Study on Path Planning Model and Algorithm of Driverless Logistics Distribution under Intelligent Network

With the rapid improvement of unmanned driving technology, unmanned driving technology in physical distribution can make full use of logistics resources and improve the quality of logistics services. It aimed to solve the optimization problem of driverless logistics distribution under an intelligent network, a vehicle route planning model with optimization goals of minimizing total cost and maximizing customer satisfaction under the single distribution center’s constraint, multiple vehicle types, closed routes, soft time windows, etc. According to the multi-objective optimization model’s characteristics, an augmented epsilon-constrained algorithm is designed to solve the problem and applied to a multi-customer distribution example to verify its effectiveness and efficiency. In this case, customer satisfaction is as high as 91.67%, and the algorithm only takes 0.94 seconds. The study can provide a reference in the field of driverless physical distribution in the future.