The complexity of urban transport system makes it difficult to understand the impact of both the macroscopic transport policy decisions by the authorities and the microscopic travel decisions made by the general public. This is because the objectives of the travelling indivisual are defined in terms of journey time, comfort and punctuality while the strategic objectives are defined in terms of urban sustainability, environmental impact, etc. which translate into promotion of socially responsible (altruistic) behaviours. An attempt to quantify the relationship between the two perspectives using standard mathematical programming techniques proved to be excessively complex. However, the novel perspective of granular modelling may provide a framework in which to capture these complex phenomena. In particular, the formulation of the relationship as a granular game could provide a generic approach to optimisation of problems defined at various levels of abstraction (granulation).
The challenge of understanding altruistic (socially responsible) behaviour in the context of traffic and transportation systems is a specific manifestation of a more general challenge identified in socio-biology (Wilson, 1975). Gintis (1995) gives the definition of the altruism as follows: an altruist is an agent who takes actions that improve the fitness or material well-being of other agents when more self-interested actions are available. In transportation systems the choice of public transport or cycling/walking alternative over the use of a private car can be seen as a manifestation of altruism. Of course, from the individual’s perspective the altruistic choice of using a less comfortable mode of transport is also informed by the knowledge of factors that are associated with the use of private cars such as fuel cost, driving stress, parking availability/cost and possible road tolls. Also there is a potential payback of an altruistic choice that includes cleaner air, less busy and safer roads, enhanced economic sustainability of cities and social acceptability. It is clear therefore that what appears as an altruistic choice may indeed involve complex evaluation of incentives and disincentives that are defined in different domains.
The scientific aim of this research - to understand the ability to optimise decisions using game-theoretic approach in the context of systems that are described at various levels of abstraction (granulation) - will be achieved through the following: