This paper aims to review variables and behavioural theories originating from social and environmental psychology as applied to transport research, to better understand decision-making mechanisms, information processing and modal choice. The first section provides an overview of the main psycho-social variables which explain behaviour and, notably, pro-environment behaviour. The analysis shows the relations among variables, highlighting some potential cause-effect mechanism or, at least, the influence that such variables can have on behaviour. Furthermore, the strengths and weaknesses of using psycho-social variables to predict travel behaviour are discussed. Such analysis feeds the section related to the behavioural theories. These are reviewed with a focus on potential application to transport sector, showing the would-be added value of introducing a socio-psychological approach in the current vision, focused on stochastic models based on maximisation of personal utility. To this end, attention is paid to the data collection and analysis, basic for any models and even more challenging to collect when they deal with personal characteristics of individuals. Finally, the concept of attitude and intention is discussed, opening the doors between disciplines to overcome the attitude-behaviour gap.

This paper aims to define an algorithm capable of building the origin-destination matrix from check-in data collected in the extra-urban area of Torino, Italy, where thousands of people commute every day, using smart cards to validate their travel documents while boarding. To this end, the methodological approach relied on a survey over three months to record smart-card validations. Peak and off-peak periods have been defined according to validation frequency. Then, the origin-destination matrix has been estimated using the time interval between two validations to outline the different legs of the journey. Finally, transport demand has been matched with existing bus services, showing which areas were not adequately covered by public transport. The results of this research could assist public transport operators and local authorities in the design of a more suitable transport supply and mobility services in accordance with user needs. Indeed, tailoring public transport to user needs attracts both more customers and latent demand, reducing reliance on cars and making transport more sustainable.

The paper aims to define the new operational requirements and procedures to allow the Gruppo Torinese Trasporti (Torino public transport company) to implement mandatory validation without negative impacts on both the company and the users. To this end, a four-step methodology has been put forward: a) choice of the reference route; b) sampling plan and data collection; c) data analysis design and model specification and d) definition and analysis of future scenarios. Attained results show an increase of commercial speed from 1.5% to 14.5%, and an increase of the proportion of total dwell time on total trip time from 1 to 13 points. The most unfavourable situation for the company would be banning people from boarding the bus/tram through any door (the case today). Indeed, it would require an increase of trips in the morning peak hour in order to maintain the same time interval at bus stops. However, the impact on passengers’ travel time is non negligible since total vehicle trip time shows a rise of up to 10 minutes during weekends shifts (from 62 minutes in the current situation to 72 minutes for the worst case scenario). Thus, the present system limits the outcomes negatively for the users in terms of waiting time. However, a change could lead to such positive consequences as fuller passenger cooperation to validate tickets/passes and a more ordered boarding, thus reducing fraud and improving the image of the company.