Transport systems as complex systems they are, share certain characteristics but not necessarily in full. The highway systems, for example, have all, others like the railway networks but a few.
- Adaptability: The agents adapt their behaviors in response to changes in their environment. This occurs both between transport companies, and between travelers and the public authorities that regulate the sector.
- Self-organization is a process where some form of overall order or coordination arises out of the local interactions between smaller component parts of an initially disordered system. Frecuently the process of self-organization in transportation are spontaneous, and there are not controlled by any auxiliary agent outside of the system.
- Some transport systems spontaneously and consistently revert to recognizable dynamic states known as attractors. While they might, theoretically, be capable of exhibiting a huge variety of states, in fact they mostly exhibit the constrained attractor states.
- The transport systems can have abrupt transitions of a wide range of intensities. For a system that is in a self-organised critical state, the magnitude of the next transition is unpredictable, but the long-term probability distribution of event magnitudes is a very regular known distribution. This property is named self-organized criticality.
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- One of the earliest known features of complex systems was chaotic dynamics, characterized by extreme sensitivity to initial conditions. This also occurs in transport systems. There is a strong path dependence on design of networks.
- Transport systems are nonlinear because they does not satisfy the superposition principle – meaning that the output of a nonlinear system is not directly proportional to the input.
- In transportation we can observe phase transitions when the system changes suddenly and dramatically (and, often, irreversibly) because a “tipping point”, or phase transition point, is reached.
- Power labs is a functional relationship between two quantities, where a relative change in one quantity results in a proportional relative change in the other quantity, independent of the initial size of those quantities: one quantity varies as a power of another.
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The SCCS research group has a wide experience in this field with several projects made with public and private partners.
Ongoing projects
 Network dynamics is an emergent scientific field that brings together traditional social network analysis (SNA), link analysis (LA), social simulationand multi-agent systems (MAS) within network science and network theory. The ‘Network dynamics’ project of SCCS aims to analyze the evolution of transport networks in Spain applying these techniques. |
 Temporal networks is an extension of complex networks as a modeling framework to include information on when interactions between nodes happen. SCCS is currently working on developing global temporary networks for commercial airlines. |
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Other projects
Publications
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The airline industry is changing rapidly. The many challenges and opportunities that airlines face every day make it one of the most competitive industries of all. Airlines’ management teams are invariably compelled to readapt their policies to the customer preferences, and the ever-changing “external factors” impose severe constraints to growth and competitiveness of airlines. Not surprisingly, complexity has seized an industry where value is increasingly more difficult to create and taking the benefits out of it, a question of survival (IATA 2014). Valueinairlines is an industry-oriented research project that pursues the modelling of the airlines’ value creation engine on novel expert data. The use of “non-traditional”, network-based computational techniques, allow researchers and practitioners simulate real-life value creation scenarios and anticipate airlines’ performance. (