Study on an autonomous distribution system for smart parks based on parallel system theory against the background of Industry 5.0

Abstract

The autonomous distribution systems used in smart parks against the background of Industry 5.0 require not only the consideration of the single goal of the economic benefits of enterprises, but also the fulfillment of their social responsibilities. Consequently, the scheduling of autonomous distribution systems and the trajectory planning of intelligent logistics vehicles have become increasingly more complex. Although technologies such as swarm intelligence have gradually been applied to the solution of independent distribution systems, there remain challenges in how to ensure that the production enterprises bear their responsibility to the public and consumers. Parallel system theory provides theoretical support for the concrete embodiment of people-oriented values in the smart park environment. In this work, based on parallel system theory, a parallel autonomous driving system is established. The system is mainly used for the autonomous transportation of finished products and materials in smart parks. The goal is to enhance the flexibility and efficiency of the distribution system in the park, and to highlight the people-oriented goal. Based on swarm intelligence theory and the A* algorithm, an improved swarm search optimization algorithm called IGSO-A* is developed to support the scheduling of parallel distribution systems and the trajectory planning of intelligent logistics vehicles. In two types of simulation experiments, compared with three other cutting-edge algorithms, the performance of the designed IGSO algorithm is improved by 4.6% on average. Moreover, compared with the A* algorithm, the performance of the proposed IGSO-A* algorithm is improved by 11.49%. The results prove the effectiveness of the proposed parallel autonomous distribution system in the distribution of finished products and materials in smart parks.