Combining two efforts for better results
April 19, 2012
Until recently, the U.S. Army Research Laboratory's (ARL) Survivability/Lethality Analysis Directorate (SLAD) performed analyses on system engineering independently of the Human Research and Engineering Directorate's (HRED) analyses on the cognitive or mental workload of Soldiers.
HRED and SLAD attended a meeting where discussion included the issue that the availability of human operators and their impact on mission performance were not being considered in the Army Test and Evaluation availability metrics used for system evaluation -- even though these systems include humans. Diane Mitchell from HRED, and Bill Landis and Kevin Agan from SLAD, proposed an analytical technique to better support the customer that would examine the impact of human and system availability on mission performance.
"SLAD and HRED don't always have the opportunity to work together, but at that meeting we realized we were able to develop something, that as far as we can tell, where we have the methodology to study the people and vehicle together," said Agan.
Between HRED's cognitive building block (CBB) technique; which connects a human's cognitive workload and capabilities to mission performance, and SLAD's system capabilities analytic process (SCAP) that connects a system's components and capabilities to mission performance, a new technique was developed combining the two analysis focuses, which resulted in the human availability technique or HAT.
"Prior to HAT, HRED focused on the cognitive or mental workload associated with a person's tasks while SLAD focused on the equipment or the vehicle -- they looked at the platform not the people side," said Mitchell. "We used the details from each method and put them together."
In support of the Joint Light Tactical Vehicle (JLTV) Program, the two directorates developed a conceptual case study involving two Soldiers performing their mission within a utility vehicle light (UVL) and to predict mission performance. The analysis used HAT to predict the mental workload of the Soldiers and to predict the protection the UVL provided them in comparison with the currently fielded vehicle.
Landis provided the vehicle analysis, and Mitchell provided the human perspective to see if their combined technique worked.
By incorporating both analysis techniques in an executable task network model known as the Improved Performance Research Integration (IMPRINT), they were able to simulate the Soldiers' tasks and mental workload derived from HRED's CBB with the system capabilities derived from SCAP. Based on Warfighters' mental workload and system design characteristics, the simulation predicted the probability of task success or the consequences of failure on mission performance.
Using IMPRINT, analysts built two models of the Soldiers performing the logistics mission. In one model, the Soldiers performed the mission in a currently fielded vehicle while in the other in a conceptual UVL. The objective of the mission was to drive the vehicle across the operational environment to deliver supplies to a pre-determined location. The Soldiers performed the same functions in both models -- they were to move across the battlespace, perform self-protection, manage platform health, transport the supplies, exercise command, and control and manage tactical information and data.
Although the Soldiers performed the same functions in both models, they accomplished this with different system capabilities to include traveling on/off roads at certain speeds, traveling on/off roads with minimal versus full capability, operating during daytime and nighttime hours, sending or receiving short and long range communications, and crew protection. The conceptual UVL provided additional capability for the crew protection that lacked in the currently fielded vehicle.
The HAT analysis predicted the Soldiers in both the currently fielded vehicle and conceptual UVL would likely experience mental overload when required to perform the multiple roles of driver, gunner, and vehicle commander with only two Soldiers operating the vehicle. The HAT analysis predicted the Soldiers would be likely to miss detection of an improvised explosive device (IED). However, the consequences of the missed IEDs varied dependent upon whether the vehicle was the UVL or currently fielded vehicle.
The HAT case study demonstrated the benefits of including a detailed representation of both Soldier and system functions in one analysis. Without the HAT technique, the IMPRINT analysis would have shown the Soldiers were overloaded in both vehicles, but it would not have shown the improved system capability.
"The bottom line is this -- the sum of the parts is greater than each of the individual pieces," said Landis. "Each is valuable, but once we discovered our work could be connected through joint analysis, we grew stronger and we can give a better answer to our customer."