21.10.2026

Environmentally Sensitive Mobility Management: Using AI to Meet the 2030 Air Quality Targets

From 2030, significantly stricter limits for nitrogen dioxide and particulate matter will apply across the European Union. This is increasing the pressure on cities and municipalities to improve air quality through targeted measures and assess the potential impact of traffic management interventions at an early stage. In her latest article in Straßenverkehrstechnik (SVT 10/2026), Lisa Schiffers, Deputy Project Manager of the research project AIAMO – Artificial Intelligence And MObility at ITS Germany e. V., explains how Artificial Intelligence (AI) and digital twins can support these efforts.

AIAMO is creating the conditions to identify potential breaches of air quality limits at an early stage and prepare appropriate countermeasures. By combining data from various sources, including traffic, environmental and weather data, it becomes possible to predict pollution levels and assess how they may develop over time and across different locations. Digital twins also enable different traffic management measures to be evaluated before implementation, taking into account their potential effects on traffic flow and air quality. This allows municipalities to implement targeted, situation-specific measures where they can contribute to improving air quality.

The research project is testing this approach under real-world conditions in the pilot regions of Leipzig and Landau in der Pfalz. The work also addresses the integration of existing systems, support for municipal decision-making and verification of the impacts actually achieved. This lays the foundation for mobility management that considers environmental impact alongside traffic safety and network performance as an operational management parameter, an approach that can also be transferred to other cities and regions.

Read the full article in the October issue of STRASSENVERKEHRSTECHNIK. (PDF)