Recent supply chain targets have led to decreased response time requests also causing enterprises invest for automation technologies for efficient management for their warehouses. In this paper, we focus on an automated warehousing environment where there are robotic order pickers travelling on ground flexibly throughout aisles. We develop deadlock and collision prevention algorithms for safely travel of those robotic order pickers. The developed algorithms can be utilized by any warehouse system having autonomous vehicles (e.g., automated guided vehicles, mobile robots, or shuttles in a multi-tier automated warehouse) that can travel between aisles freely. While developing those smart algorithms, we also aim to improve some performance metrics such as average flow time and, maximum flow time of a transaction in the system.  To test the performance of the algorithms, we model the system as a multi-agent system, where autonomous vehicles are able to communicate with each other under an Internet of Things (IoT) environment. We compare that flexible system design with a dedicated design where a dedicated vehicle is assigned for a pre-defined number of aisles. The experimental results show that under well-designed deadlock and collision prevention control algorithm, flexible travel of vehicles can provide advantage compared to dedicated design.