EUNOIA (Evolutive User-centric Networks for Intraurban Accessibility) is a research project funded under the European Union's Seventh Framework Programme ICT Programme. The goal of EUNOIA is to take advantage of the opportunities brought by smart city technologies and the most recent advances in complex systems science to develop new urban models and ICT tools empowering city governments and their citizens to design better mobility policies. The project started in October 2012 and will run for two years.

EUNOIA Position Paper: Urban Models for Transportation and Spatial Planning. State-of-the-art and Future Challenges


Smart cities: opportunities for improved urban models and decision support tools

To tackle the challenge of sustainable urban mobility, urban planners need models, decision support tools, and input data allowing the assessment of policies and their resulting effects. Urban models serve various purposes: first, models help achieve an enhanced understanding of urban dynamics (in an explanatory role); second, they enable virtual experimentation allowing the prediction of the impact of new infrastructures, technologies, or policies (in a predictive role); finally, models are powerful tools to facilitate participatory processes for collaborative decision making (in policy and design roles).

Cities have been treated as systems for several decades, but only recently has the approach changed from aggregate equilibrium systems to complex, evolving systems of systems. Different types of urban models have been developed, from the static and aggregate land use-transportation interaction (LUTI) models first developed in the 1960s, to recent activity-based microsimulation models which seek to represent cities in more disaggregate and heterogeneous terms. To fully support the assessment of urban mobility policies in terms of a comprehensive set of economic, social, and environmental sustainability indicators, further research is needed along three main axes:

  1. Data collection. The development and validation of improved models critically relies on the availability of data. Data collection efforts have traditionally been focused on trip data (origin-destination, travel time, mode, etc.), but there is still a lack of appropriate data on factors determining mobility behaviour, such as attitudes and lifestyle, which are particularly important, e.g., for developing demand management concepts aiming to influence mobility decisions.  
  2. Theoretical research. On the demand side, many questions are still open, such as the activity patterns underlying human travel behaviour; the social acceptance of transport systems and mobility policies; or the relationship between land use and transport demand, and how to quantify the contribution of transport infrastructure to land value. As for the transport supply side, particularly interesting are questions such as the impact of ICT-based services; new services with the potential to improve urban mobility, e.g. how to make car and bike sharing schemes more appealing; intermodality; or the alternatives to private, fossil fuel-based car such as electric and hybrid.
  3. Link between modellers, decision makers, and societal actors. The use of system models in policy making and planning is very heterogeneous. Many cities do not use any quantitative models at all; among the cities using simulation models, traditional LUTI models are still the most applied. The use of more advanced, state-of-the-art models based on complex systems modelling techniques (particularly of agent-based models) is still scarce, and in many cases the potential users do not have the skills to use such models or are not convinced of the benefits. To bridge this gap, the development of the models needs to be user-driven and be accompanied by user-model interaction methodologies facilitating a smooth integration of the models into the decision-making processes.

The term ‘smart city’ has become widely spread in the last few years. Even if still not clearly delimited, the smart city is now generally understood as a holistic concept encompassing not only the use of modern technology (including transport or energy technologies, in addition to ICT), but also the investment in human, social, and environmental capital, to create sustainable development and high quality of life. When it comes to urban models and policy support tools, the increased penetration of ICT, the rise of the Big Data movement, and the emergent concept of smart cities open new opportunities to make progress in the three directions previously identified:

  1. Modern ICT, such as smart phones, e-transactions, Internet social networks, or smart card technologies, allow the automatic collection of spatial and temporal movement data that can complement and enhance the data collected by using traditional methods (census data, travel surveys). Yet, the collected data have to be analysed, making it necessary to develop new data mining techniques in order to obtain useful knowledge about urban mobility patterns and improve our understanding of cities.
  2. This improved understanding can in turn inform the modelling of the mechanisms behind observed mobility patterns, helping develop new theory and better models for the quantitative assessment of different scenarios and policy options.
  3. Finally, ICT opens the door to the development of new tools which can help capture the inputs from societal actors (e.g. algorithms for reconstructing citizens’ opinion from data resources distributed throughout the Internet), support an increased participation of citizens (e.g. through applications that allow citizens to monitor and report the system status in real time), and enable collaborative, multi-stakeholder policy assessment and decision making processes.


Project objectives

The objectives of EUNOIA are the following:

  1. to investigate how new data available in the context of smart cities can be exploited to understand mobility and location patterns in cities;
  2. to characterise and compare mobility and location patterns in different European cities;
  3. to improve the understanding of the interdependencies between social networks and travel behaviour;
  4. to enhance urban land use and transportation models, by integrating the role of the social network and new models of joint trips and joint resource use into state-of-the-art agent-based models;
  5. to develop useful policy interfaces and appropriate methodological procedures for the use of simulation tools in multi-stakeholder, collaborative assessment of urban transport policies;
  6. to apply the new models and methodologies to several case studies of interest for policy makers.




EUNOIA will analyse different sets of heterogeneous data, including traditional data sources (census data, travel surveys) as well as new data sources available through smart technologies.  

Data from traditional well-proven sources will be accessible online or available upon request, such as population, employment, land uses, housing census data, or travel surveys. EUNOIA will rely on the involvement of the local authorities of Barcelona, London, and Zurich, which will support the project by providing additional data.

The EUNOIA Consortium has reached an agreement with Banco Bilbao Vizcaya Argentaria, S.A. (BBVA) to analyse data on credit card payments in Barcelona. The Consortium has also reached an agreement with Telefónica to analyse data on mobile phone records.

Data from Internet social networks will be retrieved and mined with the aim to provide new insights on travel decisions and trip purposes, as well as on the interrelationship between the spatial distribution of the social network and mobility patterns.  

The previous data will be complemented with two surveys specifically designed for the purpose of the project, which will be run in Barcelona as a joint survey: a survey on the spatial spread of the members of social networks, and a life course survey which will address the question of to what extent life style and mobility habits are passed on or modified from generation to generation.


Characterisation of mobility patterns in different types of cities

The data sets described above will be mined with a view to discern general and local basic features of urban mobility patterns, such as the existence and organisation of centres of activity in the cities. To extract useful knowledge from the data, EUNOIA will make use of standard statistical analysis and data mining methods, as well as new spatial analysis methods recently developed in the context of network theory. 


Interaction between social networks and travel behaviour 

Social interactions are of crucial importance for realistic modelling of travel decisions. EUNOIA will investigate aspects that are still not well reproduced by existing transportation models, such as the influence of the social network on the planning of joint trips and joint resource use; peer influence on travel behaviour; or the changes in mobility induced by the changes in social relationships brought about by new ICT.


Improvement of urban transportation models 

The analysis of urban mobility patterns and their relation to the spatial structure and socio-economic characteristics, as well as the conclusions about the interrelationship between social networks and mobility patterns, will be the basis for the formulation, calibration, and testing of new models of location and travel behaviour. The new models will be integrated into comprehensive, state-of-the-art urban simulation tools, in particular MATSim (, which originates from ETH; and SIMULACRA (, a more aggregate model developed by CASA. The new models will be evaluated through three case studies carried out in collaboration with the cities of London, Zurich, and Barcelona. 


Policy interfaces and methodological procedures for collaborative assessment of urban transport policies

The project will identify the key stakeholders for urban mobility policy modelling (policy makers, interest groups, citizens’ associations, etc.) and will carry out a consultation to identify the current practices and needs in different cities around the world. The analysis of stakeholders’ expectations will be used to derive requirements for ICT tools enabling stakeholders’ collaboration in policy assessment, in particular for the development of user-friendly analysis tools allowing the interaction with the policy simulation results. This will include the development of visual interactive interfaces and data representations facilitating analytical reasoning. EUNOIA will also define a methodology for collaborative assessment of mobility policies supported by the demonstrative simulation and visualisation tools developed within the project. The proposed methodology will aim at the active participation of the policy makers and the main mobility stakeholders, and will be implemented and tested in close collaboration with the Barcelona City Council, through several workshops and policy formulation events.


Case studies

The models and methodologies developed by EUNOIA will be evaluated, refined, and validated through three case studies conducted in cooperation with the cities of London, Zurich, and Barcelona. Some examples of potentially interesting questions are: mobility pricing (road tolls, parking, public transport), such as congestion charging in central London; policies to increase the attraction of urban hubs and activity centres (e.g. traffic calming), with a view to foster a polycentric urban structure with more sustainable mobility patterns; optimisation of new, emergent transport services around the idea of providing common access to resources at a lower cost and in a more energy-efficient manner, e.g. optimisation of the location of public bikes, car sharing locations and fleet sizes, etc.; optimisation of the location of the charging infrastructure for electric vehicles; demand-side management policies to foster a sustainable use of electric vehicles; or interactions between aging, migration, and travel behaviour, including intergenerational aspects.


Eunoia Project © 2012 | Developed by the IFISC lab