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 AI’s disruptive impact on road transport and its potential for ongoing innovation and improvement in the pursuit of a smarter, more efficient transportation network.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Revolutionizing Transportation System Using Artificial Intelligence Technique

    Sony, Anuj Kumar / Bhushan, Bharat / Astya, Rani | IEEE | 2023


    Role of Artificial Intelligence in Revolutionizing the Automotive Industry: A Review

    Verma Jai Krishan / Kanday Rajeev / Gupt Sachin | DOAJ | 2024

    Free access

    Smart Traffic Systems: Revolutionizing Road Transport with AI and Image Processing

    Bindu Madavi, K. P. / Krishna Sowjanya, K. / Sardar, Tanvir H. et al. | Springer Verlag | 2025



    Revolutionizing Transportation: Advancements in Robot-Assisted Mobility Systems

    Usmani, Usman Ahmad / Happonen, Ari / Watada, Junzo | Springer Verlag | 2023