## 2 Background and Literature Review  
Even though the term HMT has been coined in recent years, the concept of computers or machines assisting humans can be traced back to World War II. During this period, the French army's armored tanks were much more sophisticated in performance and maneuverability than those of the Germans. However, unlike the Germans, the French tanks had no radios to share information among tanks, which gave a distinct advantage to the Germans over French tanks [11]. This example shows the importance of interaction or communication in the areas of HMT. While no actual teaming was involved between tanks and humans, these applications laid the foundation for the field of HMT. In the assumed symbiotic partnership [12; 13; 14], individuals set the goals, establish the conditions, define the criteria, and conduct the evaluations. Simultaneously, computing machines do the pattern work to prepare the way for acumens and conclusions in technical and scientific studies. The age of shared control began in 1963 with [PERSON]'s proposal for handling radioactive material [15]. In shared control, the computer assists in the task by predicting the operator's intent [16]. Later in 2004, ref. [17] proposed methods for bi-directional information flow in the HMI field, officially commenced HMT research.  
The invention of the idea of an HMT can be attributed to the game of advanced chess. For instance, in 2005, two amateur chess players, together with three PCs, won a chess tournament against a field of supercomputers and grandmasters [18]. More recently, a current HMT application of notable significance is the F-35 Joint Strike Fighter, which serves as a fighter plane and a mobile sensor kit that collects, correlates, and analyzes an immense amount of data and displays insights on the pilot's helmet [19]. In fact, the military as a whole has begun to move towards HMT. For instance, the Army plans to fly Apache helicopters and Grey Eagle drones together such that the drones receive commands from the pilot of the aircraft during a mission [20].  
Historically, different modalities have also been used by different researchers that play a crucial role in exploring successful HMT implementation. Researchers from [21] used a model-based approach for cognitive assistance to track pilots' changing demands in a dynamic situation. They used flight deck interactions and EEG recordings to find individual pilot's behavior in response to flight deck alerts. Whereas researchers from [22] created a human-robot team where humans had their vehicle to pilot and worked together with several autonomous vehicles to accomplish a common goal in  
Figure 2: Paper outline.  
a marine environment. In their work, they planned to use the human operator's physiological measurements to help autonomous teammate vary their communication and levels of control based on the operator's cognitive load. Contrary to others, ref. [23] in their work used image descriptors to create a successful HMT. Figure 3 is a visual representation of publications in the area of human machine teaming with corresponding disciplines of the research areas.  
In this section, state-of-the-art works in HMTs that include currently published architectures and interfacing/communication methodologies have been reviewed. Furthermore, we also discuss the published HMT simulation techniques and the available benchmarking methods in the HMT area. This literature review will help us establish clear objectives for this research.