A Cooperative Planning and Control Method for Intelligent Connected Agricultural Vehicles Considering Virtual Lanes

The automation of agricultural vehicles represents a significant field of interest in the application of intelligent driving technologies. Agricultural vehicles operate in complex environments that require the cooperative movement of multiple units. Developing methods for effective cooperative planning and control of these vehicles is crucial for advancing autonomous driving in the agricultural sector. The technology of intelligent connected vehicles provides the fundamental condition for cooperative planning and control of multiple agricultural vehicles. Leveraging information from intelligent connected agricultural vehicles, this study introduces the concept of virtual lanes and proposes an innovative planning approach that integrates the graph method with the Artificial Potential Field (APF) method. The incorporated strategy aims to facilitate rapid and efficient cooperative planning of multiple vehicles operating within unstructured agricultural areas. Then, an Improved Nonlinear Model Predictive Control (INMPC) algorithm considering feedforward control is proposed, which improves the accuracy of tracking control and achieves precise cooperative movement of multiple vehicles. Simulation results indicate that the method proposed in this paper can quickly realize cooperative planning and control of multiple vehicles in complex agricultural areas, achieving platoon operation of multiple agricultural vehicles. This research can promote the application of intelligent connected vehicle technology in agricultural production and facilitate the development of agricultural automation.