Intelligent Transport Systems (ITSs) Meet Generative Artificial Intelligence
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".
Deadline for manuscript submissions: 20 April 2025 | Viewed by 6593
Special Issue Editors
Interests: network survivability; sustainable computing and communications; trust computing
Special Issues, Collections and Topics in MDPI journals
Interests: computer networks; distributed systems; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The evolution of Intelligent Transport Systems (ITS) represents an amalgamation of cutting-edge technologies integrating data analytics, advanced connectivity, and automation to fundamentally redefine the landscape of transportation networks. This transformation spans a diverse array of applications, including adaptive traffic control mechanisms, real-time predictive maintenance protocols, and the integration of interconnected vehicles. The overarching goal of ITS is to optimize traffic flow dynamics, mitigate congestion bottlenecks, and foster the development of sustainable mobility solutions. By leveraging intricate data-driven insights and innovative automation, ITSs endeavour to enhance transportation efficiency, reinforce safety measures, and build an ecosystem that adapts dynamically to evolving travel demands.
Concurrently, the frontier development in generative artificial intelligence (AI) encapsulates a realm where algorithms and models exhibit the unprecedented capability to learn intricate patterns from data and autonomously generate novel content, designs, or solutions. This paradigm shift is manifested through sophisticated techniques such as generative adversarial networks (GANs), variational autoencoders (VAEs), and deep reinforcement learning architectures. Generative AI stands poised at the precipice of transportation innovation, offering unparalleled prospects for intelligent design, simulation, optimization, and decision making within the transportation domain. The integration of generative AI with ITSs heralds a groundbreaking convergence, unveiling new horizons for unprecedented advancements in transportation technology. This juncture not only augments the prospects of intelligent transportation solutions but also paves the way for the exploration of uncharted territories within the realm of mobility.
The fusion of ITS with generative AI presents an open canvas for researchers and practitioners to embark on pioneering investigations and contribute groundbreaking insights to the transportation domain. Novel research endeavours are poised to explore and harness the potential of this convergence to unravel innovative methodologies for addressing complex challenges within transportation networks, which is creating intelligent infrastructures and vehicles offering enhanced, intuitive, safe, and personalized in-car experiences. Researchers are invited to dive into unexplored realms, devising AI-driven solutions that transcend conventional paradigms. This Special Issue invites submissions that showcase the synergistic interplay between ITSs and generative AI, fostering groundbreaking advancements that redefine the future of transportation systems. Contributions that delineate novel approaches, address challenges, and unveil transformative insights into this converging frontier are eagerly anticipated.
Possible Topics: We invite researchers and practitioners to submit original research, reviews, and perspectives on, but not limited to, the following topics:
- Distributed architectures and federated learning approaches to train generative AI models;
- Generative models for traffic predication and optimization;
- Generative AI-enabled predictive maintenance for transportation infrastructure;
- Generative AI-enabled autonomous vehicles and their integration into ITS frameworks;
- Generative AI applications in designing adaptive transportation systems;
- Ethical considerations in deploying generative AI-driven transportation solutions;
- Legal implication and liability in generative AI-enabled transport;
- Security and privacy challenges in interconnected and generative AI-enabled ITS environments;
- Human–vehicle interactions through generative AI;
- Creative content generation for in-vehicle experiences;
- Innovative applications of generative AI in augmenting public transportation, e.g., bus, tram, train, ferry experiences;
- Generative AI-driven solutions for multimodal transportation and seamless integration;
- The sustainability, e.g., carbon footprint studies on generative AI-enabled intelligent transport systems;
- Curriculum development for AI in transportation to train future professionals in the integration of generative AI within Intelligent Transport Systems.
Dr. William Liu
Dr. Xun Shao
Dr. Aniket Mahanti
Guest Editors
Manuscript Submission Information
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Keywords
- intelligent transport system
- generative artificial intelligence
- large language models
- distributed language models
- vehicular Internet of Things
- edge computing
- cloud computing
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