Autonomous driving strategies for unsignalized intersections and roundabouts in intelligent transportation systems: a systematic review and taxonomy

This paper presents a systematic review of autonomous traffic management strategies for unsignalized intersections and roundabouts within intelligent transportation systems, with a focus on connected and automated driving environments. Based on literature retrieved from Web of Science Core Collection, Scopus, and PubMed, the review combines CiteSpace-based bibliographic preprocessing with VOSviewer keyword co-occurrence analysis and develops a method-oriented taxonomy according to the primary conflict-resolution mechanisms of existing approaches. A supplementary targeted search extends the coverage to vulnerable-road-user-inclusive and lane-free traffic management. Four principal paradigms are identified: Priority and Rule-Based Systems, Communication-Driven Collaboration, Platoon-Based Optimization, and Optimization and Learning-Based Control. Beyond classification, the review compares the operational requirements and limitations of representative approaches and synthesizes selected traffic-engineering evidence on capacity, delay, travel time, and level of service. The synthesis highlights a tradeoff between the interpretability and computational efficiency of rule-based strategies and the adaptability of optimization- and learning-based approaches, while persistent challenges remain in scalability, communication robustness, sim-to-real transfer, heterogeneous-traffic validation, and consistent performance evaluation. Future research should prioritize scalable and resilient cooperative architectures, stronger sim-to-real validation, and lightweight hybrid multi-objective control. These findings provide a structured reference for safer, more efficient, and more robust signal-free traffic management within intelligent transportation systems.