Modelling uncertainty in traffic and transportation systems

This special issue ‘Modelling uncertainty in traffic and transportation systems’ is based on selected papers presented at the 11th Meeting of the Euro Working Group on Transportation (EWGT) held in Bari, Italy, 2006 (Proceedings of the EWGT2006 Joint Conference 2006). The EWGT on Transportation has been paying attention to the topic of uncertainty in this field (Proceedings of the 9th Meeting of the EWGT and 13th Mini-EURO Conference 2002, Dell’Orco et al. 2005) since transportation is a complex system in which components and relationships are more or less dominated by uncertainty. Such uncertainty may be related to human behaviour (i.e. users, planners, decision makers, social interaction etc.), environment (i.e. available data, economic and political issue, land use, transport supply and technologies, local issues and habits, etc.) and other special events (i.e. natural disaster, emergency issue, exhibitions, etc.). Thus, in order to provide more effective and reliable transport problem solutions, transport system analysts and engineers have to face the different sources of uncertainty when modelling transportation systems and its main components, such as travel demand, transport supply, interaction between demand and supply and relevant analysis and assessments. Considering that uncertainty lying in transport system analysis is strictly linked to the concept of reliability of the models and then of the transport planning process itself, this topic has been drawing the attention of many researchers who have been trying to explicitly represent the uncertainties in the traffic models they have been proposing by following different theoretical approaches and paradigms. Such interest is demonstrated by the 12 papers that were submitted in response to the call for papers for this special issue and, after a peer reviewing process, we are pleased to present five accepted papers. The authors present different approaches facing the uncertainties lying in transportation planning and operations by considering various aspects of transportation and traffic system modelling. The uncertainty relevant to users’ choice behaviour is discussed in Sunitiyoso et al. and in Zito et al., where transport system perception is modelled by different approaches. In the first one, authors investigate the potential of incorporating social interaction and social learning in modelling travellers’ change of individual choice behaviour under uncertainty. The type of uncertainty considered in this paper is the uncertainty of transportation users about the choices of other travellers and they show how to incorporate these aspects in travel behaviour modelling. Two methods of study, laboratory and simulation experiments, are used to demonstrate that the effect of social information on users’ behaviour is strictly related to social learning type. The paper by Zito et al. is relevant to the effects of Advanced Traveller Information Systems (ATIS) on transit users behaviour. In particular, the study turns attention to the