Research on Logistics Trolley Collaboration System under Complex Transport Scenario

As car ownership has increased, so has the demand for logistics vehicle services. Under the environment of mixed flow of people and vehicles, the logistics transport scene has become more complex, requiring cross-floor, cross-factory and even crossplant logistics transport. The traditional magnetic stripe and WIFI network-based logistics vehicle route fixing can no longer meet the demand for full-scene operation. Therefore, this paper adopts a cloud platform communication and collaboration system and combines a DWA-based taboo search algorithm to communicate and locate complex traffic intersections in real time to avoid the interference of information interaction between vehicles. In this way, logistics vehicles can be equipped with the functions of complex environment sensing, path planning, behavioral decision making and vehicle collaboration. In this paper, we use MATLAB Simulink to model and simulate the vehicle following model, and conclude that the vehicle following model based on vehicle collaboration has a higher degree of fit, thus realizing highly collaborative intelligent transport in complex scenarios.