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This paper describes an integrated approach for modeling transport infrastructure and optimising transport in urban areas. It combines the benefits of a multi-agent system, real time traffic information, and traffic forecasts to reduce carbon-dioxide emissions and offer flexible intermodal commuting solutions. In this distributed approach, segments of different modes of transport (e.g. roads, bus/tram routes, bicycle routes, pedestrian paths) are simulated by intelligent transport agents to create a rich multi-layer transport network. Moreover, a user agent enables direct interaction between commuters’ mobile devices and the multi-agent system to submit journey requests. The approach capitalises on real-time traffic updates and historical travel patterns, such as CO₂ emissions, vehicles’ average speed, and traffic flow, detected from various traffic data sources, and future forecasts of commuting behaviour delivered …