Cost Game Analysis of the Hybrid Delivery Model Combining Drones and Riders: A Study on the Collaborative Mechanism Based on the Stackelberg Competition Model

Abstract

As the demand for instant delivery surges and labor costs rise, collaborative delivery between drones and traditional couriers has become the key to breaking the deadlock in the industry. This study constructs a two-stage Stackelberg leader-follower game model, with the Unmanned Aerial Vehicle (UAV) as the leader (decision service density and pricing , delivery rider for followers (dynamically adjust order volume ), model incorporates specific parameters for the low-altitude economy (airspace congestion cost , density utility coefficient ), using backward induction to solve for the optimal strategy, revealing the equilibrium mechanism of the dynamic game of resources under a hybrid delivery model, provide decision-making support for the government in (ting low-altitude economy policy platforms and optimizing resource allocation. Results show that when the airspace congestion cost increases, an increase in drone density is required to reduce marginal congestion loss. The government can optimize resource allocation through the "Dynamic Airspace Access Threshold" and "Density-Subsidy Linkage" policies, thereby reducing the total system cost. This study provides quantitative tools for the (tion of low-altitude economy policies and promotes the transition of collaborative delivery between drones and couriers from theoretical concepts to large-scale practical implementation.