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Many transportation companies struggle to effectively utilize the information provided by tracking technology for performing operational control. The research as presented in this paper aims to identify the problems underlying the inability to utilize tracking technology within this context. Moreover, this paper aims to contribute to solving these problems by proposing a set of design principles based on the concept of intelligent products.

The study as described in this paper adopts a design science research methodology consisting of three phases. First, a case study in a transportation company has been performed to identify the problems faced when utilizing tracking technology. Second, to overcome these problems, a set of design principles has been formulated. Finally, a prototype system based on the design principles has been developed and subjected to experimental and observational evaluation.

This paper identifies the problems associated with the utilization of tracking technology for the control of transport operations. Moreover, the proposed design principles support the development of information systems which overcome the identified problems and thereby enhance the utilization of tracking technology in a transportation context.

The commonly held perception that tracking technology will improve the ability to perform operational control does not unequivocally stand up to empirical scrutiny. While it is widely demonstrated that tracking technology is able to accurately capture the detailed operational information, it remains a fundamental challenge to transform this abundance of information into accurate and timely control decisions. This research provides a valuable contribution with respect to tackling this challenge, by identifying problems and providing solutions related to the utilization of readily available tracking technology.

In recent years, railway systems worldwide have faced challenges such as the modernization of engineering projects, efficient management of intelligent digital railway equipment, rapid growth in passenger and freight transport demands, customized transport services and ubiquitous transport safety. The transformation toward intelligent digital transformation in railways has emerged as an effective response to the formidable challenges confronting the railway industry, thereby becoming an inevitable global trend in railway development.

This paper, therefore, conducts a comprehensive analysis of the current state of global railway intelligent digital transformation, focusing on the characteristics and applications of intelligent digital transformation technology. It summarizes and analyzes relevant technologies and applicable scenarios in the realm of railway intelligent digital transformation, theoretically elucidating the development process of global railway intelligent digital transformation and, in practice, providing guidance and empirical examples for railway intelligence and digital transformation.

Digital and intelligent technologies follow a wave-like pattern of continuous iterative evolution, progressing from the early stages, to a period of increasing attention and popularity, then to a phase of declining interest, followed by a resurgence and ultimately reaching a mature stage.

The results offer reference and guidance to fully leverage the opportunities presented by the latest wave of the digitalization revolution, accelerate the overall upgrade of the railway industry and promote global collaborative development in railway intelligent digital transformation.

This chapter critically evaluates the opportunities and challenges in adopting information technology for enhancing transportation in developing countries. The conception framework emerging from this study highlights four key stakeholders and the country context in developing and integrating information technology for improving transportation in developing countries – Tech developers, Transporters, Transport Tech start-ups and Travellers. This study makes cogent theoretical contributions to the growing body of works around technological innovation, smart mobility and intelligent transport systems, albeit from a developing country perspective. This study has also emerged from managerial implications for stakeholders, especially the tech developers, transporters and transport tech start-ups. There is a need for innovative ideas to address the inherent transportation challenges in Africa, and the customers are counting on these stakeholders to make the technology readily available and accessible.

The intelligent Central Traffic Control (CTC) system plays a vital role in establishing an intelligent high-speed railway (HSR) system. As the core of HSR transportation command, the intelligent CTC system is a new HSR dispatching command system that integrates the widely used CTC in China with the practical service requirements of intelligent dispatching. This paper aims to propose key technologies and applications for intelligent dispatching command in HSR in China.

This paper first briefly introduces the functions and configuration of the intelligent CTC system. Some new servers, terminals and interfaces are introduced, which are plan adjustment server/terminal, interface for automatic train operation (ATO), interface for Dynamic Monitoring System of Train Control Equipment (DMS), interface for Power Supervisory Control and Data Acquisition (PSCADA), interface for Disaster Monitoring, etc.

The key technologies applied in the intelligent CTC system include automatic adjustment of train operation plans, safety control of train routes and commands, traffic information data platform, integrated simulation of traffic dispatching and ATO function. These technologies have been applied in the Beijing-Zhangjiakou HSR, which commenced operations at the end of 2019. Implementing these key intelligent functions has improved the train dispatching command capacity, ensured the safe operation of intelligent HSR, reduced the labor intensity of dispatching operators and enhanced the intelligence level of China's dispatching system.

This paper provides further challenges and research directions for the intelligent dispatching command of HSR. To achieve the objectives, new measures need to be conducted, including the development of advanced technologies for intelligent dispatching command, coping with new requirements with the development of China's railway signaling system, the integration of traffic dispatching and train control and the application of AI and data-driven modeling and methods.

For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the process of current hazardous materials transportation management, this paper aims to construct the framework of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment.

The system takes the intelligent connected vehicle as the main supporter, integrating GIS, GPS, eye location, GSM, networks and database technology.

By analyzing the transportation characteristics of hazardous materials, this system consists of five subsystems, which are vehicle and driver management subsystem, dangerous sources and hazardous materials management subsystem, route analysis and optimization subsystem, early warning and emergency rescue management subsystem, and basic information query subsystem.

Hazardous materials transportation safety management system includes omnibearing real-time monitoring, timely updating of system database, real-time generation and optimization of emergency rescue route. The system can reduce the transportation cost and improve the ability of accident prevention and emergency rescue of hazardous materials.

This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.

Developments regarding the use of artificial intelligence (AI) in transportation systems, one of the important stakeholders of tourism, are remarkable. However, no review thus far has provided a comprehensive overview of research on AI in transportation systems.

To fill this gap, this study uses the VOSviewer software to present a bibliometric review of the current scientific literature in the field of AI-related tourism research. The theme of AI in transportation systems was explored in the Web of Science database.

The original search yielded 642 documents, which were then filtered by parameters. For publications related to AI in transportation systems, the most cited documents, leading authors, productive countries, co-occurrence analysis of keywords and bibliographic matching of documents were examined. This report shows that there has been a recent increase in research on AI in transport systems. However, there is only one study on tourism. The country that contributed the most is China with 298 studies. The most used keyword in the documents was intelligent transportation system.

The bibliometric analysis of the existing work provided a valuable and seminal reference for researchers and practitioners in AI-related in transportation system.

In this paper, an intelligent information assisted communication transportation framework (II-CTF) has been introduced to reduce congestion, data reliability in transportation and the environmental effects.

The main concern of II-CTF is to mitigate public congestion using current transport services, which helps to improve data reliability under hazardous circumstances and to avoid accidents when the driver cannot respond reasonably. The program uses machine learning assistance to predict optimal routes based on movement patterns and categorization of vehicles, which helps to minimize congestion of traffic.

In II-CTF, scheduling traffic optimization helps to reduce the energy and many challenges faced by traffic managers in terms of optimization of the route, average waiting time and congestion of traffic, travel, and environmental impact due to heavy traffic collision.

The II-CTF definition is supposed to attempt to overcome some of the problems of the transportation environment that pose difficulties and make the carriage simpler, safer, more efficient and green for all.

A fundamental concept of the smart city is to get the right information at the right place to make city-related decisions easier and quicker. The main goal of supply chain management (SCM) systems is to enhance the supply chain process for delivering the identified products to customers correctly in distributed organizations. In addition, new IT infrastructure such as cloud-based systems and internet of things (IoT) have changed many organizations and firms. Hence, this study aims to assess the factors that contribute to the success of SCM systems.

In this paper, the usage of urban knowledge, urban intelligent transportation systems and IT infrastructure was considered as a key factor for the success of SCM systems. For assessing the features of the model, a comprehensive questionnaire was designed. The survey questionnaires were sent to critical informers who are practical heads associated with SCM and urbanism. Of these, 315 usable responses were received, resulting in a response rate of 82.03%. The data were examined using Smart-PLS version 3.2 and IBM SPSS version 25.

The obtained results showed the high strength of the proposed model. This study found that the impact of urban ITS (safety, accessibility, information management and flexibility) is important to the success of supply chain management systems. Another important finding is that the cloud-based system (cloud security, resource virtualization, on-demand self-service and scalability) has a very important role in the success of supply chain management systems. The finding showed that the effect of IoT service variable (commercialization, mobility features, infrastructure capabilities and security and privacy) on the success of supply chain management systems is significant and positive. The findings also showed that urban knowledge (usage skills, awareness, experience and knowledge sharing) is viewed as a significant factor in the success of supply chain management systems.

The inductive nature of research methodology has introduced limitations on the generalizability of results. Therefore, it is recommended to examine the validity of this research model in other supply chains.

The statistical results support the crucial role of urban knowledge, urban intelligent transportation systems, IoT services and cloud-based systems. Therefore, aspects relating to these factors must be the focus of attention of any distributed organization in their endeavor to develop supply chain management systems. Implementing cloud based IoT through accurate and timely availability of information, can predict forecasting and planning processes, resources, logistics and support, service management and spare parts and many sub-processes in the supply chain. These technologies allow organizations to invest in manufacturing and operating processes rather than paying for the software section, which will generate more cash flow.

One of the most crucial and fundamental parts of an organization’s management is the supply chain management. The department is responsible for coordinating all units from the initial stages, such as supplying materials to the final stages, such as delivery and after-sales service. Comprehensive and credible information platforms are essential for managing a supply chain. Therefore, it is important to use integrated information systems such as IoT, cloud computing, intelligent transportation systems and more in this part of the organization management. Covering this information in a timely and accurate manner will facilitate the process and make the process more transparent. For this purpose, a model is needed to determine the relationship between technologies and supply chain management, which this study has provided a comprehensive model.