<abstract><title style='display:none'>Abstract</title>An autonomous vehicle (AV) is a vehicle that operates and performs tasks under its own power. Some features of autonomous vehicle are sensing the environment, collecting information and managing communication with other vehicles. Many autonomous vehicles in development use a combination of cameras, sensors, GPS, radar, LiDAR, and on-board computers. These technologies work together to map the vehicle’s position and its proximity to everything around it. Because of their reliance on these sorts of technologies, which are easily accessible to tampering, a autonomous vehicles are susceptible to cyber attacks if an attacker can discover a weakness in a certain type of vehicle or in a company’s electronic system. This lack of information security can lead to criminal and terrorist acts that eventually cost lives. This paper gives an overview of cyber attack scenarios relating to autonomous vehicles. The cyber security concept proposed here uses biometric data for message authentication and communication, and projects stored and new data based on iris recognition. Iris recognition system can provide other knowledge about drivers as well, such as how tired and sleepy they might be while driving, and they are designed to encrypt the vehicle-to-vehicle and vehicle-to-environment communication based on encryption security mechanisms.</abstract>

Data and Cyber Security in Autonomous Vehicle Networks

<abstract>The problem of calculation of optimal path for reverse parallel parking is examined. Elementary mathematical model of car movement on plane is described. Optimality criterion and restriction on a possible path for parallel parking are formulated. It is offered a way of choice of a quasi-optimal path for reverse parallel parking. Corresponding numerical calculations and graphic example are presented.</abstract>

Calculation of Optimal Path for Parallel Car Parking

<abstract><title style='display:none'>Abstract</title>The aim of this study was to analyze the modal shift of passengers by analyzing their preferences. If the preferences of passengers are known it is possible to build up mathematically their utility function. This is the statistically correct way to simulate the modal shift of the investigated area. To capture the preferences of passengers stated preference method was used in online questionnaire. Five key factors were identified (from the point of passengers): travel cost, travel time, comfort, safety and environmental efficiency. In order to decrease the number of questions three levels were predefined these three questions made the base of the choice model. Every replier got three alternatives and they were told to choose the best for themselves. From the results of the questionnaire the formulas and the parameters of the mode choice utility function was derived. With the help of statistical sample an exponential utility function showed the best matching. For the validation process a probability model was set up to be compared to the proportions of the utilities. With this utility function it is possible to handle the changes in possible future transport services. Based on the introduced statistical approach the described method can be used to identify the effect of transport modes on regional development and tourism. The revealed utility function can help to develop proper regional development plans.</abstract>

Budapest University of Technology and Economics, Department of Transport Technology and Economics Stoczek utca 2 Budapest H-1111

Budapest University of Technology and Economics, Department of Transport Technology and Economics, Stoczek utca 2 Budapest H-1111

Budapest University of Technology and Economics, Department of Environmental Economics, Magyar tudósok körútja 2 Budapest H-1117

Identifyingy the Utility Function of Transport Services From Stated Preferences

<abstract><title style='display:none'>Abstract</title>This article proposes a model of systems dynamics for the analysis and study of physical flows in a distribution logistics chain. The proposed model is a decision support tool that allows testing several scenarios in order to study the behavior of physical flows within a supply chain depending on the inventory and transport costs and taking into consideration the environmental issues through the integration of a CO2 tax in transport costs. The developed model can be used to analyze various scenarios and perform various “what-if” analyzes, as well as to answer questions about the long-term operation of distribution chains. The results show that logistic decisions and strategies taken at the supply chain level influence inventory and transport costs. They show also that the model is a well decision-support tool for calculating and analyzing transport and inventory costs. We first expose the methodology and the literature review. Next, we present in detail the structure of the model consisting of the causal loops diagram and stock and flow diagram. Finally, we discuss the results of the model.</abstract>

A Model of Systems Dynamics for Physical Flow Analysis in a Distribution Supply Chain

<abstract><title style='display:none'>Abstract</title>Since the mid-1990s, Colombia’s main airports (including those with the highest traffic) have been privatized, transferring governance to private operators. The remaining airports in the network (the smallest ones) continue with public governance. Based on this, the objective of this research article is to know, analyse and even measure the airport efficiency in a context of structural reform and at the same time compare this with the measure in airports with public governance. The methodology used to carry out the study is the Data Envelopment Analysis, and this methodology uses only “technical variables” (that is, only those related to infrastructure). The main results of the research reveal higher efficiency indices in the major (or more important) airports, almost all of them under private governance, although there is also a group of them (usually very small airports) with very low efficiency levels.</abstract>

Measurement of Airport Efficiency. The Case of Colombia

<abstract><title style='display:none'>Abstract</title> The transport activity is one of the most expensive processes in the supply chain. Forwarding and transport companies focuses on the optimization of transportation and the reduction of transport costs.The goal of this study is to develop a method which calculate the first (prime) cost of a given transport task more precisely than the state of the art practices. In practice the calculation of transport fee depends on the individual estimation methods of the transport managers, which could result losses for the company.In this study the elaborated calculation method for total first cost is detailed for three types of fulfilment of transport tasks. The most common type of achievement is, when “own vehicle is used with own driver”. A software was also developed for this case based on the elaborated method.Based on the calculations of our software, the first cost can be defined quickly and precisely to realize higher profit.</abstract>

First Cost Calculation Methods for Road Freight Transport Activity

<abstract>
<title style='display:none'>Abstract</title>
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.
</abstract>

Lorawan-Based RSSI-Trilateration Model for Node Location: A Simulation Integrating Flora and Omnet++

<abstract>
<title style='display:none'>Abstract</title>
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.
</abstract>

Risk Management in Railways Construction Investments: A Case Study of China-Pakistan Economic Corridor (CPEC) ML-1 Project

<abstract>
<title style='display:none'>Abstract</title>
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.
</abstract>

Vehicle Routing Optimization Algorithms for Pharmaceutical Supply Chain: A Systematic Comparison

<abstract>
<title style='display:none'>Abstract</title>
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.
</abstract>

A Novel Method for Modeling and Predicting Transportation Data Via Multideep Assessment Methodology and Fractional Calculus

<abstract>
<title style='display:none'>Abstract</title>
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.
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.
</abstract>

Enhancing Transportation Efficiency with Optimal Container Placement Using the Bat Algorithm

<abstract>
<title style='display:none'>Abstract</title>
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.
</abstract>

Analysis of Pothole Detection Accuracy of Selected Object Detection Models Under Adverse Conditions

<abstract><title style='display:none'>Abstract</title>Smart contracts are scripts on the top of the blockchain technology. They represent a form of automation by what the layers of intermediaries can be reduced or even completely replaced. Accordingly, blockchain smart contracting systems decrease transaction and enforcement costs as well as process time.Moreover, we argue, blockchain and smart contracts can facilitate cross-organisational collaboration and their underlying business processes. Hence, they are able to support the integration of entrepreneurs and SMEs into trans-national supply chains by reducing high entry barriers and weakening the dominating position of big players.This paper discusses the research questions how blockchain smart contracting can facilitate the implementation of collaborative logistics structures and how the integration of SMEs into sustainable maritime supply chains can be safeguarded. The research bases on expert interviews and case studies. The results showcase the potentials of using blockchain smart contracting in the environment of trans-national and multimodal supply chains.</abstract>

Blockchain and Smart Contracts for Entrepreneurial Collaboration in Maritime Supply Chains

<abstract><title style='display:none'>Abstract</title>One of the most essential tasks for a number of systems of the automatic controls in the autonomous electric power systems of the water transport is accurate calculation of variable harmonic components in the non-sinusoidal signal. In the autonomous electric power systems operating with full semiconductor capacity, the forms of line currents and voltages are greatly distorted, and generator devices generate voltage with inconsistent frequency, phase and amplitude. It makes calculation of harmonic composition of the distorted signals be a non-trivial task. The present paper provides a mathematical set for solution of the outlined problem including the realization in the discrete form. The simplicity and efficiency of the system proposed make possible to perform its practical realization with the help of cheap FPGA. The test of the developed system has been performed in the medium Matlab.</abstract>

Modeling of Complex Structures for the Ship's Power Complex Using Xilinx System

<abstract><title style='display:none'>Abstract</title>Currently, in many cities around the world there is a significant increase in the number of vehicles, which leads to an aggravation of problems and contradictions in the road and transport system. This is especially true of traffic congestion, since the presence of the congestion leads to a number of negative consequences: an increase in travel time, additional fuel consumption and vehicle wear, stress and irritation of drivers and passengers, environmental poisoning and others. To solve the problem of congestion, it is necessary to have a reliable system for collecting information about the situation on the roads and a well-developed method for analyzing the collected information. The paper discusses the possibilities of collecting the required information using multi-touch video cameras and ways to improve them. A distinctive feature of this study is the registration of pedestrians crossing the road at the intersection. The aim of the work is to develop methods for collecting information using road sensor video surveillance systems in a traffic congestion and data processing using statistical methods such as: multiple regression analysis, cluster analysis, multidimensional scaling methods and others. The tasks were set: 1) to identify the most significant factors affecting the intensity of movement of vehicles at intersections in a congestion; 2) divide congestion into clusters with the identification of their characteristics; 3) to give a visual representation of multidimensional statistical information obtained with the help of multi-touch road video cameras.</abstract>

The Use of Multi-Sensor Video Surveillance System to Assess the Capacity of the Road Network

<abstract><title style='display:none'>Abstract</title> This study proposes a hybrid multiple criteria decision making (MCDM) methodology for evaluating the performance of the Indian railway stations (IRS). Since the customers are heterogeneous and their requirements are often imprecise, the evaluation process is a critical step for prioritizing the IRS. To improve the existing approaches, an efficient evaluation technique has been proposed by integrating rough numbers, analytic hierarchy process (AHP) and multi-attribute border approximation area comparison (MABAC) methods in rough environment. The relative criteria weights based on their preferences given by experts is determined by rough AHP whereas evaluation of the alternatives based on these criteria are done by the modified rough MABAC method. A case study of prioritizing different railway stations in India is provided to demonstrate the efficiency and applicability of the proposed method. Among different criteria “proactively” is observed to be the most important criteria in our analysis, followed by ‘Railfanning’ and ‘DMO’ is found to be the best among the forty IRS in this study. Finally, a comparative analysis and validity testing of the proposed method are elaborated and the methodology provides a standard to select IRS on the basis of different criteria.</abstract>

Multi Criteria Evaluation Framework for Prioritizing Indian Railway Stations Using Modified Rough AHP-Mabac Method

<abstract><title style='display:none'>Abstract</title> Synchronous motors and their modifications (ac converter-fed motor, etc.) enable to develop low-noise, reliable and economically efficient electric drive systems. The construction of up-to-date systems based on the synchronous machines is impossible without development of the computing software incorporating mathematical and computing simulation. In its turn, modelling of the synchronous machines as a rule is based on the equations by Park-Gorev, application of which requires adoption of a series of allowances. These allowances in a number of cases do not permit to obtain adequate results of the simulation coinciding with the results of field experiments of the systems under review. Moreover, while applying the system of equations by Park-Gorev to research the systems including interaction of synchronous machines with semiconducting converters of electric energy it is necessary simulate the process of formation their controlling signals in the sphere of frequency. If the states of converter’s keys are defined not only by controlling impulses but also by the state of currents in the synchronous machines flowing through them, such approach is not reasonable.</abstract>

Use of Information Intelligent Components for the Analysis of Complex Processes of Marine Energy Systems

<abstract><title style='display:none'>Abstract</title> New telecommunication technologies and services have caused important challenges on travel behaviour and trip characteristics. Existing literature studies show many different outcomes regarding the effects of the new technologies on the participation of people to their personal activities and related travel; specifically, e-shopping may produce the reduction of shopping trips (substitution effect), but also an increase of trips thanks to the reuse of the travel time saved for other activities and trips (complementarity’s effect). The focus of this study is to analyse the aspects mostly affecting consumer choices of purchasing goods by web or in-store, with the aim of understanding how to operate so that e-shopping can positively modify consumers’ travel behaviour. Our research findings show that individual social and economic factors, consumer attitudes, and shopping mode characteristics influence the usage of online shopping. An experimental survey addressed to a sample of Italian consumers is used in the study.</abstract>

University of Calabria - Faculty of Engineering, Department of Land Use Planning P. Bucci, cubo 46/B, 87036 Rende (CS), Italy Ph. +39.984.496754. Fax +39.984.496784

University of Calabria – Faculty of Engineering, Department of Land Use Planning P. Bucci, cubo 46/B, 87036 Rende (CS), Italy Ph. +39.984.496784. Fax +39.984.496784

University of Calabria – Faculty of Engineering, Department of Land Use Planning P. Bucci, cubo 46/B, 87036 Rende (CS), Italy Ph. +39.984.496782. Fax +39.984.496784

Individual Attitudes and Shopping Mode Characteristics Affecting the Use of E-Shopping and Related Travel

Personalia FORM

T&T template paper

Instructions for Authors

Transport and Telecommunication Journal

The Journal of Transport and Telecommunication Institute

Journal “Transport and Telecommunication” is a peer-reviewed open-access scientific journal, owned by Transport and Telecommunication Institute and has more 10 years of experience. This...

Impact Factor

Five Year Impact Factor

Cite Score

SNIP

MNiSW

Google Scholar h5-index

Google Scholar h5-median

Journal “Transport and Telecommunication” is a peer-reviewed open-access scientific journal, owned by Transport and Telecommunication Institute...