LAUSR

Unmanned ground vehicles (UGVs) are important elements in the future intelligent transportation system (ITS), which is supposed to conduct various tasks for human beings. Obviously, the traditional edge-side (vehicle-side) dynamics control system strictly limits the performance improvement of multifunctional UGVs in various applications. Therefore, this article proposes a future ITS with multifunctional UGVs and a cloud-edge combined, big-data-driven dynamics control approach for UGVs to improve safety. The proposed cloud-edge combined control method is achieved based on big data machine learning optimization in the cloud-side controller and feedforward-feedback lateral dynamics control in the edge-side controller. In the cloud-side controller, the big data generated during the operation of the UGVs are stored and mined by the cloud brain control center to optimize the controller parameters of the edge-side controller to improve the dynamic performance and safety of the UGVs. Finally, the proposed cloud-edge combined controller is validated based on the experiments of a real UGV testbed.