Using Spoken Language to Facilitate Military Transportation Planning 
Madeleine Bates, Dan Ellard, Pat Peterson, Varda Shaked 
BBN Systems and Technologies 
10 Moulton Street. 
Cambridge, MA 02138 
ABSTRACT 
The DARPA SLS Program is developing a technology that has been 
justified, at least in part, by its potential relevance to military applications. 
In an effort to demonstrate the relevance of SIS technology to real-world 
military applications, BBN has undertaken the task of providing a spoken 
language interface to DART, a system for military logistical transportation 
planning. 
We discuss the transportation planning process, describe the real-world 
DART system, identify parts of the system where spoken language can 
facilitate planning, and describe BBN's work towards porting the HARC 
SIS system to the DART domain. 
TRANSPORTATION PLANNING 
Logistical transportation planning is the process of determining 
how to get people and cargo from where they are to where they 
need to be. Inter-theatre movements of personnel and supplies 
around the world are currently planned for the Army, Navy, Air 
Force, and other services by USTRANSCOM (the US 
TRANSportation COMmand) which operates under the Joint 
Chiefs of Staff. The transportation plarming process is quite 
complex, involving very large databases of movement 
requirements, and information about personnel, cargo, 
transportation assets, and geographic locations. Currently, the 
human interface to military planning systems is relatively 
enmbersome and unintelligent, which adds extra complexity to 
the planner's task. 
As a domain for the application of spoken language, military 
transportation planning has a number of advantages: 
1. Transportation planning is an essential military function and 
successful application of spoken language would be both 
useful to TRANSCOM and visible to other potential military 
users of SLS technology. 
2. The concept of planning movements of people and supplies 
can be understood by a wide audience. 
3. The application is non-trivial and, in the DART context that 
we will describe, affords opportunities for applying spoken 
language understanding at many levels of sophistication. 
4. Current efforts to improve the planning process using non- 
speech technology have been weU-received, and cooperative 
users may be available as close as Scott Air Force Base near 
St. Louis. 
5. An unclassified development database is available in Oracle 
on a Son. 
THE DART SYSTEM 
BBN is currently involved in an effort to improve the 
transportation process using non-speech teclmology. The DART 
(Dynamic Analysis and Replanning Tool) project 1 , is 
demonstrating the operational impact of AI planning and 
scheduling technology on transportation planning at 
USTRANSCOM. DART addresses an urgent need for fast and 
accurate plan generation and evaluation to support both long- 
range, hypothetical planning and planning in such crisis-response 
operations as those in the Middle East. 
The current DART system \[1\] is in use at Scott Air Force Base 
and other locations around the globe. The workstation 
environment which has been installed at TRANSCOM to support 
DART is already being used and has been credited with reducing 
routine plan analysis from 3 days to I day \[2\]. 
The architecture of the DART system is shown in figure 1. The 
heart of the system is a relational database. The database is 
initialized with data from two sources, a database of transportation 
characteristics, and a Time Phased Force Deployment Database 
(rPFDD). TPFDDs are usually prepared in advance to deal with 
hypothetical military operations. In a crisis situation, the planner's 
task is usually to retrieve an applicable TPFDD, and to change it 
to fit that new situation. The output of the process is a modified 
TPFDD which can be used in subsequent planning and operational 
activities. 
A typical TPFDD may contain hundreds of fields and hundreds 
of megabytes of data, but its focal point will always be a table of 
movement requirements with perhaps thousands of records 
describing the movement of all the units necessary to execute a 
plan. The planned movement of a unit, which may be as small as 
a single person or larger than a battalion, consists of three 
segments. In the first segment, a unit moves from its origin to a 
Port of Embarkation, or P.O.E. In the second segment, 
transportation is provided from the POE to a Port of Debarkation, 
or P.O.D. In the third segment, a unit moves from the POD to its 
f'mal destination. The FOEs and PODs may be airports, sea ports, 
Air Force bases, or other kinds of locations. The transportation 
from POE to POD may be by land, sea, or air. This transportation 
segment is usually of most interest to TRANSCOM planners. 
1 DART is sponsored by DARPA and Rome Laboratory and 
involves BBN, Ascent Technologies, ISX Corporation, MITRE 
Corporation, and SRA Corporation. 
217 
Transport 
Data TPFDD 
Modified 
TPFDD 
Requirements 
& Assets J 
Relational 
DataBase 
Results 
RAPIDSIM 
Figure 1: Architecture of DART. Shaded modules are candidates 
DART makes a number of tools available to the planner. These 
include a TPFDD editor for viewing units and making changes in 
their characteristics and transportation plans, a notional ports 
editor which allows ports to be combined for purposes of planning 
and simulation, a transportation assets editor which lets the 
planner modify the availability and characteristics of various 
transportation assets, the RAPIDSIM simulation system which can 
"run the current plan", and an analysis capability that enables the 
planner to examine the output of a RAPIDSIM run to determine 
whether or not the objectives were achieved 
DART allows a planner to extract pieces of pre-planned 
movement records from a database by specifying simple 
constraints on up to five items: the units to be moved (a unit 
generally contains both personnel and cargo), the place of origin 
of the units, their port of embarkation, their port of debarkation, 
and their final destination. 
The retrieved data is displayed in a spreadsheet-like window, 
horizontal bars showing the number of days each step of the 
transport is expected to take, with the color indicating whether the 
step is by land, sea, etc. An example of this window, and other 
parts of the normal DART display, is given in figure 2. 
The TPFDD Database 
The database that underlies the entire planning process is called 
the TPFDD (Time Phased Force Deployment Database) \[3\]. The 
TPFDD development database that is unclassified and available in 
Oracle has 50-100 MB of data, in 13 tables and about 500 fields. 
This data represents approximately 20,000 cargo movement 
for spoken language interfaces. 
records, 9,000 unit movement records, and a smaller number of 
personnel movement records. Each movement record contains, 
among other information: 
- location of origin 
- POE (port of embarkation) 
- intermediate locations, if any 
- transportation mode (land, sea, air) 
- transportation provider 
- POD (port of debarkation/discharge) 
- location of destination 
- RLD (ready to load date) at origin 
- ALD (available to load date) at POE 
- EAD (earliest arrival date') at POD 
- LAD (latest arrival date) at POD 
- RDD (required delivery date) at destination 
DART PLUS SLS 
Natural language access (both spoken and typed) increases the 
utility of the DART interface by providing capabilities that are not 
available in the non-language interface, and it can decrease the 
task completion time for operations that can be expressed more 
concisely in words than in mouse actions. 
We have identified six areas of the DART system where natural 
language will provide increased functionality for this military 
system: 
1. the TPFDD editor, which allows users to create and modify 
entries in the Timed Phased Force Deployment Databases 
218 
U-AC8BD U-ACBBB U-ACBBA U-AC7B U-AC7AP U-AC7AC U-AC6GU 
U-ACBBD U-ACE88 U-AC8BA U-AC7B U-AC7AP U-AC7AC U-ACGGU 
that specify movement requirements for the personnel and 
materiel involved in planned military operations, 
2. the transportation assets editor, which is used to view and 
change the number and type of transportation assets (ships, 
planes, etc.) and the days when they are available, 
3. the notional ports editor, which is used to combine actual 
ports (sea ports, air ports, or other geographical lecations) 
into single "notional" ports to simplify subsequent 
simulations of planned movements, 
4. the analysis of results from the RAPIDSIM simulation of the 
current plan's exe ution, 
5. universal (that is, available throughout the whole DART 
system) access to information in the TPFDD database that 
underlies the planning system, 
6. menu navigation through the DART system, so that a user can 
use a single verbal command instead of a lengthy sequence of 
mouse (and possibly keyboard) operations. 
Each of these opportunities for adding spoken language to the 
DART interface has separate pros and cons. They vary in 
expected vocabulary size, likely language complexity, ease of 
interface to DART, and utility for the user. 
For example, in the notional ports editor, the user is likely to 
want to give short commands to the system ("Show me Travis Air 
Force Base", "Zoom in around Charleston", "What's this port?", 
"Show the nearest military airport", "Compute the notional pert 
assignments"). The planner is also likely to refer only to the 
geographical locations that are displayed on the current map, 
which reduces the vocabulary (and the perplexity) considerably. 
Universal database query, on the other hand, will involve 
complex language ("What percentage of the Navy units headed for 
air force bases in Tunisia that are available to load from US ports 
prior to day 20 contain hazardous cargo?"). This part of the 
application will also require a very large vocabulary, since 
virtually any geographic location or other word from the database 
can be used in a query. We estimate that even for just a good 
demonstration, the vocabulary will need to be about 5000 words. 
For our initial demonstration, however, we chose to illustrate a 
database query system because such a system would be very 
useful and also because its simple interface to DART allowed us 
to minimize interference with DART development. 
NL understanding. We have implemented a mechanism to allow 
units that are retrieved via natural language queries to be imported 
into the DART plan display. 
Future Work 
Future developments will include extending the configuration 
and vocabulary to cover a larger segment of the database, and to 
allow voice commands to be executed in the DART system. 
REFERENCES 
1. Grider, T., Mosley, H., Snow, L, and Wilson, W., "Users Manual for the 
Dynamic Analytical Replanning Tool (DRAFT)", prepared for BBN by 
Systems Research and Applications Corporation, 9 November 1990. 
2. Edward Walker, personal communication. 
3. "Joint Operation Planning System (JOPS) Time Phased Force 
Deployment Data (TPFDD) and Related Files, Database Specification", 
System Planning Manual, SPM D5 143-87, Joint Data Systems Support 
Center, 1 April 1987. 
Current Status 
The videotape presentation describes the task of TRANSCOM 
planners, shows examples of the current interactions that are 
possible with DART plus SLS, and shows examples of natural 
language interactions that will facilitate the planners' work. 
As of the time of this workshop, we have transferred from the 
small in-core planning database that we developed for 
demonstrating HARC to using the real TRANSCOM development 
database in Oracle. We have developed an initial DART interface 
that uses windows to indicate activities in speech processing and 
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