Vehicular Edge Computing: Architecture, Resource Management, Security, and Challenges

Vehicular Edge Computing (VEC), based on the Edge Computing motivation and fundamentals, is a promising technology supporting Intelligent Transport Systems services, smart city applications, and urban computing. VEC can provide and manage computational resources closer to vehicles and end-users, providing access to services at lower latency and meeting the minimum execution requirements for each service type. This survey describes VEC’s concepts and technologies; we also present an overview of existing VEC architectures, discussing them and exemplifying them through layered designs. Besides, we describe the underlying vehicular communication in supporting resource allocation mechanisms. With the intent to overview the risks, breaches, and measures in VEC, we review related security approaches and methods. Finally, we conclude this survey work with an overview and study of VEC’s main challenges. Unlike other surveys in which they are focused on content caching and data offloading, this work proposes a taxonomy based on the architectures in which VEC serves as the central element. VEC supports such architectures in capturing and disseminating data and resources to offer services aimed at a smart city through their aggregation and the allocation in a secure manner.

STRUCTURE OF THE STREET ROAD NETWORK IN THE FREIGHT TRANSPORTATION SYSTEM

The road network constitutes the main part of the transport system for both passenger and freight traffic. Achieving a sustainable road transport system including multimodal terminals, autonomous vehicles, intelligent transport systems, infrastructure are considered to be important design areas. The efficient use of the transport system is essential in terms of economic, environmental and social sustainability. Therefore, it is necessary to develop methods for optimizing the transportation process

Evaluation the influence of distance-based K-means method for detecting moving vehicles

Detecting moving vehicles is one of important elements in the applications of Intelligent Transport System (ITS). Detecting moving vehicles is also part of the detection of moving objects. K-Means method has been successfully applied to unsupervised cluster pixels for the detection of moving objects. In general, K-Means is a heuristic algorithm that partitioned the data set into K clusters by minimizing the number of squared distances in each cluster. In this paper, the K-Means algorithm applies Euclidean distance, Manhattan distance, Canberra distance, Chebyshev distance and Braycurtis distance. The aim of this study is to compare and evaluate the implementation of these distances in the K-Means clustering algorithm. The comparison is done with the basis of K-Means assessed with various evaluation paramaters, namely MSE, PSNR, SSIM and PCQI. The results exhibit that the Manhattan distance delivers the best MSE, PSNR, SSIM and PCQI values compared to other distances. Whereas for data processing time exposes that the Braycurtis distance has more advantages.

Evaluation of the Feasibility of an Intelligent Transport System for an Urban Area

The Intelligent Transportation System is one of the burgeoning inventions that uses new technology to solve a variety of issues. Its compatibility with real-world issues in developing nations like India, such as traffic congestion, infrastructure demand, high traffic loads, and non-lane traffic systems. It is critical to assess a technology's potential in order to determine its viability. The goal of this article is to determine the utility cost ratio of implementation so that it may be evaluated without changing the existing infrastructure design. The end result is a utility cost analysis approach that takes social, economic, and environmental issues into account. As a result, the analysis is quickly examined so that the technology may be applied according to its appropriateness. Keywords: Investments, Congestion, Intelligent Transportation System (ITS), Benefits, Traffic.

CZECH NATIONAL STRATEGY OF DEVELOPMENT OF INTELLIGENT TRANSPORT SYSTEMS AND LINKED ACTIVITIES

The article presents topical news on intelligent transport systems policy, strategy, and linked activities in the Czech Republic. It introduces historical background, relation to other documents, and current development in 2021. The Strategy of Development of Intelligent Transport Systems 2021-2027 with a View to 2050 (in force since January 2021) is the core document. The strategy is introduced by its context, methodology and structure of the content. Focus on coming years is included in this article, too: essential support for the ITS policy brings the online ITS Library (https://www.its-knihovna.cz), a knowledge database, described here with its certain parts and space for supportive tools. The tools enable to manage information on implementation progress, selected progress indicators and monitoring of ITS data quality, expressed by data conformance testing and publishing. The conclusion chapter gives a general overview on implementation of the Strategy and the ITS Library in the future.

THE IMPACT OF INNOVATIVE TECHNOLOGIES ON THE EFFICIENCY OF RAILWAY SYSTEM MANAGEMENT

The article discusses the issues of introducing innovative technologies into the railway management system. The object of the study is the efficiency of management of railway systems. The subject of the research is innovative technologies and their impact on the effectiveness of railway systems management. The purpose of the work is to conduct a theoretical analysis of the impact of innovations on the efficiency of railway systems management and, using the example of large foreign railway systems, to determine the main factors of innovation efficiency. The scientific novelty of the presented work lies in the analysis of foreign experience in the development of effective management tools for railway systems in the context of innovation. The paper concludes that the future of the railway industry directly depends on the degree of its digitalization and technologization, the introduction of intelligent transport systems and active integration into the global space of innovative development.