Chapters authored
Approaches for Modelling User’s Acceptance of Innovative Transportation Technologies and Systems 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
Adaptive Travel Mode Choice in the Era of Mobility as a Service (MaaS): Literature Review and the Hypermode Mode Choice Paradigm 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
Applications of Driving Simulators in Intelligent Transportation Systems: Investigating Driver Behaviour under Variable Speed Limits By Behnood Baiky, Facundo Storani, Roberta Di Pace, Stefano de Luca
This study explores driver perception and compliance with variable speed limits (VSLs) within Intelligent Transportation Systems (ITS), emphasizing the critical role of human behavior in traffic efficiency and safety. Using driving simulators (DSs), it bridges the gap between model-based and safety-oriented VSL studies and real-world driver responses, providing insights into behavioral realism and adaptive system performance. A structured narrative review was conducted to synthesize studies using DSs to analyze driver behavior and compliance under VSLs within ITS. Following strict inclusion criteria and database searches, 24 high-quality studies (1994–2025) were selected and systematically analyzed to identify methodological trends, research gaps, and behavioral insights. DSs prove to be powerful, cost-effective tools for analyzing driver perception, compliance, and behavioral adaptation under VSLs, offering realistic, safe testing environments for ITS research. Future studies should integrate DS experiments with connected vehicle data, artificial intelligence (AI)-driven behavioral models, and cross-cultural analyses to design adaptive, human-centered, and globally applicable VSL systems.
Part of the book: Connected, Cooperative, and Automated Mobility
Enhanced Strategies for Wide-Area Traffic Control By Franco Filippi, Roberta Di Pace, Facundo Storani, Stefano de Luca
This chapter presents a comprehensive state-of-the-art review of wide-area traffic control strategies aimed at mitigating congestion and improving urban traffic flow. Network-wide control, implemented via ramp metering, intersection gating, and wide-area gating, regulates vehicle entry into specific network regions to maintain optimal conditions. The chapter explores theoretical foundations, adaptive control mechanisms, and the integration of macroscopic fundamental diagram (MFD)-based models for real-time traffic management. Emerging approaches for coordinating traffic with dynamic demand are discussed. Benefits such as congestion reduction, enhanced safety, and environmental improvements are highlighted, alongside challenges in implementation, such as public acceptance and infrastructure constraints. This work contributes a holistic understanding of current methodologies and identifies future directions for smart urban mobility solutions.
Part of the book: Connected, Cooperative, and Automated Mobility
