AI-Enabled Peri-Urban Mobility and Logistics: A Structured Literature and Project-Based Review of Drivers, Barriers, and Integration Gaps

Background: Peri-urban areas face mobility and logistics challenges, including car dependence, congestion, decarbonisation pressures, fragmented public transport, and growing demand for sustainable goods distribution, yet they remain less systematically addressed than dense urban cores. This paper examines how AI-enabled solutions can address these challenges in peri-urban systems. Methods: This study combines a structured literature review and a project-based systematic review of EU-funded initiatives. The literature review applies a Technology-Organisation-Environment lens to Web of Science and Scopus sources published between 2015 and 2026, while the project review screens initiatives from CIVITAS, EIT Urban Mobility, Interreg/KEEP, and CORDIS, retaining 124 relevant projects from 16,627 candidates. The synthesis focuses on three AI-enabled concepts: Green-Safe Routing Algorithms, Peri-Urban Mobility Hubs, and Smart and Collaborative Governance. Results: Key challenge is not the absence of individual technologies but an integration deficit involving data spaces, AI optimisation, digital twins, multimodal and freight-capable hubs, circular logistics, citizen participation, and governance capacity. The identified barriers are primarily institutional and social rather than technical. Conclusions: This paper provides an integrated conceptual framework, a drivers-barriers-integration-gaps matrix, and priorities for interoperable data governance, inclusive AI, scalable hub typologies, and policy-linked implementation pathways.