Research progress in truck-drone collaborative route planning: a systematic review

To systematically review the research progress in truck-drone collaborative routing, 386 relevant publications retrieved from the Web of Science Core Collection were analyzed using VOSviewer for bibliometric and scientific knowledge mapping, complemented by a qualitative review of representative studies. The development trajectory and knowledge base of this research field were examined from five perspectives: annual publication trends, country and regional distributions, source journals, document co-citation networks, and keyword co-occurrence. Based on the keyword co-occurrence analysis, a research framework encompassing problem types, model development, solution algorithms, and application scenarios was established. The results show that truck-drone collaborative route planning has evolved from the traveling salesman problem (TSP) and the vehicle routing problem (VRP), with research settings gradually expanding from early single-truck-single-drone collaborative delivery to more complex scenarios involving multiple trucks and drones, flexible launch and recovery, multiple customer visits, integrated pickup and delivery, and dynamic operations. Model development have formed a comprehensive constraint framework centered on objective functions, network constraints, resource constraints, service constraints, truck-drone coordination and synchronization constraints, and uncertainty constraints. Solution approaches have evolved through the parallel development of exact algorithms, heuristic and metaheuristic methods, and learning-based methods. In terms of applications, relevant studies have extended from urban last-mile delivery to remote-area logistics, medical logistics, humanitarian logistics, agricultural and forestry operations, and infrastructure inspection. With the rapid advancement of air-ground collaborative transportation technologies, this systematic review not only clarifies the technical evolution of truck-drone collaborative route planning but also provides references for future model development and algorithm design in real-world applications, thereby facilitating the translation of theoretical research into engineering practice.