rss_2.0Transport and Telecommunication Journal FeedSciendo RSS Feed for Transport and Telecommunication Journal and Telecommunication Journal Feed Traffic Safety in Existing and New Road Tunnels with the Novel NDBA Concrete Safety Barrier<abstract> <title style='display:none'>Abstract</title> <p>Two main elements are essential in terms of road traffic safety. The first element is accident prevention and the second is the minimization of accident severity once a crash has occurred. Concrete safety barriers have very good anti-collision performance against roadside obstacles, relatively modest construction and maintenance costs, and low dynamic deflection and therefore are widely used in tunnels. Thanks to their characteristic redirective profile these barriers can redirect errant vehicles into their original lane after collisions. However insufficient research has been done for increasing the performance of concrete barriers purposely designed for tunnel installations. This research presents the new “NDBA Tunnel” concrete safety barrier designed and constructed by the Italian Road Operator ANAS indicated to be installed in road tunnel sections for safety improvements. In Europe, road safety barriers must be designed in compliance with the European Standard EN 1317. Therefore, the barrier “NDBA Tunnel” was subject to the TB11 and TB81 full-scale crash tests according to the European EN 1317 regulation. The results prove the barrier's ability to absorb impact loads of light and heavy vehicles with a working width W2. Therefore, the NDBA concrete barrier can be installed on existing or new tunnels at a distance less than or equal to 70 cm from the facing of the tunnel wall.</p> </abstract>ARTICLEtrue and Hardware Implementation of Polar Coding for 5G Telecommunications<abstract> <title style='display:none'>Abstract</title> <p>The article explores a recursive algorithm for determining Bhattacharyya parameters, which is a measure of the degree of channel polarization for telecommunications with polar coding. A method is given for determining the positions of information and fixed bits in a polar code. The principles of constructing a polar encoder and a polar decoder successive cancellation are considered. The Field-Programmable Gate Array implementation of the successive cancellation list decoder is considered. Experimental studies of the construction of a polar code using Gaussian approximation have been carried out. The influence of the design signal-to-noise ratio on the bit error rate of telecommunications with polar codes has been studied. The use of multi-position modulation in telecommunications with polar codes has been studied. It is expected that the results obtained will be useful in hardware and software implementation of 5G telecommunications with polar coding.</p> </abstract>ARTICLEtrue Low-Cost “Handshake” Two-Way Ranging Protocol Applied to Road Traffic Communications<abstract> <title style='display:none'>Abstract</title> <p>The densification of the vehicle fleet leads to numerous challenges in road safety management. Wireless Sensor Networks (WSN) helps to manage vehicle-vehicle-infrastructure interactivity, in particular to predict dangers and avoid accidents, detect and penalize traffic violations. This requires a massive deployment of communicating nodes embedded in vehicles and in road infrastructure. The reliability of the systems built on these nodes lies in the accuracy of the ranging. In order to improve the factors that impact accuracy, various ranging protocols have been developed, but their implementations most often involve the use of expensive and specialized transceivers, which incorporate a dedicated IEEE 802.15.4a ranging layer. Our approach implements the basic and advanced functions integrated into low-cost transceivers and microcontrollers. As result, in two or three links according to the case, our protocol performs simultaneously the ranging and the data exchange, against a specific ranging session with a minimum of three exchanges for the other protocols. Moreover, each node knows the ranging data and has its clock frequency adapted to the controlled process. So, we meet the challenges of large-scale low-cost node deployment, while ensuring high reliability and performance of ranging.</p> </abstract>ARTICLEtrue Electric Vehicle Charging Station with Integrated Local Server OCPP Protocol as a Management System<abstract> <title style='display:none'>Abstract</title> <p>Electric vehicles are widely regarded as pivotal in driving the sustainability of transportation networks forward, thanks to their capacity to diminish carbon emissions, enhance air quality, and bolster the robustness of electricity grids. The accessibility of charging infrastructure and the subjective norms that endorse electric mobility actively shape the electric vehicles acceptance. In this study, Our main goal is to provide off-grid electric vehicle charging infrastructures and the data communication protocols that connect to servers. We analyze the specifications of the OCPP (Open Charge Point Protocol) with an emphasis on its applicabillity for electric charging stations for vehicles. Our research concludes that off-grid electric vehicle charging systems can be effectively applied to small electric vehicles such as electric motorcycles, scooters, and bicycles. The OCPP data communication protocol can also support interactions between small electric vehicle charging stations and central server management systems (CSMS). Furthermore, we tested the electric vehicle charging process for a duration of two hours, and the charging station consistently produced stable voltage, current, and power output, matching the inverter outputs and fulfilling the specifications required by electric vehicle charging adapters. Analysis of throughput data indicates a positive correlation between the number of operational ports at a charging station and the volume of data processed by the server. However, beyond a certain threshold a decline in data transactions was observed, attributable to data loss.</p> </abstract>ARTICLEtrue Falsification Detection Approach Using Travel Distance-Based Feature<abstract> <title style='display:none'>Abstract</title> <p>This paper addresses the vulnerability of vehicular ad hoc networks (VANETs) to malicious attacks, specifically focusing on position falsification attacks. Detecting misbehaving vehicles in VANETs is challenging due to the dynamic nature of the network topology and vehicle mobility. The paper considers five types (constant attack, constant offset attack, random attack, random offset attack, and eventually stop attack) of position falsification attacks with varying traffic and attack densities, considered the most severe attacks in VANETs. To improve the detection of these attacks, a novel travel distance feature and an enhanced two-stage detection approach are proposed for classifying position falsification attacks in VANETs. The approach involves deploying the misbehavior detection system within roadside units (RSUs) by offloading computational work from vehicles (onboard units, or OBUs) to RSUs. The performance of the proposed approach was evaluated against different classifiers, including a wide range of paradigms (KNN, Decision Tree, and Random Forest), using the VeReMi dataset. Experimental results indicate that the proposed method based on Random Forest achieved an accuracy of 99.9% and an F1-Score of 99.9%, which are better not only than those achieved by KNN and Decision Tree but also than the most recent approaches in the literature survey.</p> </abstract>ARTICLEtrue Needs of Researchers Implementing Supply Chain Digitalisation<abstract> <title style='display:none'>Abstract</title> <p>The digitalisation of the supply chain has presented substantial opportunities for companies to enhance resource allocation, pricing strategies, and overall operational efficiency. In this context, researchers play a crucial role in developing novel methodologies and algorithms that can confer a competitive edge to stakeholders. This study employed operational research methods to investigate the specific requirements of researchers in this domain. The results highlight the challenges, motivations, and practical needs experienced by researchers. Additionally, data-related issues and databases were examined to identify areas of improvement. The findings indicate that enhancing researchers' engagement in data-driven solutions for supply chain problems primarily hinges on addressing issues related to data quality, data accessibility, and regular dataset updates. By addressing all the aspects defined in this study, organisations can enhance the practical implementation of findings and drive advancements in supply chain management.</p> </abstract>ARTICLEtrue 2020 Project Analysis by Using Topic Modelling Techniques in the Field of Transport<abstract> <title style='display:none'>Abstract</title> <p>Understanding the main research directions in transport is crucial to provide useful and relevant insights. The analysis of Horizon 2020, the largest research and innovation framework, has been already realized in a few publications but rarely for the field of transport. Thus, this article is devoted to fill this gap by introducing a novel application of topic modelling techniques, specifically the Latent Dirichlet Allocation (LDA), in the Horizon 2020 framework for transport projects. The method is using the Mallet software with pre-examined code optimizations. As the first step, a corpus is created by collecting 310 project abstracts; afterward, the texts of abstracts are prepared for the LDA analysis by introducing stop words, optimization criteria, the number of words per topics, and the number of topics. The study successfully uncovers the following five main underlying topics: road and traffic safety, aviation and aircraft, mobility and urban transport, maritime industry and shipping, open and real-time data in transport. Besides that, the main trends in transport are identified based on the frequency of words and their occurrence in the corpus. The applied approach maximizes the added value of the Horizon 2020 initiatives by revealing insights that may be overlooked using traditional analysis methods.</p> </abstract>ARTICLEtrue Security Framework for VNF Package Protection in 5G Network Slicing Services<abstract> <title style='display:none'>Abstract</title> <p>The demand for scalable, open and granular networks has enabled mobile networks such as 5G to adopt new concepts including NFV (Network Function Virtualization). NFV separates the dependency of network functions from the hardware component, allowing them to be deployed flexibly and dynamically across network slices. In this way, operators can deliver personalized services and optimize the use of network resources, contributing to greater operational efficiency and an enhanced end-user experience. However, there are several issues to be addressed, such as the security of VNFs and the way in which service provider customers instantiate NSSIs (Network Slice Subnet Instance). In this article, we present a new approach based on blockchain 2.0, which guarantees the immutability of VNFs and templates, as well as highly secure instantiation with access management and support for replay attacks.</p> </abstract>ARTICLEtrue for Selecting Optimal Routes for the Transportation of Dangerous Goods in Conditions of Risk Uncertainty<abstract> <title style='display:none'>Abstract</title> <p>* A risk situation is a type of uncertainty situation where events are likely to occur. In other words, risk is an estimated probability, and uncertainty is something that cannot be quantified. The greater the uncertainty when making a decision, the greater the degree of risk.</p> <p>The investigation is devoted to the development of a unified methodology for selecting optimal (from the proposed alternatives) routes for transporting dangerous goods (any of the 9 standard classes) by road.</p> <p>A model for determining two groups of risk components for transporting dangerous goods on separate routes is proposed, namely: parameters of risks of probability of occurrence of emergency situations and parameters that affect the risks of complexity of eliminating their possible consequences. This opened up opportunities for correct selection of criteria when forming a multi-criteria optimization problem of transportation.</p> <p>Mathematical algorithms for a comprehensive solution of the multi-criteria optimization problem of routing dangerous goods transportation are developed using the classical criteria of Laplace, Wald, Savage, and Hurwitz.</p> <p>To confirm the legal capacity of the proposed approach and mathematical apparatus, the optimal route for transportation of cylinders with technical gases through the transport network of Lutsk was calculated. Possible alternative transportation routes have been identified and safety criteria have been formalized for two groups of risk components</p> </abstract>ARTICLEtrue Attractiveness of Newly Introduced Flights – Results of a Study for the Ostrava International Airport<abstract> <title style='display:none'>Abstract</title> <p>The paper addresses the issue of evaluating the attractiveness of new airport connections, one of which is a global transfer hub and the other is a regional European international airport. The attractiveness of new connections expressed, for example, by predicting the demand for new flight routes has long been studied, mainly using gravity models. The aim of the presented paper is to check whether an approach based on gravity models could be replaced with other approaches, in this case by multi-criteria evaluation methods. Questions of substitution of approaches based on gravity models, compiled for demand prediction, are relevant in cases where there are not enough input data for existing gravity models. The absence of input data occurs especially in cases where either there is no historical data on the operation of flights, or historical data do not have current significance, e.g. the operation of the flight has been interrupted for a longer time. The results of a study carried out for Ostrava International Airport located in the Czech Republic, show that gravity models for which relevant data are not available can be fully replaced by multi-criteria evaluation methods.</p> </abstract>ARTICLEtrue Analysis of Engine Type Trends in Passenger Cars: Are We Ready for a Green Deal?<abstract> <title style='display:none'>Abstract</title> <p>The air pollution of our planet is rising, and the contribution of road transport to global pollution has a serious impact on this phenomenon. Previous papers have analysed and recommended measures to reduce road transport’s negative environmental impact and carbon footprint. However, some restrictions are impossible (or very costly) to meet, even in developed countries. Unfortunately, presenting the impact of transport on air pollution levels as a whole can only give a general picture. This paper provides a more detailed analysis and attempts to assess the impact of one of the most important elements shaping modern transport, that is, vehicle engine types. Thus, the main objective of the study is to analyse and evaluate the different types of engines in vehicles from the point of view of technical, environmental, and economic aspects in European countries and to verify whether Europe is ready to implement the European Green Deal. The results indicate significant technological developments must occur in electric vehicles to become environmentally better than combustion engine-based cars. Additionally, in the case of some developing countries, owning a means of transport is still perceived as a symbol of a certain status, which is why it is still an important material asset. Thus, in rich countries, material status and environmental awareness (e.g. choice of public transport) will help to achieve climate neutrality, while poorer countries (even developed ones) may have severe problems in meeting EU requirements. Overall, while answering some questions, this article also poses new ones. Decision-makers often face challenging aspects. This article is intended to give them a basic knowledge to pursue an environmental policy that is viable and feasible for all countries.</p> </abstract>ARTICLEtrue Novel Method for Modeling and Predicting Transportation Data Via Multideep Assessment Methodology and Fractional Calculus<abstract> <title style='display:none'>Abstract</title> <p>Aviation is one of the most global industries, and if we can model and predict a country’s air transportation flow and indicators ahead of time, we may be able to use it as a key decision-making tool for the management and operation process. This study proposes a new modeling, and prediction method that employs both fractional calculus and Multi Deep Assessment Methodology (MDAM) techniques. For the application, air passengers carried, air freight, available seat kilometers, number of flights, destination points, international travelers, international destination points, and international flight data between 2011 and 2019 for eight countries with the busiest airports were chosen. As a result, the highest modeling error was discovered to be Germany’s air transport freight factor expressed as a percentage of 1,59E-02. The percentage of predictions with errors less than 10% was 90.278. We also compared the performance of two different MDAM methodologies. The novel MDAM wd methodology proposed in this paper has a higher accuracy in aviation factors prediction and modeling.</p> </abstract>ARTICLEtrue Transportation Efficiency with Optimal Container Placement Using the Bat Algorithm<abstract> <title style='display:none'>Abstract</title> <p>The objective of this article is to provide an in-depth exploration of the complex task of container storage at seaports, a problem characterized as one of the challenging NP (Non-Deterministic Polynomial time) problems. Seaports are faced with the dilemma of accommodating a finite number of containers due to the constrained surface area available, making the management of container storage operations a formidable task.</p> <p>To address this challenge, the present study leverages a meta-heuristic approach aimed at identifying an optimal storage plan for containers within a storage area. This approach is informed by insights drawn from bat swarm intelligence, commonly known as the Bat Algorithm. By integrating principles from this nature-inspired algorithm, the authors seek to develop a robust solution for optimizing container storage strategies in seaports. This approach takes into account several critical constraints, including container travel distances and considerations related to container type and departure dates.</p> </abstract>ARTICLEtrue Routing Optimization Algorithms for Pharmaceutical Supply Chain: A Systematic Comparison<abstract> <title style='display:none'>Abstract</title> <p>Nowadays, supply chain and road networks are full of complexity. Companies can differentiate themselves by offering superior customer service. Therefore, pharmaceutical distributors need to optimize route distribution for efficient and effective delivery to pharmacies, enhancing their competitiveness. In the field of operations research (OR), efficient route optimization is a significant function of the Vehicle Routing Problem (VRP) where the goal is to find the optimal distance travelled. The VRP can be solved using a range of algorithms, comprising exact methods, heuristics and meta-heuristics. This paper gives the basic concepts of some algorithms and these algorithms are compared based on the results. This study also extends its focus to the variation known as the Vehicle Routing Problem with Time Windows (VRPTW), that closely mirrors real-world scenarios, allowing for a more practical assessment of pharmaceutical distribution challenges and optimization solutions.</p> </abstract>ARTICLEtrue RSSI-Trilateration Model for Node Location: A Simulation Integrating Flora and Omnet++<abstract> <title style='display:none'>Abstract</title> <p>This work presents the employing of LoRaWAN (Long Range Wide Area Network) for location applications through a network simulation to determine a mobile node position. We rely on FLoRa (Framework for LoRa) and OMNeT++ (Objective Modular Network Testbed in C++) simulator, which uses Python feature tools, following the calculation of node placement using the trilateration technique. Our method differs from others in that we calculate the FLoRa power loss and determine different simulation settings using the shadowing feature of the log-distance path loss model. We approached RSSI (Received Signal Strength Indicator) to measure the distance between the LoRa gateways and the nodes, establishing a link between these parameters. Our work aims to promote the integration of open-source tools for verifying signal intensity values based on node distance from gateways. We consider it useful for engineers in predicting signal behaviors according to topology and settings variations. During the experimentation, the network underwent different performances according to the transmission parameters considered during the simulation. This was critical when increasing the number of mobile nodes, leading to consuming computer capacity and resources. Through repetition of tests, we confirmed the lower intensity of the received signal as the node moves to farther positions, reaching consistent power indicators and positioning accuracy. Overall, the results show that LoRaWAN integrated with trilateration techniques can be practical in providing adequate performance for node positioning accuracy and long-distance communication with low power consumption.</p> </abstract>ARTICLEtrue Management in Railways Construction Investments: A Case Study of China-Pakistan Economic Corridor (CPEC) ML-1 Project<abstract> <title style='display:none'>Abstract</title> <p>Railway projects are incredibly costly due to their complex nature. This study performs risk analysis and management of Pakistan railways ML-1 project expansion and upgradation that will be undertaken at US$6.8 billion under the China-Pakistan Economic Corridor (CPEC). The risks were identified based on an extensive literature review and their relevance to the CPEC. We employed fuzzy set theory (integrated with the risk severity index) to obtain the most severe risks. The novelty of this study is the technique employed to analyse and rank the risk, also there are no previous studies conducted that emphasized the construction risk of railway projects in Pakistan. The study is useful for all stakeholders of the project, as it can plan for them to tackle these risks and implement ML-1 successfully.</p> </abstract>ARTICLEtrue of Pothole Detection Accuracy of Selected Object Detection Models Under Adverse Conditions<abstract> <title style='display:none'>Abstract</title> <p>Potholes detection is an essential aspect of road safety and road infrastructure maintenance. Potholes, which are typically caused by a combination of heavy traffic and weather, are depressions or holes in the road surface that can cause damage to specific parts of a vehicle. Autonomous vehicles, in particular, must be capable of detecting and avoiding them. Hitting a deep or sharp-edged pothole at high speed can lead to loss of control or even an accident. This makes pothole detection all the more important. The accuracy of pothole detection systems installed in autonomous vehicles may be significantly impaired by adverse weather and bad light conditions. Therefore, the classification accuracy of selected well-known computer vision models for pothole detection under these specific conditions has been investigated. The results were then compared with state-of-the-art methods. Our findings showed that we outperformed many of them when used under adverse weather and low light situations. This paper presents valuable insights into the precision of various computer vision models for potholes detection. It may aid in selecting the optimal model for a specific application.</p> </abstract>ARTICLEtrue Road Traffic Video Congestion Classification Based on the Multi-Head Self-Attention Vision Transformer Model<abstract> <title style='display:none'>Abstract</title> <p>Due to rapid population growth, traffic congestion has become one of the major issues in urban areas. The utilization of technology may help to address this issue. This paper proposes a new Multi-head Self-attention Vision Transformer (MSViT) based macroscopic approach, for road traffic congestion classification. To evaluate this approach, we use the UCSD (University of California San Diego) dataset that includes different weather conditions (clear, overcast and rainy) and different traffic scenarios (light, medium and heavy). The classification accuracy reached a high level of 99.76% with this dataset and 99.37% when night-mode frames are added to it. The proposed MSViT based method outperforms the state-of-the-art macroscopic and microscopic methods that have been evaluated using the same UCSD dataset, which makes it an efficient solution for traffic congestion prediction.</p> </abstract>ARTICLEtrue of Automated Bascule Bridge and Collision Avoidance with Water Traffic<abstract> <title style='display:none'>Abstract</title> <p>The development of movable bridges is a modern technological advancement that requires the integration of multi-disciplinary concepts such as control, automation, and design. In order to demonstrate how a collision avoidance system works, this research offers the design of an automated double-leaf bascule bridge with a pulley-rope moving mechanism and Pratt truss. The bridge is created where a settled railway or roadway intersection of a navigable stream cannot attain a steep profile. The design took into account the length, height, and width of the bridge as well as automatic ship identification and scaffold leaf movement activity for ship crossing. For the safe passage of cars on the bridge and for stopping vehicles during bridge movement, the system includes a collision avoidance control system and an automated road barrier system. After sensor adjustment, the model bridge’s performance under test produced results that were adequate, with a success rate of 100%.</p> </abstract>ARTICLEtrue Dissemination Among Vehicles To Aid In Rendering Quick Emergency Services<abstract> <title style='display:none'>Abstract</title> <p>Road traffic in metropolitan cities is increasing at enormous rates resulting in congestion. Vehicles rendering emergency services like ambulances, fire engines, law enforcement vehicles, etc., act as lifelines and should be looked into with the highest priorities on the road. Such emergency vehicles (EmVs / EVs) are seen stuck many times in traffic, especially during peak hours of the day. The vehicles that block the EmVs on the road are unaware of the arrival of the same. Hence this work proposes a system that uses a central server that receives the location of the EmV and shares it with the civilian vehicles around. This is achieved through pinpointed accuracy systems like the Indian Regional Navigation Satellite System (IRNSS), Global Positioning System (GPS), and Global System for Mobile Communication (GSM), etc., The objective here is to help the EmVs reach their target location earlier thus saving lives.</p> </abstract>ARTICLEtrue