  Computing and intelligence are substantial requirements for the accurate
performance of autonomous ground vehicles (AGVs). In this context, the use of
cloud services in addition to onboard computers enhances computing and
intelligence capabilities of AGVs. In addition, the vast amount of data
processed in a cloud system contributes to overall performance and capabilities
of the onboard system. This research study entails a qualitative analysis to
gather insights on the applicability of the leading cloud service providers in
AGV operations. These services include Google Cloud, Microsoft Azure, Amazon
AWS, and IBM Cloud. The study begins with a brief review of AGV technical
requirements that are necessary to determine the rationale for identifying the
most suitable cloud service. The qualitative analysis studies and addresses the
applicability of the cloud service over the proposed generalized AGV's
architecture integration, performance, and manageability. Our findings conclude
that a generalized AGV architecture can be supported by state-of-the-art cloud
service, but there should be a clear line of separation between the primary and
secondary computing needs. Moreover, our results show significant lags while
using cloud services and preventing their use in real-time AGV operation.
