Formalizing Criteria of Intelligent Transportation and Logistic Systems Functioning

Transportation systems operate in a domain that is anything but simple. Many exhibit both spatial and temporal characteristics, at varying scales, under varying conditions brought on by external sources such as social events, holidays, and the weather. Yet, modeling the interplay of factors, devising generalized representations, and subsequently using them to solve a particular problem can be a challenging task. These situations represent only a fraction of the difficulties faced by modern intelligent transportation systems (ITS). In this paper, we present a survey that highlights the role modeling techniques within the realm of deep learning have played within ITS. We focus on how practitioners have formulated problems to address these various challenges, and outline both architectural and problem-specific considerations used to develop solutions. We hope this survey can help to serve as a bridge between the machine learning and transportation communities, shedding light on new domains and considerations in the future.

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.

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.

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.

In transportation environment, Intelligent Transportation System (ITS) is being used in various stages of every transport mode (road, rail, air & sea). The aim of intelligent transportation system is to provide the On-Road Vehicles (ORVs) with reliable Internet access connectivity, emergency notification and other safety information via infrastructure-based Road Side Units (RSUs). In the past decade, intelligent transportation system has been started in many countries where RSUs are provided with all type of communication services to connect, compute, communicate and share the information between its neighboring RSUs and on-road vehicles. However, there are certain diffcuilties in which the information cannot be delivered reliably such as Line Of Sight (LOS) communication with on-road vehicles, packet loss, latency, retransmission overhead and multiple target tracking of objects over time-to-time etc. Thus, the intelligent transportation system becomes a complex network of entities. Modern intelligent transportation systems use relay-RSU nodes (i.e., small sized Unmanned Aerial Vehicles) also referred as RRSU node network deployed between satellites and on-road vehicles as they provide many advanages like coverage, reliability and information sharing without depending more on knowledge provided by satellites. In this paper, a novel Aerial Intelligent Relay-Road Side Unit (AIR-RSU) framework has been proposed to determine the network connectivity status level and analyze the communication link stability among RRSUs, and between RRSUs and on-road vehicles for every time instants Ti based on certain performance metrics discussed in this paper. The proposed AIR-RSU framework holds the precise status/information about the network connectivity needed in the transportation environment carefully and effectively accounting the frequent changes in positions. The performance of the proposed AIR-RSU framework is evaluated using rectangle waypoint mobility model for on-road vehicles and steady state random waypoint mobility model for RRSU nodes, which measures the network connectivity status and the performance metrics periodically. Furthermore, a comparative analysis is done to both individual nodes and entire network in terms of network load.

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.

With the rapid advancement of intelligent transportation systems (ITS), secure processing of color traffic images has become critical for traffic management, safety monitoring, and flow analysis. However, ITS are increasingly susceptible to malicious attacks and data tampering. To address this, we propose an advanced visual encryption method specifically for color traffic images. Our approach employs discrete wavelet transform (DWT) to represent images sparsely, followed by dynamic three‐dimensional spiral disruption for encryption. Chaotic systems then compress the encrypted data, embedding it into a carrier image via least significant bit (LSB) techniques. Experimental results demonstrate robust visual security, achieving a peak signal‐to‐noise ratio (PSNR) above 42 dB, strong resilience against common attacks, and a substantial a key space of 2 512 ×10 60 , effectively resisting brute‐force attacks. Neighboring pixel correlation coefficients drop below 0.15, compared to original images (>0.87), and under shear resistance attack with 128×128 data loss, PSNR remains above 23 dB. Additionally, employing P‐tensor product compressed sensing significantly reduces measurement matrix dimensionality, enhancing transmission efficiency. This method offers a viable solution for secure storage and transmission in modern ITS, significantly bolstering privacy and system robustness. The implementation is available at: https://gitee.com/zhangshuo‐aly/image‐encryption .

The concept of smart transportation systems is increasingly becoming critical in addressing the challenges posed by an increasing number of mega cities in both developed and developing regions in maintaining safety, smooth traffic flow, and an environmentally friendly and sustainable urban environment. The Government of Zimbabwe deregulated its transport sector in the early 1990s. This development ushered in the informal public transport operators, locally referred to as ‘kombis'. Major cities such as Harare are characterised by a disjointed and chaotic urban public transport system. The major problems are the impacts this has on the quality of the environment. Currently, the urban public transport system is contributing greatly to both air and noise pollution within the confines of the city, especially in the Central Business Districts. The problem is further exacerbated by the massive importation of used vehicles from outside the country. These developments have resulted in high emission rates of major air pollutants resulting in a deterioration of the ambient air quality especially in the major cities such as Harare. Transportation is a major source of air pollutants. Vehicles are probably the largest single source of pollutants such as hydrocarbons, nitrogen dioxide and carbon monoxide. Other harmful emissions include as lead, benzene, arsenic, aldehydes, sulphates, particulate matter and the secondary creation of ozone. In Harare the number of registered vehicles increased from 192 901 in 1994 to 292 862 and by August 1999 showing that the increase in the number of vehicles is mostly in the cities. This chapter seeks to explore how smart transportation system can be adopted in Harare, the capital city of Zimbabwe. Harare was purposefully selected as it is experiencing rapid urbanization and motorization in the country. Using documentary analysis, discourse analysis and textual analysis, the chapter also describes and examines the challenges, constraints and opportunities of adopting smart urban transportation system in Harare. From this chapter the major conclusions are that the main problem associated with this rapid growth in vehicle population in the major cities is increase concentration of line and area emission sources due to traffic congestion at peak times. The stock of vehicles is quite old and they lack emission control equipment. Major constraints and limitations are observed in the current pieces of legislation. For example, the current Atmospheric Pollution Prevention Act (1971) does not require vehicles to be fitted with emission control equipment. Most of the vehicles use leaded fuel resulting in emission of the dangerous lead particulate matter in the urban areas. There is therefore an urgent need to design and implement air pollution control measures in the urban areas of the country. It is also critical to develop smart and eco-friendly transportation infrastructures so as to achieve sustainable urban communities. The integration of transportation, land use and decision making is also critical in the achievement of smart transport.

Indicators development to support intelligent road infrastructure in urban cities

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.

Over the past few decades, intelligent transportation systems (ITS) have emerged as an effective way to improve the performance of transportation systems. ITS provide innovative services, enhance travel safety, provide travellers with more choices, and make transportation systems more efficient. Multi-agent systems (MAS), which define autonomous interacting entities, are suitable for modelling distributed and intelligent systems in general and ITS in particular. This paper provides an in-depth review of multi-agent systems applied to Advanced Public Transportation Systems (APTS), a subclass of ITS dedicated to managing public transportation networks. We carefully analysed 38 papers in this study, published in 19 journals during 31 years (1990–2020). We perform a synthetic analysis of the trends in this domain and a qualitative analysis focused on multi-agent systems’ dimensions and properties. We show that the MAS approach is well suited to the real-time management of disturbances thanks to their delegation process, and their pro-activeness and autonomy properties.

With the rapid development of the transportation industry, Intelligent Transportation System (ITS) tries to adapt to industry changes through constructing new organizational forms, management methods, and incentive mechanisms. However, many new governance issues have arisen due to the transportation system’s complexity, diversity, and uncertainty. DAO(Decentralized autonomous organization) enabled by blockchain and smart contracts are regarded as effective methods to solve the organizational governance problems for complex systems. Therefore, this article analyzes the main issues currently faced by ITS. Then, this paper proposed a 6-layer DAO structure framework for ITS and discussed its key research issues. Finally, a case study for the Macau transportation system is carried out, and further research directions are proposed. The DAO-based transportation system will represent the future trend of ITS development. This paper aims to motivate more discussion for this new direction and provide helpful guidance and reference for future research work.

Chapter 20 - Sensing and monitoring of smart transportation systems

IBMAS (Identity-based message authentication systems) is a viable option for safeguarding data transfers in Internet of Vehicles (IoV) settings. We cover the state-of-the-art in IBMAS for IoVs in this book chapter, including their goal, techniques, results, contributions, implications, limits, and relevance. The goal of this chapter is to give academics and practitioners an overview of IBMAS for IoVs, including their design and implementation, to assist them in understanding the potential benefits and limits of these systems. We provide a study of existing IBMAS for IoVs in the literature, assessing their features, performance, and security aspects. We also propose a technique for assessing the efficacy of IBMAS for IoVs, concentrating on essential parameters such as message authentication performance, scalability, and attack resistance. The results of our test show that IBMAS can offer excellent message authentication with little overhead in IoV situations. Our addition to the literature is a thorough examination of IBMAS for IoVs, including their benefits and drawbacks, as well as a practical approach for assessing their performance and security qualities. We also talk about the consequences of IBMAS for IoVs, such as how they could affect data security and privacy in smart transportation systems. However, IBMAS has significant disadvantages, such as its reliance on a trusted third party and the risk of key exposure. Notwithstanding these limitations, IBMAS is important for IoVs because of its capacity to offer efficient and secure message authentication, which is crucial for the safe and dependable functioning of IoV systems. Finally, this chapter is an excellent resource for academics and practitioners interested in IBMAS for IoVs, covering their design, implementation, and assessment, as well as their implications for data security and privacy in intelligent transportation systems.

As a strategic step toward sustainable mobility, this study examines the integration of Enterprise Architecture (EA) into an Intelligent Transportation System (ITS) utilizing the TOGAF framework (The Open Group Architecture Framework). Given the escalating intricacy of the transportation system, the primary emphasis is on the synergy between ITS and EA, which is organized and structured using TOGAF. This study aims to determine how the TOGAF framework can aid in developing a more sustainable and efficient transportation system by facilitating the integration of EA and ITS. This methodology is grounded in qualitative analysis, particularly an exhaustive review of the relevant literature. This literature review identifies current trends and best practices regarding applying TOGAF for EA integration in ITS. Research shows that transportation service operational efficiency and effectiveness are enhanced when EA and ITS are integrated using TOGAF, improving coordination, resource management, and strategic decision-making. This, in turn, supports sustainable mobility.