Δημοσιεύσεις έργου

Chatzistelios, G., Dermitzakis Em., Konstantinidou M., Kirytopoulos, K., (2022), “Increasing the quality of road infrastructure through systemic approach in safety management”, ESREL 2022

The value of road infrastructure is greatly appreciated in contemporary cultures and lives. Such infrastructure binds communities together by facilitating communication and commerce. Their acceptance and use are now widespread across the world. Road tunnels are critical road infrastructure elements because they increase transportation flow inside metropolitan areas, allow for crossing high terrain, and reduce the environmental impact, travel time, and transportation costs (Kirytopoulos et al., 2020). According to Santos et al. (2017), one of the most significant parameters for evaluating the quality of roadway operators is safety. The purpose of this paper is to propose a framework on enhancing the quality of highway services through increased and systemic approach for safety issues. The present study is focusing on a very specific and critical element of the road infrastructure, that is tunnels.

M. Konstantinidou, G. Sisias, S. Kontogiannis, (2022), “An ADR vehicles recognition tool for the prevention of emergency situations in tunnels”, Proceedings of the International Conference on Planning, Challenges of Disaster Management and Resilience (ICPCDMR).

Undoubtedly, fire accident events are the greatest threat to road tunnel systems. Destructive experiences such as the Mont Blanc fire in France or the fire in Yanhou China are only indicative of the severity of such incidents. Past tunnel fire accidents have shown that apart from the thermal radiation effects, the toxic effects of the trapped fire smoke inside the tunnel in combination with the increased deploying temperatures result in a high number of fatalities amongst the tunnel trapped users. Safety management with respect to dangerous goods transportation primarily aims at reducing the frequency of fire accidents. The importance of the information that the tunnel operators are receiving in case of a fire accident is crucial; operators should be informed as soon as possible about the specific characteristics of the particular fire incident in order to take the appropriate actions. One of the fundamental information about the accident and the fire progression is the substance that is involved in it. This paper describes the development of an automated tool to identify and recognize ADR vehicles before they enter tunnels. This tool is as a software component interfaced to a Resources Management System developed in parallel and validated by a road operator. The overall goal of this ADR detection tool is to efficiently record, statistically visualize and therefore manage the motorway passage of vehicles carrying dangerous goods from tunnels. In this way by tracking the vehicles before they enter a tunnel the substances can be controlled over time, thus minimizing the risk of a potential accident.

Full article here. Video of presentation can be found here.

Konstandinidou M., Sisias G., Kontogiannis S., (2021), “Development of a Proactive Tool for Dangerous Goods Management in Tunnels”, Proceedings of the 31st European Safety and Reliability Conference, ESREL 2021.

As a rule, tunnels are considered safe road infrastructures. Nevertheless, when an accident occurs inside a tunnel it can maximize its impact and casualties due to its constrained space of occurring events. Undoubtedly, fire accident events are the greatest threat to road tunnel systems and destructive experiences such as the Mont Blanc fire in France (1999) or the fire in Yanhou, China (2014) are indicative of the severity of such incidents. The use of automated deep learning and data mining algorithms that can provide accurate detection, frequency patterns and concentration predictions of dangerous goods passing through tunnels, is a significant fire incident restriction factor. To achieve automated detection, a post processing image detection tool has been developed, that identifies and marks the passage of dangerous goods through tunnels. This tool receives input from toll camera images and offers timely information of vehicles carrying dangerous goods, since such vehicles are signalled with a proper ADR label number (ADR vehicles). Knowing the exact number of ADR vehicles along with their carrying substance at any particular time, followed by classification and associated rules to fire incident occurrences, can lead to an effective management of the passage of such vehicles and consequently to an effective preventive management of fire incidents in tunnels.

Full article here.

Kontogiannis S., Kastellos, A., Kokkonis, G. & Gkamas, T. 2021, "Driving Speed Estimation and Trapped Drivers’ Detection inside Tunnels Using Distributed MIMO Bluetooth Devices", Electronics, 2022, 11(2), 265.

Accidents in highway tunnels involving trucks carrying flammable cargoes can be dangerous, needing immediate confrontation to detect and safely evacuate the trapped people to lead them to the safety exits. Unfortunately, existing sensing technologies fail to detect and track trapped persons or moving vehicles inside tunnels in such an environment. This paper presents a distributed Bluetooth system architecture that uses detection equipment following a MIMO approach. The proposed equipment uses two long-range Bluetooth and one BLE transponder to locate vehicles and trapped people in motorway tunnels. Moreover, the detector’s parts and distributed architecture are analytically described, along with interfacing with the authors’ resources management system implementation. Furthermore, the authors also propose a speed detection process, based on classifier training, using RSSI input and speed calculations from the tunnel inductive loops as output, instead of the Friis equation with Kalman filtering steps. The proposed detector was experimentally placed at the Votonosi tunnel of the EGNATIA motorway in Greece, and its detection functionality was validated. Finally, the detector classification process accuracy is evaluated using feedback from the existing tunnel inductive loop detectors. According to the evaluation process, classifiers based on decision trees or random forests achieve the highest accuracy.

Full article here: 265

Kontogiannis S., Konstantinidou, M., Kastellos, A., Kokkonis, G., Gkamas, T. & Pikridas, Ch. 2021, "Proposed Distributed System Architecture and Preliminary Measurements for the Detection of Trapped Individuals Inside Motorway Tunnels", IEEE 9th International Conference on Information, Communication and Networks (ICICN), Xi'an, China, 25-28 Nov. 2021.

This paper presents the architecture of a distributed system based on Bluetooth detectors for locating vehicles and people trapped in a motorway tunnel accident. The distributed architecture of the proposed system includes an automated dynamic way of adding or removing detectors from the system, a non-relational database for storing sensory measurements and an-easy-to-use graphical interface for displaying real-time or close to real-time detection information. The installation of the proposed system detectors is installed on the escape exits inside tunnels. The proposed system has been experimentally placed to both directions of a tunnel at the EGNATIA motorway in Greece and its functionality has been validated. Then, with the use of existing tunnel TMS inductive loop detectors, the accuracy of the detector measurements has been evaluated.

Full article here: ICICN

Kirytopoulos, K., Mourelatos, A., Chatzistelios, G., Ntzeremes, P. & Konstantinidou, M. 2021, " Employing serious games to increase safety in driving through road tunnels", Proceedings of the 31th European Safety and Reliability Conference, Anger, France, 19-23 September 2021.

Research has shown that tunnel safety is a matter of great importance. Recent studies have shown that, while driver behavior is one of the decisive factors in road tunnel accidents, drivers hardly receive proper education about the particularities of the tunnel environment, and they also exhibit deficiencies on how to deal with emergency situations inside a tunnel. As a means of tackling this challenge, the present research endeavor develops a software tool based on the concept of serious games, to educate and inform potential users on the specific rules and behavioral patterns that should govern driving through tunnels. To do so, the initial step was the determination of the basic instructions that a user must be familiar with, while driving through tunnels. The proper behavioral patterns were gathered from the relevant standards and guidelines and the specific needs for education have been explored through previous studies. Subsequently, the research proceeded with the development of an innovative tool for the purpose of users’ training, consisting of a game environment which simulates from a first-person perspective the task of driving through a tunnel. Within this environment various different scenarios were developed with the aim of evaluating the knowledge of users as well as educating them. The ultimate aim is to further increase safety within road tunnels, focusing on driver behavior as one of the most crucial parameters.

Full article here: ESREL 2021

Kontogiannis S. & Asiminidis, C. 2021, " Proposed Management System and Response Estimation Algorithm for Motorway Incidents", Energies, 14(10), 2736.

Motorway’s personnel tasks management and incidents monitoring, and response are critical processes that contribute to the motorway’s orderly and smooth operation. Existing management practices utilize SCADA technologies that control motorway actuator systems as well as various means of personnel communications mobile technologies. Nevertheless, contemporary motorways lack a unified incident response solution that tracks resources, sends notification alerts when necessary, and automates incident resolution. This paper presents a new holistic and unified management and response system called Resources Management System (RMS). This system was originally implemented as a generic motorways resources management system for the EGNATIA ODOS motorway that uses it in Greece. The implemented RMS provides real-time resources tracking, personnel utilization algorithms, and data mining capabilities towards incident confrontation. It operates as an incidents’ collection and resources central communication interface. It is also capable of incident response and completion time categorization; real-time tunnel exits sensory monitoring, staff mobilization, and tracking system. Furthermore, the RMS includes machine learning methodologies and smart agents (bots) for solving the problem of estimating and evaluating the response and completion time of incidents based on previous successful incidents’ confrontations.

Full article here: 2736

Konstantinidou M., Kazaras, K. & Kirytopoulos, K. 2020, "Human, Organizational Factors and Mental Workload for Tunnel Operators in Emergency Situations", Proceedings of the International Symposium on Human Mental Workload: Models and Applications, Springer, Cham, Granada, Spain, December 3–5.

Accident rates appear to be slightly lower in tunnels than on open road, however an accident in a tunnel may have much greater impact; especially in the event of fire, where the enclosed space hinders the dissipation of smoke and poses difficulty in ensuring safe escape route of the tunnel users. In order to assess the risk of such events that may cause heavy losses as well as serious damage to the tunnel infrastructure and facilities, it is crucial to focus on the key elements that constitute the road tunnel system. Taking into account that the road tunnel operator’s performance is of utmost importance for the overall safety of these critical infrastructures, this paper examines the cognitive overload that may occur during emergency situations. The analysis reveals that the main factors that have a substantial effect on the mental effort of the tunnel operator are the level of information processing, the available time to complete the necessary tasks and the number of switches the operator has to make between different task-sets. In order to improve the operator’s performance and reduce the mental workload in this safety critical domain of the transportation system, various performance shaping mechanisms are analyzed in a holistic and systemic perspective.

Full proceedings here: H - WORKLOAD 2020

Asiminidis C., Kokkonis, G. & Kontogiannis, S. "BLE Sniffing for Crowd Sensing and Directionality Scanning of Mobile Devices Inside Tunnels," 2020 3rd World Symposium on Communication Engineering (WSCE), Thessaloniki, 2020, pp. 54-58, doi: 10.1109/WSCE51339.2020.9275574..

With the predominance of individual Bluetooth gadgets, smartphone user’s security and privacy have been an expanding concern. Until now, Bluetooth traffic sniffing has been regarded as a complex errand because of Bluetooth’s indiscoverable mode and adaptive hopping behavior. This paper presents a novel BLE Scanning system for motorway tunnels which its goal is to use Bluetooth Sniffing, guide and show the emergency exit receiving the RSSI values from users’ smartphones and thus, find the directionality of the users in real time, in case of an emergency in a tunnel. In addition, the authors proposed BLE Scanning system and presented the preliminary results that have been carried out in a tunnel in the largest motorway in Greece, named EGNATIA ODOS.

Full proceedings here: WSCE

Kirytopoulos, K., Ntzeremes, P., Chatzistelios, G., Saramourtsis, A., Tsantsanoglou, A. & Konstantinidou, M. 2020, "How much do Greek drivers know about safety when driving through road tunnels?", in Francesco Di Maio, Pierro Baraldi and Enrico Zio (eds), Proceedings of the 30th European Safety and Reliability Conference (ESREL 2020), European Safety and Reliability Association, Research Publishing, Hannover, Germany, November 1–6.

The influence of infrastructure on driver behavior should be primarily examined for enhancing the level of road safety due to its impact on a significant number of accidents. Since tunnels are critical road infrastructure elements, they have to be at the forefront. Greece particularly has one of the highest number of deaths with 76 deaths per million inhabitants while the European average is 50. Meanwhile, Greece possesses the fourth place within the EU based on the number of road tunnels longer than 500m. Therefore, this survey aims at exploring road tunnel drivers' behavioral intentions in Greece. To do so, a questionnaire survey is conducted through which 306 responses are collected and analyzed. Initially, users' driving behavior is investigated in order to compare potential divergences between tunnels and open roads. Special emphasis is given in comparing respondents behaviors with the behavior of other drivers around them. Subsequently, the perceptions that affect users' driving behavior are investigated such as their perceived risk and control when passing through tunnels or their comparative optimism. Finally, the survey explores potential users' lack of education in dealing with emergency situations and how this issue impacts on their driving behavior. By investigating and recording drivers' concerns, this paper provides important information that can be deployed by tunnel managers and safety analysts in applying adequate safety measures and designing relevant information campaigns.

Full proceedings here: https://www.rpsonline.com.sg/proceedings/esrel2020/pdf/4108.pdf

Sisias G., Kontogiannis, S., Konstantinidou, M. & Dossis, M. 2020. "Preliminary results of a proposed CNN framework for use in motorway applicable detection systems", Proceedings of the 5th South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM 2020), Corfu, Greece, September 25–27.

This paper presents the preliminary results of theThis paper presents the preliminary results of thefirst stage of a proposed framework of existing image detectionconvolutional algorithms, and sets the image portable detector requirements,focusing on portable detection devices. Such devicesperform image segmentation and transmit monitoring meta-data.Four pre-trained CNNs have been used to classify images ofvehicles passing through toll posts, and the results are presentedand compared. At subsequent stages of the presented frameworkcertain types of vehicles will be detected and categorized, basedon the type of cargo they carry.The proposed framework is wrapped by an appropriatesystem architecture which interacts with incident responseor facility management systems, and tries to achieve precisespeed/memory/accuracy balance for each targeted detection applicationaccordingly. To this end, various ways are investigatedand evaluated, to trade accuracy for speed and memory usage inmodern mobile convolutional algorithm driven detection systemsmonitoring specific regions of interest. Such tradeoffs provideincreased detection capabilities to incident response systems thatinteract with such detectors in real-time, or in post-processingwith facility management systems for accurate and automateddecisions adaptation.

Full proceedings here: To be Published

Ntzeremes, P., Kirytopoulos, K. & Leopoulos, V. 2020. "Discussing the need to manage uncertainty relating to users in road tunnel fire risk assessment", Journal of Risk Analysis and Crisis Response, 10(1), 12 - 18.

Although tunnels provide roads with numerous advantages, they also include significant risks. Especially, fire accidents are the biggest threats. Nowadays, risk assessment has the predominant role for managing tunnel fire safety and users are in the centre of attention. However, existing methods exhibit lack in treating uncertainty stemming from users. This paper aims to discuss current ways of representing tunnel users’ uncertainty as well as to introduce the importance of distinguishing these representations in the wider context of risk assessment.

Full article: https://www.atlantis-press.com/journals/jracr/125940112

Ntzeremes, P., Kirytopoulos, K. & Leopoulos, V. 2019. "Developing a risk-based method for predicting the severity of fire accidents in road tunnels", Risk Analysis Based on Data and Crisis Response Beyond Knowledge: in Chongfu Huang & Zoe S. Nivolianitou Proceedings of the 7th International Conference on Risk Analysis and Crisis Response (RACR 2019), Athens, Greece, October 15-19, 518-525, CRC Press.

Fire accidents are considered serious events for tunnel safety since they can cause heavy losses as well as serious damage to the tunnel infrastructure and facilities. Although risk assessment prepares the tunnel system to deal with potential fire accidents, an adequate response by tunnel operators depends also on the information about a particular fire event. This paper propos-es a novel risk-based method that supports tunnel operators in assessing the criticality of potential fire events. The structure of the proposed method is as follows. Initially, the factors that determine the criticality of a fire event are featured and the system parameters that affect these factors are identified. Subsequently, the method performs multiple simulations by changing the examined parameters randomly and thus the relation between the factors and the parameters arises. The outcome facilitates tunnel operators to predict promptly the severity of potential fire events and make better-informed decisions.

Full proceedings here: https://www.taylorfrancis.com/books/e/9780429286346/chapters/10.1201/9780429286346-74

Το 7ο Διεθνές Συνέδριο για την Ανάλυση Κινδύνου και την Αντιμετώπιση Κρίσεων (Risk Analysis & Crisis Response, RACR-2019) πραγματοποιήθηκε στην Αθήνα στις 15-19 Οκτωβρίου 2019. Το γενικό θέμα του συνεδρίου που φιλοξενήθηκε Εθνικό Κέντρο Έρευνας και Φυσικών Επιστημών "Δημόκριτος" (Ε.Κ.Ε.Φ.Ε. "Δ") αφορούσε την Ανάλυση Κινδύνου με βάση τα δεδομένα και την Αντιμετώπιση Κρίσεων πέρα από τη γνώση, τονίζοντας την επιστήμη και την τεχνολογία για τη βελτίωση των δυνατοτήτων ανάλυσης κινδύνου και τη βελτιστοποίηση της στρατηγικής αντιμετώπισης κρίσεων.

Στα πλαίσια του έργου ΟΔΟΣ και του παραδοτέου της ενότητας 1.2 το ΕΜΠ παρουσίασε τα αποτελέσματα της έρευνας σχετικά με μια νέα μέθοδο που βασίζεται στον κίνδυνο και υποστηρίζει το κέντρο λειτουργίας της σήραγγας στην αξιολόγηση της κρισιμότητας πιθανών ατυχημάτων πυρκαγιών.

Asiminidis, C., Kontogiannis, S., Kokkonis, G., Zinas, N. & Papadopoulos, C. 2019. "Mass notification for public safety: Current status and Technical Challenges" Risk Analysis Based on Data and Crisis Response Beyond Knowledge: in Chongfu Huang & Zoe S. Nivolianitou Proceedings of the 7th International Conference on Risk Analysis and Crisis Response (RACR 2019), Athens, Greece, October 15-19, 211-216, CRC Press.

Critical and emergency incidents often lead to asset, infrastructure and human loss, all major concerns for companies, organizations and governments. Early prediction, emergency management plans and immediate dissemination of information can mitigate such events from occurring. To this end, early warning systems have been deployed. Early warning systems comprise of sensors, event detection and decision subsystems that work together to forecast the occurrence of possible incidents. These forecasts are then processed by a mass notification system for the dissemination of public alert guidelines and coordinated emergency group actions. While these systems reduce risks and enable authorities’ coordination, their deployment often fails to offer timely alerts specifically in case of incidents affecting a massive number of participants. This study presents existing notification systems, their minimum requirements and technical challenges for large scale deployments. Furthermore it proposes a high level architecture and required features for a mass notification system which focuses on public safety and protection of life and property on a large scale.nt System.

Full proceedings here: https://www.taylorfrancis.com/books/e/9780429286346/chapters/10.1201/9780429286346-30

Στα πλαίσια του έργου ΟΔΟΣ και του παραδοτέου της ενότητας 2.5 το ΠΙ-ΜΑΘ παρουσίασε τα αποτελέσματα της έρευνας σχετικά την τρέχουσα κατάσταση και τις τεχνικές προκλήσεις της μαζικής ειδοποίησης σε έκτακτα συμβάντα.

Zeeri, M.O., Kirytopoulos, K. & Ntzeremes, P. 2019, "Exploring road tunnel drivers' behavior: The case of Greece", in Michael Beer and Enrico Zio (eds), Proceedings of the 29th European Safety and Reliability Conference (ESREL 2019), European Safety and Reliability Association, Research Publishing, Hannover, Germany, September 23–26, pp. 253-260.

Full proceedings here: http://itekcmsonline.com/rps2prod/esrel2019/e-proceedings/index.html

Στα πλαίσια του έργου ΟΔΟΣ και του παραδοτέου της ενότητας 2.1 το ΕΜΠ εξέτασε μέσω ερωτηματολογίου τη συμπεριφορά των Ελλήνων οδηγών κατά τη διέλευσή τους σε οδικές σήραγγες. Τα αποτελέσματα δημοσιέυτηκαν στο Ευρωπαϊκό συνέδριο ασφάλειας και αξιοπιστίας (ESREL) που διεξήχθει για το 2019 στο πανεπιστήμιο του Αννόβερο.

Ch. Asiminidis, I. Georgiadis, D. Syndoukas, G. Kokkonis and S. Kontogiannis, Performance evaluation on encrypted-non encrypted database fields containing IoT data, In Proc. Of the 23th International Database Engineering & Applications Symposium, Athens, 2019, ACM proceedings, presented May 2019, Harokopio University, Athens, Greece

IDEAS scope

The annual IDEAS conference is a top international forum for data engineering researchers, practitioners, developers, and application users to explore revolutionary ideas and results, and to exchange techniques, tools, and experiences. We invite participation of all interested in this meeting which provides an insight into original research contributions relating to all aspects of database engineering defined broadly, and particularly topics of emerging interest describing work on integrating new technologies into products and applications, on experiences with existing and novel techniques, and on the identification of unsolved challenges.

Στα πλαίσια του έργου ΟΔΟΣ και του παραδοτέου της ενότητας 2.5 το ΠΙ-ΜΑΘ εξέτασε τη δυνατότητα -απόδοση της βάσης δεδομένων postgreSQL του Συστήματος Διαχείρισης Πόρων για τη Διαχείριση του προσωπικού της Εγνατίας καθώς και την δυνατότητα χρήσης της ως Βάσης για τη συλλογή μετρήσεων από τους αισθητήρες του αυτοκινητοδρόμου μέσω της υπηρεσίας συλλογής μετρήσεων του Συστήματος Διαχείρισης Πόρων.

Within the framework of the HMRT project and the deliverable 2.5, the UOI-MATH performed a thorough evaluation of the postgreSQL database service used by the Resource Management System(deliverable 1.2) for the Management of the Egnatia motorway personnel as well as its potential use as a data collection service for the collection of measurements of the EGNATIA motorway sensors throught the Measurement Collection Service of the HMRT Resource Management System.