Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Book Chapter Faculty Publications- Book Chapter Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Fahim, Md Forkan Hossain; Usman, Muhammad Mansur; Al Mahedi Hassan, Md; Sardar, Tanvir Habib; Bindu Madavi, K.P.; Venkatachalam, Nirmala Title A name given to the resource Revolutionizing Road Transportation: The Role of Artificial Intelligence in Smart and Efficient Systems Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived Springer Tracts on Transportation and Traffic;Volume;22;pp.87-107 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/978-3-031-87627-1_6" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/978-3-031-87627-1_6</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105006841073?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105006841073?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Fahim M.F.H., IniAstra Tech, Chattogram, Bangladesh; Usman M.M., Department of CS, African University of Science and Technology, Abuja, Nigeria; Al Mahedi Hassan M., IniAstra Tech, Chattogram, Bangladesh; Sardar T.H., Department of CSE, Dayananda Sagar University, Bengaluru, India; Bindu Madavi K.P., Department of CSE, Christ University, Bengaluru, India; Venkatachalam N., Department of Artificial Intelligence and Data Science, Easwari Engineering College, Chennai, India Description An account of the resource This chapter is about how AI is transforming road transportation by improving efficiency, safety, and comfort. By emphasising the importance of AI integration and moving on to main AI technologies such as machine learning (ML) for applications like traffic prediction and autonomous driving. Deep learning techniques, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs), are essential for vehicle detection and traffic analysis. Also, natural language processing (NLP) enhances traffic planning and customer support by providing real-time information and virtual assistants. We can also know from the chapter that AI applications like self-driving cars that use AI for vision and control, intelligent traffic management systems that optimise signal timings, and predictive maintenance to avoid vehicle problems. It also discusses data privacy, technology, and ethics questions, as well as demonstrates effective real-world AI deployments and future trends. Overall, the chapter emphasises AIs disruptive impact on road transport and its potential for ongoing innovation and improvement in the pursuit of a smarter, more efficient transportation network. The Author(s), under exclusive license to Springer Nature Switzerland AG 2025. Subject The topic of the resource AI-based traffic management systems; Artificial intelligence; Autonomous vehicles; Intelligent Traffic Management Systems (ITMS); Machine learning; Predictive maintenance; Road transport; Smart cities; Smart transportation systems; Traffic management Publisher An entity responsible for making the resource available Springer Science and Business Media Deutschland GmbH Relation A related resource ISSN: 21948119; Language A language of the resource English Type The nature or genre of the resource Book chapter Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online