Application Research of Key Frames Extraction Technology Combined with Optimized Faster R‐CNN Algorithm in Traffic Video Analysis

Aim. Threats of a non-physical nature have a significant effect on the security of intelligent transportation systems (ITS). They may have the form of unlawful interference in the development and implementation of ITS. The creation of a trusted framework for the development and implementation of ITS is examined as in the case of intelligent water transportation systems (IWTS). Problems. By decree of the President of the Russian Federation, ITS, telecommunications and security of information processing are among the priority areas of scientific and technological development. ITS technologies, as well as those involved in the creation of trusted, secure system and application software are among the most important critical high technologies. The operation of ITS involves wide use of computerised systems that implement the latest information and telecommunication technologies, automated and automatic control technologies, artificial intelligence that can pose security threats. ITS are to be developed and operated in a trusted environment. Methods. The paper used the methodology for ensuring the security of IWTS, development of secure hardware and software platforms for secure automated systems, methods of system analysis, dependability theory, information protection, and law. Results. The paper defines the problem of creating a trusted framework for the development and implementation of IWTS, the applicable terminology is developed. The author examined the effect of IWTS on the security of critical information infrastructure (CII) and national security, developed a model of relationships between the IWTS security domains taking into account threats of physical and non-physical origin. Examples of computer incidents within IWTS that caused consequences at the national and international levels are given. The composition of the IWTS facilities attributed to CII is defined, critical processes implemented by standard CII facilities as part of the IWTS are set forth. The author lists conceptual problems of IWTS security, defines the principles of creating a trusted framework for the development and implementation of IWTS. Conclusion. Ensuring the security of IWTS against modern threats requires solving a number of problems associated with the creation of a trusted framework for the development and implementation of IWTS. For the purpose of improving the timeliness and quality of their solution, the paper proposes an intuitive terminology that reflects the subject area and helps finding a common understanding of the security domain by experts from various industries. IWTS facilities have an effect on CII security and national security in general. That is taken into account in the model of relationships between IWTS security domains, demonstrated using cases of computer incidents within IWTS that caused consequences at the national and international level. Given the above, the paper lists IWTS facilities attributed to CII and sets forth examples of critical processes implemented by standard CII facilities as part of the IWTS. The defined list of conceptual IWTS security problems take into account the growing landscape of IWTS security threats that includes insecure software, hardware and software platforms, software and hardware systems and emerging technologies. When developing the principles for the creation of a trusted IWTS development and implementation framework, the author took into account the best practice of implementing the methodology for creating national secure hardware and software platforms of CII facilities that enables the creation of secure automated systems for various applications that are based on domestically-developed solutions. The examined matters are of a systemic nature, which allows using the findings in the development and implementation of ITS in other modes of transportation.

Transportation infrastructures integrate advanced Information Technology to enable the operations and management of transportation systems. Advanced vehicle and road systems of a comprehensive concept that improve the efficiency and safety of road traffic are being built and will be commercially available through Intelligent Transport Systems (ITS) technology and services. To support ITS technology, Vehicle-To-Everything (V2X) is needed, and in the 3rd Generation Partnership Project, many studies have focused on Long Term Evolution (LTE)-based vehicle communications. In order to realize reliable and optimized communications performance in vehicle communications, which move in propagation environments at high speed, in this study, we propose a novel channel estimation scheme suited for LTE sidelink-based Vehicle-To-Vehicle systems. Conventional channel estimation schemes can be categorized as Decision-Directed Channel Estimation, spectral temporal averaging, and smoothing methods. In this study, unlike conventional channel estimation schemes, we propose a Novel Interference Cancellation of Channel Estimation (NICCE) using Quadratic Smoothing of the pilot symbols, which estimates a channel with greater accuracy, and a novel interference cancellation of channel estimation in data symbols. In simulation results, the proposed NICCE scheme shows improved overall performance in terms of the Normalized Mean Square Error and uncoded Bit Error Rate relative to conventional schemes.

Traffic congestion in urban areas has become crucial problem for town planners and government who are trying to offer good transport services to citizens by using the advancements in technology. Though there is huge development in transportation systems due to emergence of Information and Communication Technology (ICT) still there is a scope for further improvement. Intelligent Transportation System (ITS) is the core part in development of smart cities. Internet of things (IoT) has launched enough space for the technology to grow more. With these advancements we propose smart barricade system which diverts the traffic to less congested reverse side of the road. The main concept is to use the underutilized side of the road. The system offers solution to reduce the road traffic congestion to some extend in certain types of situations. An experimental prototype of the proposed system has been developed. This paper provides a deep insight about applicability of IoT in the management of transportation system.

Half of the world’s population resides in cities and this percentage is going to rise in the coming years. This rapid transformation of the economy and society is making traditional city management redundant. Intensive urbanization has brought with it some challenges. Scanty resources, population growth, increased carbon footprint, reduced air quality, congestion on roads, depriving health status, and falling food quality, all are prominent parts of cities. Does this bring a question in mind is accelerated growth sustainable? The answer and solution to this is an adaption of the Smart City Concept. A smart city integrates all the available technology with the requirements of city development and builds infrastructure which can improve the quality of life of citizens. Smart cities are designed in a manner to use minimum resources with maximum efficiency in all areas of urban life. It provides smart solutions using smart technologies. Urban needs and technological advancements meet in smart cities. It manages cities more quickly and effectively by using AI, IT technologies, and robotic process automation. Intelligent transportation, intelligent energy, intelligent governance, intelligent security, intelligent healthcare are all central to the idea of smart cities. The emphasis of this essay is on smart transit as a component of smart cities. The movement of people and goods across several geographical boundaries has been significantly aided by the transportation sector. Globally, the majority of smart cities face logistical and transportation issues. Both the fast growing human population and the increase in the number of cars on the road are to blame for this. In order to design and run a sustainable transportation system, technology may be of great assistance. Robotic systems for real-time vehicle data collection, traffic management, and using mobility on demand in trip planning through a single user interface have emerged as cities struggle with traffic congestion. The transportation industry, which faces difficulties including traffic congestion, unanticipated delays, and routing issues that cause businesses to lose money, has successfully used robotic process automation. Robotic process automation provides reliable results and affordable solutions while reducing uncertainty in the decision-making process. It is very helpful in designing and running a successful transit system. Robotic Process Automation (RPA) systems for obtaining real-time data from vehicles, buses, and trucks for traffic management and using mobility on demand in trip planning through a single user interface have emerged as cities struggle with poor management and congestion. By examining different uses of robotic process automation, it is possible to evaluate precise prediction and detection models that are intended to forecast traffic volume, an appropriate route, traffic conditions, accurate information about timing, incidents, and which time and roadway for transport are suitable for running and mobility. The application of RPA in smart cities could be seen in Intelligent Transportation Systems’ Traffic Management, Public Transportation, Safety Management, Manufacturing, and Logistics. The research focuses on areas of concern for smart cities in the sphere of the transportation sector and related difficulties that may be solved via robotic process automation. The article emphasizes the challenges and solutions for making smart transportation more effective by using Intelligent Robotic Transportation Systems.

Recently, electric vehicles (EV) have gained much attention as a potential enabling technology to support CO2 emissions reduction targets. Relative to their internal combustion vehicle counterparts, EVs consume less energy per unit distance, and add the benefit of not emitting any carbon dioxide in operation and instead shift their emissions to the existing local fleet of power generation. However, the true success of EVs depends on their successful integration with the supporting infrastructure systems. Building upon the recently published methodology for the same purpose, this paper presents a “systems-of-systems” case study assessing the impacts of EVs on these three systems in the context of Abu Dhabi. For the physical transportation system, a microscopic discrete-time traffic operations simulator is used to predict the kinematic state of the EV fleet over the duration of one day. For the impact on the intelligent transportation system (ITS), the integration of EVs into Abu Dhabi is studied using a multi-domain matrix (MDM) of the Abu Dhabi Department of Transportation ITS. Finally, for the impact on the electric power system, the EV traffic flow patterns from the CMS are used to calculate the timing and magnitude of charging loads. The paper concludes with the need for an intelligent transportation-energy system (ITES) which would coordinate traffic and energy management functionality.

Intelligent Transportation Systems (ITS) are increasingly shifting toward data-driven and artificial intelligence-based frameworks that integrate sensing, prediction, and control to enhance mobility efficiency, safety, and adaptability. This dissertation contributes to the development of next-generation ITS through three complementary studies focusing on flexible traffic monitoring, real-time traffic forecasting, and stability-aware vehicle control. The first study develops a multi-drone framework for wide-view corridor traffic analysis and origin-destination (OD) estimation. By coordinating multiple unmanned aerial vehicles, as demonstrated with two drones in this study, the framework enables continuous vehicle tracking across extended corridors. A deep learning-based pipeline combining vehicle detection and tracking automatically reconstructs vehicle trajectories and matches them across drone views. Field experiments conducted at a freeway weaving section achieved over 91% accuracy in OD flow estimation compared with ground-truth data, demonstrating the framework’s effectiveness for scalable and high-resolution traffic monitoring. The second study proposes a day-specific spatial-temporal graph convolutional network (Day-STGCN) for real-time traffic forecasting. Building upon the classical STGCN architecture, the model integrates rolling historical time-dependent features with day-type categorization to capture both short-term variations and long-term recurring patterns. Using real-world sensor data, the model significantly improves prediction accuracy over baseline graph neural networks, providing robust day-aware forecasting that reflects realistic daily traffic dynamics. The third study investigates cooperative adaptive cruise control (CACC) and its effects on traffic string stability under varying market penetration rates of connected and automated vehicles (CAVs). Analytical derivations establish explicit stability conditions linking controller parameters, time headway, and control intervals in both homogeneous and heterogeneous traffic flows. The results reveal that appropriately designed CACC controllers enhance string stability even in mixed environments with different types of vehicles. Collectively, these studies present an integrated framework that advances ITS through data-driven sensing, learning, and control, offering theoretical and practical foundations for more intelligent, responsive, and stable transportation systems.

The rapid increase in population has increased the traffic density in urban areas. In current scenario, the major challenges faced by transportation systems are congestion, accidents and pollution control, etc. In recent decade’s development of Internet of Things (IoT) and communication technologies and connected devices have paved way for the involvement of information and communication in all aspects of smart city. IoT has transformed the transportation system by enhancing customer experience, safety, and operational performance. The smart or intelligent transportation system is possible that can provide in vehicle transportation and navigation system and assistance. Various new techniques are required to further enhance the intelligence and capabilities of applications. Cyber-physical system is an integral part of intelligent transportation system. CPS can help in gathering information in distributed manner over various diverse networks and analysing useful information to control operations of Intelligent Transportation system. This paper provides the description of the main elements of traffic management system in intelligent transportation systems. The focus is on the algorithms used to increase the efficiency of transport management in Intelligent Transportation System.

The Intelligent Transportation System (ITS) is the effective and comprehensive application of advanced science and technology (information technology, computer technology, data communication technology, sensor technology, electronic control technology, automatic control theory, operations research, artificial intelligence, etc.) in transportation, service control, and vehicle manufacturing to strengthen the connection between vehicles, roads, and users. The result is an integrated transport system that ensures safety, enhances efficiency, improves the environment and saves energy. It is an effective means to solve the current urban traffic problems and an important indicator for the construction of a "smart city". Through the construction of an urban traffic collection system, the system solves the existing traffic problems, further integrates all kinds of road traffic resources, builds the urban "traffic brain", mines the huge amount of traffic data, deconstructs the operation law and characteristics of urban traffic, realizes the accurate urban traffic management, scientific management and normal management, and makes people's traffic travel safer. It makes people's traffic travel safer, more convenient and more efficient. This study introduces innovative computational models and algorithms specifically designed for traffic optimisation, as well as data-driven machine learning techniques to improve the operational efficiency of intelligent transport systems. An extensive analysis of case studies on the integration of AI into traffic management systems provides empirical evidence of their impact, focusing on the performance evaluation of these AI applications as well as potential scalability issues that may arise in different urban environments.

The high-speed railway (HSR) transportation system in China has been growing rapidly during the past decade. In 2016, the total length of HSR in China has reached to 22,000 kilometers, and there are over 2,000 pairs of high speed trains operating daily. With the advancement of design and manufacturing technologies, the reliability and construction costs have been improved significantly. However, there is still great need for reduction of their operation and maintenance costs. With such incentive, a pilot project has been launched to develop a prognostics and health management system for rolling stock to transform the maintenance paradigm from preventive to predictive maintenance. Considering the high task variety and big data environment in HSR real-time monitoring system, a cyberphysical system (CPS) architecture is proposed as the framework for its PHM system. This paper reviews the needs of predictive maintenance for the HSR system, and then present a concept design of the CPS-enabled smart operation and maintenance system.

The high-speed railway (HSR) transportation system in China has been growing rapidly during the past decade. In 2016, the total length of HSR in China has reached to 22,000 kilometers, and there are over 2,000 pairs of high speed trains operating daily. With the advancement of design and manufacturing technologies, the reliability and construction costs have been improved significantly. However, there is still great need for reduction of their operation and maintenance costs. With such incentive, a pilot project has been launched in CRRC to develop a prognostics and health management system for rolling stock to transform the maintenance paradigm from preventive to predictive maintenance. Considering the high task variety and big data environment in HSR real-time monitoring system, a cyber-physical system (CPS) architecture is proposed as the framework for its PHM system. This paper reviews the needs of predictive maintenance for the HSR system, and then present a concept design of the CPS-enabled smart operation and maintenance system.

Indicators development to support intelligent road infrastructure in urban cities

Internet of Vehicles is the basis of the application of intelligent transportation system .This article has carried on the analysis and discussion about the concept of IOV, applicable architecture, system service type, and need to emphasize solving the key technology of application and development of IOV system. IOV technology involves many disciplines, it needs to be studied further.

Intelligent Transport Systems (ITS) work with information and control technologies providing the core of ITS functions. Some of these technologies like loop detectors are well known to transportation professionals. However, there are a number of less familiar technologies and system concepts that are keys to ITS functions. Although information and control technologies act as a technical core of ITS, human factors also remain vitally important and potentially very complex issues. The process of operating ITS is influenced by a number of random factors. Along with an assessment of dependence upon separate random factors, the classification of those in the whole hierarchical structure of operating ITS is presented. Statistical information on operating ITS is renewed and replenished in the course of time. With the growth of information amounts, the costs of storing them also increase. Therefore, the article presents relevant algorithms for obtaining required statistical assessments with the least statistical information. It is deduced that while modelling the process of operating ITS, an analytical description of random factors applying non‐parametric assessment is suitable.

The complex large-scale integrated open systems (CLIOS) process is an overarching mechanism for considering systems, especially those exhibiting nested complexity, in which both the physical and the institutional aspects are complex. A special case of the CLIOS process is regional strategic transportation planning. New technologies, such as intelligent transportation systems, allow consideration of the planning, management, operations, and maintenance of transportation systems at the regional scale. Although the technological issues in advancing to this scale have proved tractable, the institutional issues concerned with deploying these systems across political jurisdictions with different measures of performance and different cultural perspectives has proved quite difficult. This paper explores processes for studying these institutional questions and integrating a number of concepts into the process: technological change, sustainability, real options, supply chain management, the various transport modes, and social, political, and economic factors. The paper serves as a case study of tailoring the CLIOS process into a process specifically designed to systematically address particular issues, in this case, regional strategic transportation planning.

To enable intelligent transportation systems, the Internet of Vehicles (IoV) uses wireless communications between roadside units, onboard units), phones, and other gadgets within a vehicle to deliver a new convenient, comfortable, and safe driving experience. IoV is now more exposed and frequently targeted because of its greatly increased reliance on wireless communication, control, and computer technology, To put it another way, an adversary may target such an open channel to intercept, change, inject malicious messages, or erase loaded data. This could lead to replay, impersonation, middle attack, privileged insider, and other related attacks. An authentication protocol should strive to accomplish security, anonymity, and untraceability among other critical aspects. In this research, we suggest a brand-new key agreement and mutual authentication methodology for IoV powered Intelligent transportation system (ITS). We demonstrate that our suggested system is secure against several known threats in IoV- the enabled ITS environment. Furthermore, a thorough comparison of our proposed system to eight other competing ones reveals that it has the lowest communication and computational costs. In addition, it is more secure and provides more functionality characteristics.