Safety-related Applications Research Articles

Contributions to the development of safe and accurate localisation solutions: The LOCSP project

GNSS are now in everybody's pocket, embedded in our smartphones and is widely used for informative uses (navigation, leisure…). In future transportation modes, and in particular autonomous vehicles or for safety related railways applications, localisation needs to be accurate and/or safe and trustful. In many of the environments crossed by users, satellite signal propagation is disturbed by buildings, trees or other obstacles that degrade performance. To contribute to the development of safe and accurate localisation solutions in these environments, the LOCSP project intends to evaluate and compare past algorithms on a new shared database but also focuses on the development of two research proposals: through cooperative vehicle localisation using artificial intelligence and with interference mitigation. This paper aims to introduce the project and the first results on these two axes.

A Novel V2V-Based Temporary Warning Network for Safety Message Dissemination in Urban Environments

Vehicular communication networks (VCNs) have been widely recognized as promising solutions to support safety-related applications in urban transportation systems. However, constructing and maintaining such networks is quite challenging due to the complex traffic and communication environment. Substantial studies have focused on the design of the networking schemes and message dissemination protocols. Nonetheless, most existing designs only consider the connectivity and rapid end-to-end transmission, regardless of the network coverage and duration. In this article, we propose a novel temporary warning network (TWN) for safety message dissemination in the urban traffic environment, in which both the spatial distribution and temporal duration of the networking scheme are taken into account. Specifically, TWN is constructed by the selection of relay vehicles based on the spatiotemporal correlation of vehicle trajectory so that the safety message can be quickly disseminated within the Regions of Interest (RoIs). To maintain TWN during an accident, a reselection mechanism is also proposed, which enables newly come vehicles in the RoI to receive the messages in time. Finally, we conduct extensive numerical experiments to validate the effectiveness of our method in various traffic scenarios.

A Tightly Coupled Integration Approach for Cooperative Positioning Enhancement in DSRC Vehicular Networks

Intelligent transportation system significantly relies on accurate positioning information of land vehicles for both safety and non-safety related applications, such as hard-braking ahead warning and red-light violation warning. However, existing Global Navigation Satellite System (GNSS) based solutions suffer from positioning performance degradation in challenging environments, such as urban canyons and tunnels. In this paper, we focus on the positioning performance enhancement of land vehicles via cooperative positioning under a partial GNSS environment in a Vehicular Ad-hoc NETwork (VANET). The availability of Time-of-Flight (ToF) based inter-vehicle or vehicle-to-infrastructure ranges is verified via 5.9 GHz Dedicated Short-Range Communication (DSRC) vehicle-to-everything communication with RTS/CTS unicast mechanism. An inertial navigation sensor aided, tightly coupled integration approach for land vehicle cooperative positioning using DSRC ToF ranges and carrier frequency offset range-rates is proposed, where a digital map is used to constrain the position estimates. If available, the GNSS pseudorange and Doppler shift under partial GNSS environment can also be incorporated. A Rao–Blackwellized particle filter is utilized to estimate the unknown variables allowing for reduced computational complexity in comparison with the conventional particle filter. The posterior Cramer–Rao lower bound is also derived to give a theoretical performance guideline. Both simulation and experimental results show the validity of our proposed approach.

Automated avalanche mapping from SPOT 6/7 satellite imagery with deep learning: results, evaluation, potential and limitations

Abstract. Spatially dense and continuous information on avalanche occurrences is crucial for numerous safety-related applications such as avalanche warning, hazard zoning, hazard mitigation measures, forestry, risk management and numerical simulations. This information is today still collected in a non-systematic way by observers in the field. Current research has explored the application of remote sensing technology to fill this information gap by providing spatially continuous information on avalanche occurrences over large regions. Previous investigations have confirmed the high potential of avalanche mapping from remotely sensed imagery to complement existing databases. Currently, the bottleneck for fast data provision from optical data is the time-consuming manual mapping. In our study we deploy a slightly adapted DeepLabV3+, a state-of-the-art deep learning model, to automatically identify and map avalanches in SPOT 6/7 imagery from 24 January 2018 and 16 January 2019. We relied on 24 778 manually annotated avalanche polygons split into geographically disjointed regions for training, validating and testing. Additionally, we investigate generalization ability by testing our best model configuration on SPOT 6/7 data from 6 January 2018 and comparing it to avalanches we manually annotated for that purpose. To assess the quality of the model results, we investigate the probability of detection (POD), the positive predictive value (PPV) and the F1 score. Additionally, we assessed the reproducibility of manually annotated avalanches in a small subset of our data. We achieved an average POD of 0.610, PPV of 0.668 and an F1 score of 0.625 in our test areas and found an F1 score in the same range for avalanche outlines annotated by different experts. Our model and approach are an important step towards a fast and comprehensive documentation of avalanche periods from optical satellite imagery in the future, complementing existing avalanche databases. This will have a large impact on safety-related applications, making mountain regions safer.

Analysis of thermocouple-based finger contact temperature measurements

The understanding of heat conduction during finger contact with cooler or hotter objects is important for designing many electronic devices and for setting safety standards in a variety of occupational settings. In the most common experimental approach to study this process, a micro-thermocouple is placed at the finger-object interface. However, the interpretation of what this measurement corresponds to is not clear. To this end, we develop a three-dimensional thermal simulation of the finger-thermocouple-substrate configuration. The model predictions match finger cooling measurements in eight distinct cases available in prior literature (finger pressed with 1 N or 9.8 N against a steel or an aluminum substrate held at −2 °C or −10 °C). We demonstrate that the thermocouple can be represented accurately as a truncated sphere with emerging cylindrical wires while a multilayer block model of the finger provides similar results to an anatomically representative model. Our simulations show that in the eight previously studied cooling cases, the average surface temperature of skin that is in contact with the substrate follows nearly the same but offset cooling trend as the thermocouple tip temperature. The value of the offset is predominantly determined by the substrate material, with the thermocouple tip temperature being lower than the average skin surface temperature by 1–5 °C and 3–10 °C for steel and aluminum substrate cases, respectively. This temperature difference results in a moderate to an extreme thermocouple underprediction of the time necessary for the skin surface to reach the experimental safety threshold of 1 °C. Consequently, from the perspective of the safety related applications the thermocouple measurement provides a conservative limit on the contact duration and thereby is suitable for such purposes, but for applications requiring accurate skin temperature measurements alternative experimental approaches should be used.

Adaptive and Optimized Control Channel Utilization in Vehicular Ad Hoc Networks

Vehicular ad hoc networks (VANETs) are counted as a state-of-art technology which can be considered to provide reliable communication which is increase the safety and convenience of drivers in the road. Due to channel congestion occurrence in both highway and urban scenario, many VANET’s safety applications face degradation in their quality of service especially in a high-density environment. To improve the performance, reliability, and safety of VANETs, message overhead on the standard wireless channel dedicated short-range communications (DSRC) should be alleviated to guarantee safety-related applications. To this end, this paper proposes an approach to optimize the utilization of the control channel (CCH) and make the control channel interval (CCHI) adaptive to the emergency cases in the vehicular scenarios. More precisely, when there is an emergency cases, a part of service channel interval (SCHI) is exploited to ensure the guarantee of emergency message delivery. When a vehicle intended to transmit the safety message to the surround vehicles, the proposed method granted that CCH is allocated to meet the traffic safety demands; then, the safety messages disseminate properly to the transmission range. A part of the service channel interval (SCHI) is exploited to ensure the guarantee of emergency message delivery, Then, applying the laying chicken algorithm (LCA) to solve the derived CCH optimized utilization. Finally, extensive simulations are carried out to validate the proposed optimized CCH utilization. To validate the performance of the proposed adaptive congestion control approach (ACCA), we used the network simulator Ns-3 [35] to simulate the vehicle’s environment, after generating vehicles’ mobility traces of the nodes using the network simulator for urban mobility (SUMO) with OpenStreetMap (OSM). The simulation indicates that our congestion algorithm (ACCA) performs better service quality than other existing algorithms. We got a better network connection regarding safety messages, beacon rate with time, and packet length for different vehicles’ densities.

An Efficient Certificateless Ring Signcryption Scheme With Conditional Privacy-Preserving in VANETs

As an ever-increasing ingredient of intelligent transportation systems, vehicular ad hoc networks (VANETs) can be leveraged to improve road safety and driving convenience. However, the extreme mobility and volatility of VANETs can arouse serious concerns about vehicle identity privacy leakages as well as the authenticity and confidentiality of safety messages in vehicular communication. To cope with these issues, we propose a certificateless ring signcryption scheme with conditional privacy-preserving based on elliptic curve cryptography, which can provide secure vehicular communication with low transmission latency and communication overhead. Besides, by integrating a tracking mark into the safety message, we design a tracking algorithm that enables the trusted party to distinguish malicious vehicles from the ring member list. It realizes conditional privacy while avoiding the huge cost of vehicular storage resources. Through security analysis, this scheme is proven to be secure under the Elliptic curve discrete logarithm and Elliptic curve computational Diffie–Hellman assumptions in the random oracle model. Finally, we implement the performance evaluations in terms of the computational overhead, the communication bandwidth and the packet loss rate. By utilizing the MIRACL cryptography library and the Veins simulation framework, the results illustrate that the proposed scheme can support an efficient and highly reliable communication protocol for safety-related applications in VANETs environment.

Approach towards qualification of TCP/IP network components of PFBR

Distributed control system architecture is adopted for I&C systems of Prototype Fast Breeder Reactor, where the geographically distributed control systems are connected to centralized servers & display stations via switched Ethernet networks. TCP/IP communication plays a significant role in the successful operations of this architecture. The communication tasks at control nodes are taken care by TCP/IP offload modules; local area switched network is realized using layer-2/3 switches, which are finally connected to network interfaces of centralized servers & display stations. Safety, security, reliability, and fault tolerance of control systems used for safety-related applications of nuclear power plants is ensured by indigenous design and qualification as per guidelines laid down by regulatory authorities. In the case of commercially available components, appropriate suitability analysis is required for getting the operation clearances from regulatory authorities. This paper details the proposed approach for the suitability analysis of TCP/IP communication nodes, including control systems at the field, network switches, and servers/display stations. Development of test platform using commercially available tools and diagnostics software engineered for control nodes/display stations are described. Each TCP link behavior with impaired packets and multiple traffic loads is described, followed by benchmarking of the network switch's routing characteristics and security features.

A Survey on Mobile Road Side Units in VANETs

The number of vehicles on the road increases daily, causing many fatal accidents and wasting much time for the average commuter every day due to congestion. Vehicular ad hoc networks (VANETs) were introduced to overcome these issues by enabling vehicle-to-vehicle communication and vehicle-to-infrastructure communication. The prime challenge in VANETs is the necessity of very low communication delays, especially for safety-related applications due to the high mobility nature of vehicles. The VANET architecture introduces a network component, the Road Side Unit (RSU), to meet the required delay limitations. Even though the RSU is a critical component in VANETs, as expected, the RSUs were not deployed throughout the world because of their high investment cost. As a solution, the idea of mobile RSU (mRSU) was introduced, and, ever since, several techniques of mRSU deployment strategies have been proposed. In this survey, we first analyze the importance of the RSU to the VANET architecture with real-world data incorporating the new 5G standard. Then, we investigate the research done in the areas of mRSU and exploit the pros and cons of each mRSU deployment strategy. Finally, we also discuss the future research directions of mRSU, and we explain the challenges connected to these future trends.

Simulation of Virtual Redundant Sensor Models for Safety-Related Applications.

Applications of safety-related control systems demand reliable and credible inputs from physical sensors, therefore there is a need to extend their capabilities to provide a validated input with high availability. Our main idea is to insert virtual sensors between physical sensors and the control system’s logic. The created solution can validate the values of real sensors and with the use of multiple virtual sensors we can achieve high availability in addition, therefore our solution is entitled as a virtual redundant sensor. It works by the digital twin’s concept and uses fusion function to calculate validated results. The fusion function is used to transform the measured values from the physical sensors according to designed numerical models. The selection of a numerical model with assigned fusion functions can be performed via the WEB-based graphical user interface. Proposal of the numerical model is created and validated on the experimental workplace with emulation of physical sensors and MQTT integration (smart IoT sensors). The results of testing have shown that our solution can be applied to validate the values of physical sensors. Proposed fusion functions calculated results according to the selected model in all cases, while non-standard cases were handled according to our definition. In addition, the high availability concept with a group of two virtual sensors has proven fast recovery and availability of results for safety-related applications as well.

Integrity Monitoring of PPP-RTK Positioning; Part I: GNSS-Based IM Procedure

Nowadays, integrity monitoring (IM) is required for diverse safety-related applications using intelligent transport systems (ITS). To ensure high availability for road transport users for in-lane positioning, a sub-meter horizontal protection level (HPL) is expected, which normally requires a much higher horizontal positioning precision of, e.g., a few centimeters. Precise point positioning-real-time kinematic (PPP-RTK) is a positioning method that could achieve high accuracy without long convergence time and strong dependency on nearby infrastructure. As the first part of a series of papers, this contribution proposes an IM strategy for multi-constellation PPP-RTK positioning based on global navigation satellite system (GNSS) signals. It analytically studies the form of the variance-covariance (V-C) matrix of ionosphere interpolation errors for both accuracy and integrity purposes, which considers the processing noise, the ionosphere activities and the network scale. In addition, this contribution analyzes the impacts of diverse factors on the size and convergence of the HPLs, including the user multipath environment, the ionosphere activity, the network scale and the horizontal probability of misleading information (PMI). It is found that the user multipath environment generally has the largest influence on the size of the converged HPLs, while the ionosphere interpolation and the multipath environments have joint impacts on the convergence of the HPL. Making use of 1 Hz data of Global Positioning System (GPS)/Galileo/Beidou Navigation Satellite System (BDS) signals on L1 and L5 frequencies, for small- to mid-scaled networks, under nominal multipath environments and for a horizontal PMI down to 2×10−6, the ambiguity-float HPLs can converge to 1.5 m within or around 50 epochs under quiet to medium ionosphere activities. Under nominal multipath conditions for small- to mid-scaled networks, with the partial ambiguity resolution enabled, the HPLs can converge to 0.3 m within 10 epochs even under active ionosphere activities.

Adaptive Zone–Assisted Iterative Localization in Energy-Efficient Wireless Sensor Networks

In the public safety-related applications which use wireless sensor networks (WSNs) to estimate a target’s location, identifying the most effective search zone in which the target is located can reduce computational complexity and shorten the response time. We formulated a threshold-based scheme that only uses binary reports from sensors to identify the most effective search zone. This scheme requires no <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> information regarding statistics on the sensor’s decision preference. Based on this scheme, we developed an adaptive zone–assisted iterative localization (AZ-IL) scheme. Compared with existing iterative localization schemes, our scheme can reduce the computational complexity of localization processes and maintain the localization performance in energy-efficient WSNs, in which some sensors are placed in sleep mode.

What about Using Photovoice for Health and Safety?

The positive reception of Wang and Burris’ photovoice method, published in 1997, has led to a proliferation of ways in which professionals deploy photovoice in a widening range of application fields, e.g., public health, social development and phenomenological research of human experiences. A scoping review method is used to obtain an overview of current photovoice designs and of application examples in the health and safety domain. The results show a variety of method designs. Our findings indicate that all of the photovoice designs are composed from different combinations of eleven process steps. Five generic objectives cover the range of application examples found in our literature study. We therefore condensed the variety into five generic photovoice designs for: (a) communication, (b) education, (c) exploration, (d) awareness, and (e) empowerment purposes. We propose this for use in a classification system. The potential for application of these photovoice designs in safety management is illustrated by the existence of various safety related application examples. We argue that the five generic designs will facilitate the implementation and usage of photovoice as a tool. We recommend that both a theoretical framework and guidance are further developed. We conclude that photovoice holds potential for application in health and safety management.

Experimental Evaluation of IEEE 802.11p in High-Speed Trials for Safety-Related Applications

This paper presents and analyzes a test campaign's outcomes to assess the application-level performance of IEEE 802.11p at high speeds of up to 250 km/h. The main focus is on safety-related applications, but we also discuss performance figures resulting from additional tests performed to address other purposes that might use lower transmission powers. In particular, we investigate the impact that speed, transmission power, distance, and different degrees of congestion may have on application-level metrics such as TCP Goodput, UDP Goodput, RTT, Jitter, and Datagram/Packet Loss in real-world scenarios, and aim to find out which guarantees can be obtained in those environments with generic off-the-shelf equipment. Overall, the results indicate that IEEE 802.11p can satisfy safety-related requirements even as vehicles move with high velocity in heavily congested networks. For other kinds of applications, the performance might be compromised, especially under congestion, but figures attest that these networks may also serve additional purposes unanticipated when the standard was introduced.

Bats: An Appliance Safety Hazards Factors Detection Algorithm with an Improved Nonintrusive Load Disaggregation Method

In an electrical safe microenvironment, all kinds of electrical appliances can be operated safely to ensure the safety of life and property. The significance of safety hazard factors detection is to detect safety hazards in advance, to remind the administrators to exclude risk, to reduce the unnecessary loss, and to ensure that the electrical operation is healthy and orderly before the occurrence of accidents. In this paper, batteries are selected as the primary research subject of safety detection because batteries are used more and more in the Internet of Things (IOT), and they often cause fire in the process of discharging and charging. The existing algorithms need to be embedded into the specialized sensor for each important electrical appliance. However, they are limited by the actual deployment, so it is extremely difficult to spread widely. According to the opinions above, an improved load disaggregation algorithm based on dictionary learning and sparse coding with optimal dictionary matrix period is proposed to detect potential safety hazards of battery loads. For safety-related electrical applications, doing so can increase interpretability. Through experiments, we test this algorithm on the REDD dataset, and compare it with the baseline algorithms (combinatorial optimization, factorial hidden Markov model, basic discriminative dictionary sparse coding algorithm) to achieve a degree of trust. The Mean Absolute Error (MAE) value is 8.26, which drops by 70%. The Root Mean Square Error (RMSE) value is 97.75, which is also better than those baseline algorithms.

Strategical Approach for the Neutronics in the European Fusion Programme

One of the main aims of the European fusion programme is the design of a DEMOnstration fusion power plant (DEMO). The related work is conducted by the EUROfusion consortium and includes a strong supporting research and development programme. Support is also provided to the design of the high intense neutron source IFMIF-DONES (International Fusion Material Irradiation Facility-DEMO Oriented NEutron Source) to be built for the qualification of materials considered for DEMO. Neutronics plays a fundamental role for the design, operation, and safety of these facilities including the evaluation and verification of their nuclear performance. The lessons learned during the ITER design and construction phase point to the need to strengthen nuclear design integration already in the early DEMO design phase and establish an improved nuclear safety culture. This requires a coordinated approach for the neutronics that relies upon the availability of suitable computational procedures, tools, and data, qualified and validated for specific design- and safety-related applications. Accordingly, the approach builds on the development of advanced computation tools and the provision of high-quality nuclear data supported by integral experiments for their validation. Furthermore, configuration and requirement management principles ensure the alignment with the global nuclear design integration. This translates into appropriately chosen design margins and acceptance criteria, along with the specification of the nuclear analyses to be conducted in the various design phases. This paper presents the outlined approach as implemented in the EUROfusion Power Plant Physics and Technology (PPPT) programme and provides a strategical outlook of planned activities. This includes development works on advanced simulation tools with their application in various nuclear design- and safety-related analyses. The efforts to improve the nuclear database, in particular, with regard to radiation damage and activation cross-section data relevant to DEMO and DONES, are highlighted. Furthermore, the methodological approach applied to PPPT nuclear analyses including design, shielding, activation, and radiation dose calculations is discussed on the basis of specific examples.

Adaptive Clustering Algorithm for Stable Communication in Vanet

Clustering in VANET is important for recent days due to more number of vehicle present in urban area. In future Intelligent Transportation System (ITS), VANET is capable of providing safety related applications, Internet accessing and various user applications for drivers and passengers. Clustering based topology an efficient data interaction among vehicles, can be applied to the groups of vehicle nodes in geographical vicinity together that supports direct interaction between the intercluster data interaction through cluster heads (CHs). In existing method, so many algorithms developed Related to clustering based VANET communication, but due to high mobility of vehicle and their parameters like position, velocity and acceleration is improve the complexity and reduce the performance. In this research, we propose an adaptive self-learning approach based hybrid clustering. In hybrid clustering, the process divided in three steps. In first step Type1, it used for Road side unit (RSU) act as a static cluster head. In second step, divide the multiple zones with whole area and apply zone sensitive based clustering algorithm. It is used for predict the efficient centroid/weight value for each Vehicles. Finally in the third step, from the above algorithm, in neuro- fuzzy training samples we got. Neuro fuzzy prediction based cluster head selection was applied. Percentages of cluster-Head for each zone assign the purpose of reduces the end-to-end delay and reduce congestion. In simulation results shows that demonstrate the efficiency of proposed algorithm compare to existing method.

Towards Optimal Dissemination of Emergency Messages in Internet of Vehicles: A Dynamic Clustering-Based Approach

In this paper, we target dissemination issues of emergency messages in a highly dynamic Internet of Vehicles (IoV) network. IoV is emerging as a new class of vehicular networks to optimize road safety as well as users’ comfort. In such a context, forwarding emergency messages through vehicle-to-vehicle communications (V2V) plays a vital role in enabling road safety-related applications. For instance, when an accident occurs, forwarding such information in real time will help to avoid other accidents in addition to avoiding congestion of network traffic. Thus, dissemination of emergency information is a major concern. However, on the one hand, vehicle density has increased in the last decade which may lead to several issues including message collisions, broadcast storm, and the problem of hidden nodes. On the other hand, high mobility of vehicles and hence dynamic changes of network topology result in failure of dissemination of emergency packets. To overcome these problems, we propose a new dissemination scheme of emergency packets by vehicles equipped with both DSRC and cellular LTE wireless communication capabilities. Our scheme is based on a dynamic clustering strategy, which includes a new cluster head selection algorithm to deal with the broadcast storm problem. Furthermore, our selection algorithm enables not only the election of the most stable vehicles as cluster heads, and hence their exploitation in forwarding the emergency information, but also the avoidance of packet collisions. We simulated our scheme in an urban environment and compared it with other data dissemination schemes. Obtained results show the efficiency of our scheme in minimizing collision and broadcast storm problems, while improving latency, packet delivery ratio and data throughput, as compared to other schemes.

RPO-MAC: reciprocal Partially observable MAC protocol based on application-value-awareness in VANETs

Numerous safety-related applications have rigid requirements for the threshold of latency limitation of message transmissions to enhance safety and traffic efficiency of vehicles on the road in vehicular ad-hoc networks (VANETs). Consequently, a medium access control (MAC) protocol for reliable and fast transmission of safety messages should focus on the maximum transmission delay. Herein, we refer to the concept of packet value and integrate it with the latency of different messages determined by the waiting interval of packets in a queue. Subsequently, we propose a reciprocal revenue function, i.e., the transmission probability of the participants, by considering both its own benefit and the other nodes’ revenue. Additionally, an inter-vehicle cross-layer cooperative game model based on the local optimal utility of participants is constructed. We then theoretically prove the existence of an equilibrium using the partially observable Markov decision process (POMDP), and provide a specific approach for obtaining the channel access probability of a vehicle by using deep reinforcement learning. Finally, the analysis and simulation results in saturated and non-saturated data traffic conditions are presented to evaluate the performance of Reciprocal Partially Observable MAC Protocol (RPO-MAC) proposed in this paper and compare it with the IEEE 802.11p standard protocol. These comparisons demonstrate the advantages of our proposed reciprocal revenue game method in the case of channel network congestion, especially in terms of delay. It is shown that the RPO-MAC protocol can provide a strong support to delay-sensitive safety related applications.

On safety assessment of artificial intelligence

In this paper we discuss how systems with Artificial Intelligence (AI) can undergo safety assessment. This is relevant, if AI is used in safety related applications. Taking a deeper look into AI models, we show, that many models of artificial intelligence, in particular machine learning, are statistical models. Safety assessment would then have t o concentrate on the model that is used in AI, besides the normal assessment procedure. Part of the budget of dangerous random failures for the relevant safety integrity level needs to be used for the probabilistic faulty behavior of the AI system. We demonstrate our thoughts with a simple example and propose a research challenge that may be decisive for the use of AI in safety related systems.