AET Transport and Mobility Forum

The integration of Artificial Intelligence (AI) into sustainable urban mobility and transport development represents a transformative paradigm shift, redefining how cities approach efficiency, equity and environmental stewardship. By harnessing AI’s computational power and predictive capabilities, stakeholders can unlock unprecedented opportunities to optimise traffic flow, reduce congestion and democratise access to mobility services. Innovations such as autonomous vehicles (AVs), AI-driven traffic demand management systems leveraging big data and e-micromobility platforms exemplify this revolution, enabling smarter resource allocation, reducing carbon footprints and bridging gaps in last-mile connectivity.

However, the rapid adoption of these technologies demands rigorous interdisciplinary scrutiny. Beyond their technical promise, AI systems raise critical questions about economic viability (cost-benefit trade-offs for public infrastructure), social equity (e.g. winners and losers of using AVs), ethical dilemmas (data privacy in surveillance-driven systems) and environmental trade-offs (energy consumption of AI models versus emissions saved). Moreover, as AI permeates public discourse, a pressing challenge emerges: How do we disentangle its substantive potential from hyperbolic marketing narratives? Is AI merely a buzzword repackaging incremental advancements, or does it herald a genuine leap in transport innovation? This session will interrogate these questions, exploring both the transformative power and limitations of AI, including emerging tools, such as Large Language Models (LLMs), which offer novel opportunities for real-time decision-making, but also amplify risks such as disinformation and over-reliance on opaque algorithms.

The purpose of this session is primarily to foster a nuanced understanding of AI’s role in transport, bridging theory and practice through case studies from academia and industry. Speakers will dissect real-world applications, such as AI-optimised public transit networks, equity-focused micromobility schemes, and LLM-assisted traffic management pilots, etc. Attendees need no prior technical expertise and the discussion is designed for policymakers, practitioners, urban planners, lecturers and students who are seeking to critically engage with AI’s role in shaping mobility systems and transport futures.

Through these lenses, the session will highlight case studies demonstrating how AI can play a significant role in the field of mobility and transport systems. By synthesising cutting-edge research and practical insights, this dialogue aims to chart a path toward sustainable mobility and transport development that are not only smarter and greener but also socially just.