Travel behaviour has been an area of great interest to practitioners and researchers ever since forecasting user choice was identified as crucial in the planning and management of transport systems. Travel behaviour arising from the choices of individuals is perhaps the most significant determinant of performance of transport systems and effectiveness of transport schemes. Realising that individuals’ travel behaviour and choices do not necessarily lead to economic, social and environmental wellbeing, governments all over the world have been taking measures to change travel behaviour for the benefit of society – usually by regulating the transport market, reform pricing to improve efficiency, or (more recently) changing attitudes towards transport alternatives.

Much of the behavioural theories in transport context are based on the assumption the individual traveller is a ‘homo economicus’, a rational economic human beings who, through choice-making, maximise her utilities. On the other hand, recent empirical studies provide much evidence that in real life the behaviour of travellers is typified by bounded rationality (‘homo psychologicus’). It has been argued that travellers’ limited cognitive resources have a strong effect on their travel-choice behaviour.

Inspired by the works of cognitive psychologists (such as Tversky & Kahneman) and behavioural economists (such as Thaler & Sunstein) Dr Avineri and his colleagues tested some of the paradigms in travel behaviour and developed alternative models of travel-choice behaviour that can incorporate awkward but important aspects of travel behaviour. It was found that while travellers’ choices can not be anticipated in a standard economic framework, they can be explained and predicted by cognitive psychology models. Moreover, it opens the opportunity to change travellers’ behaviour towards better alternatives - in a way that does not limit their freedom of choice (or, as it is fashionable to say, people are ‘nudge-able’). The paper provides theoretical background, empirical findings and potential applications in areas such as demand management, travel information systems, travel plans and traffic calming.