective structural monitoring, particularly for reinforced concrete structures. In fact, once distress mechanisms are triggered, these can deteriorate faster than the time required for rehabilitation, strengthening, or replacement.To this extent, it is evident that the monitoring of the actual health conditions of the existing bridges is a priority for asset operators in order to guarantee the structural integrity, the safety of the operations and preventing irreversible damages or even structural collapses.Within this context, Non-Destructive Testing (NDT) methods such as Ground Penetrating Radar (GPR) and Terrestrial Laser Scanner (TLS) amongst many others have been used for the assessing and monitoring such structures in the past few years[2]. However, topic-related studies [3-4] have demonstrated that stand-alone use of ground-based techniques may not represent a definitive solution to particular major structural issues, such as scour and differential settlements, as these require continuous monitoring and data collection on long-term bases . To that extent, the use of satellite-based remote sensing techniques, such as Synthetic Aperture Radar Interferometry (InSAR), have proven to be effective in detecting displacements with a millimetre accuracy along with transport infrastructures [3-5] and natural terrain considering long periods of observation.Accordingly, this research aims to present a novel integrated monitoring approach including the use of ground-based technologies (GPR, TLS) and the InSAR techniques over a Maillart arch type bridge: the Viadotto Olivieri in Salerno, (in the South of Italy).Main objectives of the research are: (1) to prove the viability of low-frequency and high-frequency GPR systems in providing structural detailing of the bridge-deck at different depths and resolutions; (2) to measure seasonal structural displacements with a millimetre accuracy to detect potential critical issues of the bridge.The outcomes of this study, under the National Project “EXTRA TN”, PRIN 2017- Prot. 20179BP4SM, demonstrate how multi-temporal InSAR remote sensing techniques can be synergistically applied to complement the traditional ground-based surveys. References[1] Hosseini Nourzad, S. H. and Pradhan, A. Vulnerability of Infrastructure Systems: Macroscopic Analysis of Critical Disruptions on Road Networks. Journal of Infrastructure Systems, 22(1), 04015014. 2016[2] D’Aranno, P., Di Benedetto, A., Fiani, M., and Marsella, M.: Remote Sensing Technologies For Linear Infrastructure Monitoring, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W11, 461–468, https://doi.org/10.5194/isprs-archives-XLII-2-W11-461-2019, 2019.[3] Bianchini Ciampoli, L., Gagliardi, V., Clementini, et al., Transport Infrastructure Monitoring by InSAR and GPR Data Fusion. Surv Geophys 41, 371–394 (2020). https://doi.org/10.1007/s10712-019-09563-7[4] Gagliardi V., Benedetto A., Bianchini Ciampoli L., D’Amico F., Alani A., Tosti F., 2020. Health monitoring approach for transport infrastructure and bridges by satellite remote sensing Persistent Scatterer Interferometry (PSI). Proc.SPIE 11534. https://doi.org/10.1117/12.2572395[5] Bianchini Ciampoli L., Gagliardi V., Calvi A., D’Amico F., Tosti F., Automatic network-level bridge monitoring by integration of InSAR and GIS catalogues. Proceedings of SPIE - The International Society for Optical Engineering, 11059, (2019). DOI: 10.1117/12.2527299

The European Directive 2014/24/EU and its recent Italian transposition law DM 560/2017 strongly encourage an extensive use of BIM-based practices in transport infrastructure design and management operations. Accordingly, a step forward from the traditional management approach towards a shared and highly integrated model capable of including the various monitoring and maintenance phases along with economic, operational, and environmental concerns, is required. This study aims at investigating the potential of an interoperable and upgradeable BIM model supplemented by non-destructive pavement survey data, such as Ground Penetrating Radar (GPR) and Mobile Laser Scanner (MLS) data, and satellite Remote Sensing information (i.e. InSAR). The main goal of the research is to contribute to the state-of-the-art knowledge on BIM applications, by testing an infrastructure management platform capable of minimizing, or in some cases totally removing, the limitations typically related to the separate observation of these assessments to the advantage of an integrated analysis including both the design information and the routinely updated results of monitoring activities. As a test to the proposed methodology, an experimental activity was conducted over a real highway infrastructure, that was parallelly inspected by GPR, MLS and InSAR. To the purpose of the study, the raw dataset from the three surveys were separately processed, scaled and converted into suitable file formats to be more rapidly implemented into the BIM environment. As a result, the synergistic use of geometric and design information with the results from monitoring activities allowed the definition of a Digital Twin Model of the investigated road infrastructure, which can be progressively updated at each new survey, thereby permitting to detect pavement distresses and to control their evolution over time, while being aware of the effect of any delay in maintenance activities. Preliminary results have shown promising viability of the data management model for supporting asset managers in the various management phases, thereby proving this methodology to be worthy for implementation in Pavement Management Systems (PMS)

Advances in data processing and the availability of large datasets from very high-resolution (VHR) SAR satellite missions are promoting the use of multi-temporal InSAR techniques for the near-real-time assessment and the health monitoring of bridges and transport infrastructures. On the other hand, the Ground-Penetrating Radar (GPR) is a Non-destructive technology widely applied to monitor the internal state of infrastructure asset by rapid electromagnetic inspections. This research aims to investigate the viability of a novel Non-Destructive Health-Monitoring Approach (ND-HMA) based on the synergistic use of satellite remote sensing and GPR techniques for structural assessment of bridges and the prevention of damages induced by structural subsidence. The analyses were developed to identify and detect structural displacements of the Olivieri Bridge, located in Salerno, Italy. To this purpose, commercial VHR COSMO-SkyMed (CSK) products, provided by the Italian Space Agency (ASI), were acquired and processed by persistent scatterers (PS) InSAR technique. The historical time-series of deformations of the scatterers, found in correspondence of critical structural elements of the structure (i.e., bridge piers and arcs), were analyzed. Furthermore, in-situ GPR inspection analysis were carried out by using multi-frequency GPR systems equipped with both air-launched and ground-coupled antennas with central frequency ranging between 200 MHz and 1000 MHz. The implementation of the integrated approach provides a technologically enhanced and reliable mechanism for the provision of "early warning" information to be more rapidly processed and conclusively actioned by asset owners and management agencies. In particular, a novel data interpretation approach is proposed based on the selection of several PS data-points with coherent deformation trends on the bridge and the analysis of GPR outputs. The outcomes of this study demonstrate that multi-temporal InSAR remote sensing techniques can be applied to complement non-destructive ground-based analyses (e.g., ground-penetrating radars), thereby paving the way for integrated approaches in the smart monitoring of infrastructure assets.

In recent years, successful applications of the Synthetic Aperture Radar Interferometry (InSAR) for the monitoring of subsidence and deformations in transport infrastructures have been reported in the literature. The main advantage of this technique compared to other non-destructive surveying methodologies is in the possibility to perform fast network-level surveys as well as the provision of time-series of the displacements by multi-temporal data acquisitions. Given the medium ground resolution, C-band imagery are usually not employed for transport infrastructure monitoring as it is considered unlikely to obtain sufficiently accurate information. However, the use of medium resolution SAR data has not been thoroughly investigated until now and is still an open challenge. This study presents a novel approach for transport assets monitoring, based on the synergistic use of medium resolution (C-Band) and high resolution (X-Band) SAR imagery. To this effect, a multi-temporal SAR Interferometry analysis of high and medium-resolution datasets is performed on a runway of the Leonardo Da Vinci Airport in Rome, Italy. The data were acquired by the Sentinel-1A and the COSMO-SkyMed missions, respectively. A comparison between the results from medium and high-resolution datasets demonstrates the viability of using multi-frequency SAR imagery, and pave the way to the development of new methodologies for the monitoring of transport infrastructures. © 2021 IEEE

Satellite Remote-Sensing has been successfully applied for detection of natural-hazards, (e.g. seismic events, landslides and subsidence) and transport infrastructure monitoring over the last few years. Persistent Scatterer SAR Interferometry (PSI), is a satellite remote sensing technique able to measure ground displacements over the time. More specifically, the PSI technique is an evolution of the DInSAR technique and it is based on a statistical multi-temporal differential interferogram analysis. This allows to determine coherent stable-pixels over a data-stack of SAR images, in order to identify potential ground displacements. This study aims at demonstrating the potential of the PSI technique as an innovative health-monitoring methodology for the structural integrity of bridges. For this purpose, X‐Band COSMO‐SkyMed images provided by the Italian Space Agency (ASI) were acquired and processed in order to detect structural displacements of the Rochester Bridge in Rochester, UK. Outcomes of this investigation outlined the presence of various PSs over the inspected bridge, which were proven useful to achieve a more comprehensive monitoring methodology and to assess the structural integrity of the bridge. This research paves the way for the development of a novel interpretation approach relying on the integration between remote-sensing technologies and on-site surveys to improve upon current maintenance strategies for bridges and transport assets.

Persistent Scatterer Interferometry (PSI) is an Interferometric Synthetic Aperture Radar (InSAR) remote sensing technique based on a multi-temporal interferogram analysis of SAR images. The aim of the technique is to extract long-term high phase stability benchmarks of coherent point targets, namely Persistent Scatterers (PSs). In the last few years, several approaches have been developed to obtain PSI point targets, proving their viability for applications to transport infrastructure monitoring and surveillance. However, SAR satellites can only detect displacements in the Line-of-Sight (LoS), with reference to the specific orbit-related incident angle. This work proposes a novel geo-statistical approach to ease the post-processing of large datasets of PSs resulting from the application of the PSI algorithms over an area of interest. The approach aims at correcting the component of the displacement collected from the acquisition geometry of the sensor.