Growing use of motorised individual transport has become an emerging challenge for most European societies and a threat to their environment, economy and citizens’ health (Möser et al., 2008). In particular, road transport accounts for the highest proportion (72% in 2019) of overall transport greenhouse gas emissions. A major source of emissions from road transport is traffic congestion (Smit et al. 2008). TomTom (2022) estimates that 15% of total CO2 emissions in London, 13% in Paris and 10% in Berlin come as a result of inefficient traffic and congestion. Congestion appears when smooth free-flow traffic conditions deteriorate due to increased demand or reduced capacity (Smit et al., 2008). Increased number of acceleration and deceleration events during stop-and-go traffic lead to the 40% increase in CO2 emissions when compared to vehicle moving at constant speed (Barth and Boriboonsomsin, 2008). Congestion is a complex phenomenon and a fundamental challenge in traffic management. It can be recurrent on nonrecurrent event, may occur in result of increased demand, traffic incident, extremely bad weather or due to road works, and thus, the spatio-temporal influence and effects it brings may be different depending on congestion source, type or location. Precongestion conditions may be also of particular importance. Scientific knowledge and methods are essential in recognising congestion patterns and managing the congestion. Big transportation data may be remarkably useful in this context, for detecting congestion event, recognising its source, predicting its effects, or to effectively manage the congestion with available traffic management tools. Gdansk Tech together with Royal Institute of Sweden plan to join their forces and expertise (AI, big data, traffic engineering) in the project in order to jointly address the issues on what causes traffic congestion, how congestion events may be identified in the data and predicted in the future, what are the effects of congestion and what countermeasures are the most effecting in mitigating the effects. The seed money project will allow the partners to strengthen cooperation, develop a common and detailed project concept and build a consortium around it. The benefits to Gdansk Tech include increased cross-border cooperation, experience and know-how exchange with Swedish partner, and exploring new areas of activity (in terms of AI and using the most of big data opportunities in transportation research works).