With the rapid implementation of intelligent networking and low-altitude logistics technology, ground-air collaborative distribution has become a new technological path to solve the bottleneck of end-of-pipe logistics distribution in urban and rural areas, thanks to its advantages of flexibility, efficiency, three-dimensional coverage, and dynamic adaptation. In response to the strong timeliness of delivering characteristic agricultural products in rural areas of Dalian, as well as the pain points of traditional vehicle delivery services such as large radius, high empty driving rate, and shortage of transportation capacity during peak hours, this paper takes rural logistics in Dalian as the research object, introduces the “vehicle drone” ground-air collaborative delivery mode, and conducts dynamic path planning optimization research in rural scenarios. Based on the spatial distribution characteristics of rural distribution customers, the DBSCAN clustering algorithm is used to aggregate and divide the demand nodes for village level distribution, and accurately locate the vehicle parking points based on the centroid of each clustering cluster. Simultaneously building a collaborative delivery scheduling model, solving and validating the model through improved ant colony algorithm. The research results indicate that DBSCAN clustering can effectively integrate village-level distribution nodes, significantly reducing the frequency of vehicle stops and detours. Compared to traditional bicycle delivery models, the two collaborative modes of “vehicle-drone” parallel delivery and portable delivery can effectively reduce comprehensive delivery costs and improve the operational efficiency of end-of-pipe delivery.