Work

Digital twins in public bus transport: A systematic literature review of architectures, intelligence, and interaction

Year: 2026

Type: review

Abstract: The adoption of Digital Twin (DT) technologies in public transport systems, particularly bus networks, is gaining momentum as cities seek smarter, more responsive, and efficient mobility solutions. Enabled by advances in IoT, AI, and Big Data Analytics, DTs offer real-time monitoring, simulation, and optimization of transit operations. However, despite their potential, the application of DTs in bus-based public transport remains relatively underexplored and fragmented across the literature. This study presents a Systematic Literature Review (SLR) aimed at synthesizing current research on DT technologies in this domain. Specifically, it investigates architectural models, technological frameworks, and platform designs; examines how AI and machine learning models are integrated to support operational tasks; and analyzes the role of Human-Computer Interaction (HCI) in the design and usability of such systems. By identifying key trends, challenges, and research gaps, this work provides a structured overview of the current landscape. Furthermore, it outlines directions for future research in DT-enabled public transportation systems.

Source: Future Generation Computer Systems

DOI: 10.1016/j.future.2026.108379

Authors: Manuel Andruccioli, Giovanni Delnevo, Roberto Girau, Paola Salomoni

Institution: University of Bologna

Language: English

Topic: Digital Transformation in Industry

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: hybrid

Estimated APC paid: $3,000