AI in future mobility: A multimodal journey chain perspective

Digital services and tools have become increasingly ubiquitous in public transport. Recently, the use of artificial intelligence has gained substantial momentum among practitioners and academia in the field. The vast amount of data collected from public transport systems provides not only opportunities for authorities and service providers to improve and optimize public transport systems using AI but also enables new types of user-centric services. In particular, AI provides opportunities for personalized, customized, and context-aware services that set the promise of altering the experience of using public transport, making it more accessible, appealing, and secure. However, despite the growing interest, the ways in which AI provides opportunities for creating new user-centric services for PT remain scattered. By using the multimodal journey chain framework, we describe the various approaches and AI use cases that have the potential to support passenger activities throughout different journey phases. Our results highlight how developments in AI pledge to make PT-based multimodal journey chains more accessible, providing autonomy to users with special needs.