07 May 2025

The Athens ACUMEN Workshop held on February 3, 2025, aimed to explore how and when AI can be integrated into traffic management systems. Fifteen stakeholders participated, including representatives from OSY SA Road Transports SA, GEFYRA, the Municipal Police of Athens, the City of Athens (Departments of Road Management and Sustainable Mobility), and FedEx. Two members of the ACUMEN reference group—the Cluster for Logistics (Luxembourg) and the Ministry of Economy (Luxembourg)—also contributed to the discussions.

The workshop was part of a broader series organised within the ACUMEN project, which is developing a governance and regulatory framework, as well as a decision support tool, to guide policy makers in integrating artificial intelligence (AI) and machine learning (ML) into transport management systems. To ensure practical relevance, ACUMEN conducted four workshops with its pilot cities – Luxembourg, Athens, Helsinki and Amsterdam – bringing together national and local traffic management stakeholders.

These workshops provided an insight into existing traffic management systems and facilitated the exchange of best practices. They also helped to identify the practical needs and regulatory gaps that AI integration presents. Feedback from participants will be used to refine the governance framework and decision-making tool to ensure its applicability in real transport systems. The final tool will be shared with stakeholders to demonstrate the benefits of AI-based traffic management and encourage cities to adopt AI-driven solutions for long-term mobility improvements.

Athens faces persistent traffic congestion, particularly at major intersections. Another challenge is institutional fragmentation and limited coordination between national, regional, and local authorities, as well as law enforcement agencies. The lack of a centralised data management model further complicates decision-making, while real-time monitoring tools lack predictive capabilities, making proactive congestion management difficult. Inefficiencies in freight and last-mile delivery compound the problem.

The ACUMEN pilot in the Athens Metropolitan Area aims to design and test an integrated mobility platform to support traffic management and decision-making. Focusing on private cars, last-mile delivery vehicles, and public transport, the platform will serve transport authorities by combining data from various sources, including terrestrial and aerial inputs. Using AI-powered forecasting and predictive analysis, the platform will feature a visualisation tool and decision support system to help authorities better understand and manage multimodal mobility across the region.

Discussions during the workshop highlighted how AI could improve traffic management. AI-powered adaptive signals could optimise traffic flow, while real-time incident detection and predictive analytics could help anticipate congestion before it occurs. AI could also enhance multimodal traffic management by improving coordination between public transport, pedestrians and private vehicles. The integration of multiple data sources through AI-driven decision support systems was identified as a critical solution for improved monitoring and response efficiency.

The workshop also addressed regulatory and governance challenges. While EU and national transport regulations provide some guidance, there is little clarity on AI-specific governance in traffic management. Concerns about public acceptance, data security and privacy compliance underlined the need for a clear regulatory framework to mitigate risks.

Stakeholders had mixed views on AI governance. Some argued that national and local governments should take the lead in ensuring regulatory compliance and public accountability, while others saw private technology companies as better placed to drive AI adoption due to their technical expertise. A few participants argued for independent regulatory bodies to oversee transparency and ethical use of AI. The most widely supported approach was collaborative governance, where public authorities, private companies, civil society and academia work together to manage AI integration.

Recommendations include:

• Defining clear roles and responsibilities.
• Developing AI-specific regulations that address ethics, privacy and cybersecurity.
• Ensuring that AI-driven decisions remain interpretable and subject to human oversight.
• Increasing public awareness and engagement to build trust and address concerns about AI in urban mobility.
• Establishing a centralised data-sharing platform to improve coordination between traffic management authorities and private operators, thereby increasing overall efficiency.