Stefano de Luca

By Stefano de Luca, Roberta Di Pace and Facundo Storani

The gradual penetration of new transport modes and/or new technologies (advanced information systems, automotive technologies, etc.) requires effective theoretical paradigms able to interpret and model transportation system users’ propensity to purchase and use them. Along with the traditional approaches mainly based on random utility theory, it is a common opinion that numerous nonquantitative variables (such as psychological factors, attitudes, perceptions, etc.) may affect users’ behaviors. Different traditional approaches and more advanced ones (e.g. hybrid choice model (HCM) with latent variables, theory of planned behaviour, regret theory, prospect theory, etc.) may be identified and properly applied in the literature. In particular, the chapter will focus on the hybrid choice modeling with latent variables, aiming to incorporate users’ perceptions, attitudes and concerns in order to model the user’s propensity to use and the willingness to buy a new technology. The methodology overview and the results of the application at real data are discussed.

Part of the book: Transportation Systems Analysis and Assessment

By Stefano de Luca and Margherita Mascia

Mobility as a Service (MaaS) is becoming a “fashionable” solution to increase transport users’ satisfaction and accessibility, by providing new services obtained by optimally integrating sustainable modes, but also guaranteeing mass transport and less sustainable modes, guaranteeing fast and lean access/egress to the mass transport. In this context, the understanding and prediction of travellers’ mode choices is crucial not only for the effective management of multimodal transport networks, but also successful implementation of new transport schemes. Traditional studies on mode choices typically treat travellers’ decision-making processes as planned behaviour. However, this approach is now challenged by the widely distributed, multi-sourced, and heterogeneous travel information made available in real time through information and communication technologies (ICT), especially in the presence of a variety of available mode options in dense urban areas. Some of the real-time factors that affect mode choices include availability of shared vehicles, real-time passenger information, unexpected disruptions, and weather. These real-time factors are insufficiently captured by existing mode choice models. This chapter aims to propose an introduction to MaaS, a literature review on mode choice paradigms, then it proposes a novel behavioural concept referred to as the hypermode. It will be illustrated a two-level mode choice decision architecture, which captures the influence of real-time events and travellers’ adaptive behaviour. A pilot survey shows the relevance of some real-time factors, and corroborates the hypothesized adaptive mode choice behaviour in both recurrent and occasional trip scenarios.

Part of the book: Models and Technologies for Smart, Sustainable and Safe Transportation Systems