UAV delivery and ground transfer scheduling in emergency scenarios represent critical technological systems for enhancing disaster response capabilities and safeguarding lives and property. This study systematically reviews recent advances across eight core research domains: UAV emergency delivery systems, ground–air integrated transportation coordination, emergency logistics optimization, UAV path planning and scheduling algorithms, collaborative optimization between ground vehicles and UAVs, emergency response decision support systems, low-altitude economy and urban air traffic management, and intelligent transportation system integration. Research findings indicate that UAV delivery technologies in emergency contexts have evolved from single-aircraft applications to intelligent multi-modal collaborative systems, demonstrating significant advantages in medical supply distribution, disaster relief, and search-and-rescue operations. Current technological development exhibits four major trends: hybrid optimization algorithms, multi-UAV cooperation, artificial intelligence enhancement, and real-time adaptation capabilities. However, critical challenges persist, including regulatory framework integration, adverse weather adaptability, cybersecurity protection, human–machine interface design, cost–benefit assessment, and standardization deficiencies. Future research should prioritize distributed decision architectures, robustness optimization, cross-domain collaboration mechanisms, emerging technology integration, and practical application validation. This comprehensive review provides systematic theoretical foundations and practical guidance for emergency management agencies in formulating technology development strategies, enterprises in investment planning, and research institutions in determining research priorities.

Expressway travel demand climbs steeply during public holidays, and the severe congestion that follows has become a principal constraint on both network operating efficiency and the quality of travel services. Dependable forecasting of holiday congestion, coupled with the practical realization of proactive management, accordingly carries considerable theoretical and practical weight for improving how expressways are operated and administered and for safeguarding efficient and safe public travel. Organized around the central theme of congestion prediction and proactive management for expressways over holiday periods, this paper reviews the progress of research across five interrelated areas: traffic speed and flow prediction methods; congestion state identification and forecasting; holiday travel characteristic analysis together with demand prediction; multi-source data fusion and congestion propagation mechanisms; and expressway traffic control together with traveler behavior guidance. Having surveyed the theoretical underpinnings, core technologies, and representative methods of each area, the paper concentrates in particular on the shortcomings and difficulties that existing studies encounter in coping with the hallmark features of holiday traffic, namely demand surges of short duration combined with pronounced spatiotemporal heterogeneity, and proceeds to outline promising avenues for subsequent research. Overall, the review seeks to provide wide-ranging literature support and a theoretical reference for developing technologies that predict and proactively manage congestion on expressways during public holidays.