Unmanned Vehicle Task Scheduling Method Based on Iterative Cognitive Interaction

At present, in the field of autonomous driving, the application of unmanned vehicles has made considerable progress. However, there are still a large number of engineering problems to be solved in practical application. For example, the ability of multi-vehicle interactive autonomous operation in high-dynamic and time-sensitive environment is not sufficient for large-scale application. These kinds of problems restrict the effective integration of unmanned intelligent transportation system and current traffic system. Facing the problems described above, this paper focuses on introducing knowledge-driven and experiential memory decision-making process for agents, which is based on the research on the process characteristics of human brain cognitive reasoning under the condition of dynamic changes in the observation results of multi-agent clusters. Thus, the method of unmanned vehicles tasks scheduling method based on iterative cognitive interaction is proposed in this paper. In view of the behavior and decision-making process of multi-vehicle in aspects of cognition, interaction, and association, the analysis and research on the time scale will provide a research route for solving the continuous autonomous operation of multi-vehicle system in a high dynamic environment. Contribution of this paper can provide theoretical basis and practical value for multi-application fields.