You are here

Methodologies and Algorithms for Ground Soldier Load and Route Selection Decision Applications

Description:

TECHNOLOGY AREAS: Information Systems, Ground/Sea Vehicles, Human Systems

OBJECTIVE:  To research, develop, and demonstrate tools that could support tactical small unit load planning and route selection. 

DESCRIPTION:  The Army’s small units (Infantry Company and below) will benefit from decision applications that support mission planning and execution of their operational tasks.  The selection of equipment to take on a mission and the selection of routes can be based upon numerous factors that are quite complex, to include the METT-TC elements (mission, enemy, terrain and weather, troops and support available, time available and civil considerations), work-rest cycles, Soldier performance, resupply, contingency planning and terrain analysis.  Terrain analysis is often further broken out by the OACOK rubric, with the major elements including: Observation and Fields of Fire, Avenues of Approach, Cover and Concealment, Obstacles, and Key or Decisive Terrain.  Tools can be developed to support execution of these interdependent tasks. 

There are currently several tools that have some applicability to load planning and route selection, but they all have significant shortcomings for the Small Unit (SU).  Most planning is currently done using a paper map or digital imagery from Falcon View, Google Earth or some other source.  The unit leader must interpret this terrain data and integrate it with other sources of information.  Force XXI Battle Command Brigade and Below (FBCB2) provides battle command and situational awareness information, but focuses on enemy locations and higher echelon decision makers.  There are commercial mobile applications that could be used for route planning for civilian applications, but almost all focus on vehicle transportation.  Commercial mobile application have little to no utility for the kind of route planning that SU Soldiers/Leaders in the battle space are required to do (i.e. Soldiers rarely get to travel on improved roads, they must be concerned with elevation and navigation in under/undeveloped areas, and they must conduct topographical analysis to understand areas along the route that could provide ambush and or attack opportunities for the enemy).  As a result, we know there are shortcomings that need to be addressed in the following areas:

•  Ability to conduct terrain analysis to accurately determine where Soldiers can move and the difficulty (energy cost) associated with the movement

•  Linking the energy cost of movement with resulting impacts on Soldier and SU performance of critical cognitive and physical combat tasks

•  Estimating time to arrival based upon load, terrain, Soldier state and other parameters

•  Estimating impacts of terrain, load and other parameters on thermal burden and heat strain

•  Linking key Personal Status (PERSTAT) parameters with ability to execute missions that involve significant movement

•  Ability to use intervisibility tools to aid the SU leader in identifying areas of cover and concealment and in identifying potential avenues of approach and egress

This effort would research, develop, and demonstrate methodologies and algorithms that enhance tools for load planning, route selection and in making changes during mission execution.  It would also be desirable that the route and load planning tools be compatible with and support the military planning process, e.g. generation of Operation Order.  Potential approaches should address the data, methodologies, algorithms, and validation audit trail.  Proposals should identify how the proposed research will advance the current state of the art.  The products should support development or improving battlefield and training decision support applications focused on Soldier load issues.  The SU leader is responsible for making the final decision and we are trying to provide actionable information (e.g. timely, accurate or more complete) in which to do so.  Elements that could be important to execution of this work include:  identifying the SU leader decisions that are to be supported, understanding user needs; identifying the factors that are important; identifying, researching, and developing methods of obtaining the data needed; developing user interfaces that meet user needs; developing methodologies and computer algorithms; providing the desired output in a useful form; and addressing software and platform integration issues.  Since validation is a critical issue, the algorithms and decision aid application must accurately represent the intended real world phenomena from the perspective of its intended use.  At this point, we are assuming that the SU will have: intermittent network connectivity, some resident computational capabilities, terrain databases, and some form of display available to them.  At this time, it is not clear if the products of this effort would be integrated with other existing battle command systems, become a module in an integrated application or be utilized as a stand-alone application. 

PHASE I:  Phase I will provide a proposed concept for the generation of methodologies and algorithms that would be needed and could be incorporated into an application to support load planning and route selection at the SU level.  The focus should be on the METT-TC and/or OACOK elements.  This will include identifying a number of specific operationally relevant decisions and actions that could be at least partially supported by a decision support application.  The proposal should also show how the proposed methodologies and algorithms would provide the SU leaders with useful information to support his decision making.  As a result, it is important that verification and validation planning be initiated at this stage.  It is desirable that algorithms be computationally efficient within a potential battlefield and training decision support aid.  Any data needs and assumptions required by the concept to be compatible with a SU decision aid should be clearly outlined and explained.  Phase I should also include identification and discussion of additional operationally relevant algorithms that could support equipment and route selection at the SU level. 

Phase I will perform a proof of concept that describes how one proposed concept may be utilized within a ground Soldier battlefield decision support aid.  Metrics in phase I will include:

•  The usefulness of the methodology or algorithm to support load planning or route selection across a range of situations,

•  The applicability and utility of an initial methodology and algorithm to be implemented within a decision application,

•  The degree that it represents the important elements of the real world (valid),

•  Documentation and ability to demonstrate the methodology or algorithm,

•  Modularity and ability to be incorporated into a route selection cost function that incorporates other factors, and applicability of the selected approach to the development of additional algorithms.

PHASE II:  Phase II will include research, design and implementation of multiple methodologies and algorithms necessary in accordance with the topic objective.  Knowledge elicitation may need to be conducted with tactical small unit SME’s to ensure that critical real world factors (i.e. METT-TC or OACOK) are identified and included in such a way as to support the development of each methodology, to include the necessary data elements and data structures.  In Phase II, validation and verification will have to be addressed.  The plan may also include how specific applications could be developed.  A set of use cases that describe relevant military operations or missions will be provided to guide research, methodology development and support testing and experimentation.  The work effort will lead to demonstration of the products developed in phase II within an appropriate environment. 

Other tasks include documenting and delivering a report including all user needs assessments, methodologies, algorithms, and any data structures or software products necessary to support transition of the work to DoD materiel developers.  The phase II report should also demonstrate and document how algorithms may be transitioned to support implementation into battlefield and training decision support applications.  Metrics for this effort will include the number of methodologies and algorithms developed, the degree to which they represent the important elements of the real world, their potential utility within the decision application, documentation and their ability to be demonstrated.  Other considerations include the degree to which the algorithms are computationally efficient, can be modified if additional factors need to be included, and can be implemented within appropriate decision applications of the governments’ choosing.  Because we do not yet know if the products of this effort will lead to a stand-alone system or be integrated within another system, compatibility is an important issue.  As a result, the architecture, modularity and interfaces are all important.

PHASE III DUAL-USE APPLICATIONS: The developed methodologies and associated implementation have commercial applications of these simulation products to proposed DoD materiel solutions whose goal is to provide Soldier’s applications that will support enhanced Soldier situational awareness and improved decision-making.  Also, there is potential application to future automated or semi-automated ground Soldier battlefield systems, such as an Unmanned Ground Vehicles.  Non military applications could relate to route selection where there are common elements with tactical small unit operations.

US Flag An Official Website of the United States Government