a multi-agent system for tracking the intent of surface contacts in ports and waterways
DESCRIPTION
A Multi-Agent System for Tracking the Intent of Surface Contacts in Ports and Waterways. Tan, Kok Soon Oliver Project Manager C4IT-IKC2 DSTA [email protected]. Agenda. Introduction Concepts Multi-agent System Design System Validation Scenarios Recommendations and Conclusion. - PowerPoint PPT PresentationTRANSCRIPT
A Multi-Agent System for
Tracking the Intent of Surface Contacts
in Ports and Waterways
Tan, Kok Soon Oliver Project Manager
C4IT-IKC2DSTA
Agenda
• Introduction
• Concepts
• Multi-agent System Design
• System Validation Scenarios
• Recommendations and Conclusion
Introduction
• A thesis on modeling the intent of surface contacts with a multi-agent system (MAS) for asymmetric threat identification in busy ports and waterways
• Inspired by similar work done in the area of air threat assessment in Air Defense Laboratory (ADL) [Ozkan 2004, NPS]
Thesis Questions
• How can surface contact intent be modeled with a MAS for the identification of potentially hostile behaviors and threats in ports and waterways?
• Will the models be sufficiently realistic to be used as a decision aid in maritime security?
Why a MAS?
A multi-agent model is a distributed intelligence model that is a “natural” solution of a large-scale real-world problem1
• The real world problem is physically distributed– Every surface contact is an autonomous entity that we are interested in knowing its
probable intentions;• The knowledge to solving the real world problem is widely distributed and
heterogeneous– No one agent or system is "knowledgeable" enough to trawl and mine databases,
process real-time sensor data, monitor for rule violations or suspicious behaviours etc;
• The sources of data are distributed over networks– Naturally this encourages us to take a distributed view of a solution for the real world
problem; and• The real world problem is too complex to be analysed as a whole
– There are too many parameters and constraints to be considered altogether. Local approaches, partitioning the large problem into smaller and more tractable sub-problems, can produce results quickly.
1. Ferber, J., Multi-Agent Systems An Introduction to Distributed Artificial Intelligence, Addison-Wesley, 1999.
MAS Objectives
A multi-agent system (MAS)• To help the human operator sieve through
hundreds of surface contacts• To integrate intelligence and information from as
many sources as possible• To highlight any suspicious or potentially hostile
surface contacts
Requirements of the MAS
• Support rules and regulations of a Vessel Traffic Service (VTS) such as:– Traffic Separation Scheme (TSS), part of the
International Navigation Rules defined by the International Maritime Organization
– the 1972 Collision Regulations (72 COLREGS)– International Ships and Port Facilities Security (ISPS)
Code (To be implemented)– all other practices of safe navigation and prudent
seamanshipPredefined safe speed limits in TSSSafe speed limits for different surface track types
Requirements of the MAS cont…
• Use Surface Warfare Threat Assessment cues and corresponding perception of threat [Liebhaber 2002, SPAWAR Systems Center, San Diego]
• Obtained through empirical and observational studies of the threat assessment process by experienced surface warfare officers
• Each cue has a Threat Level Change Rating (TCR) that changes the threat level posed by a surface contact
1. Platform/Weapon Envelope/ESM
2. Origin-Flag
3. Range/Distance from Own-Ship (subsumed under CPA)
4. Heading (subsumed under CPA)
5. Closest Point of Approach (CPA)/Speed
6. Number of vessels (To be implemented)
7. Own support in area (To be implemented)
8. Destination
9. History/Voice communication
10 Sea Lane/Other intelligence
11. Superstructure Type (To be implemented)
12. Coordinated Activity (To be implemented)
Requirements of the MAS cont…
• Use information from ship-borne • Automatic Identification system (AIS)
• Transponder for large vessels (>300gt)• International Maritime Organization (IMO) recommendation
• Harbor Craft Transponder system (HARTS)• For smaller vessels• Applies to the Port of Singapore only
1. Track Type
2. Callsign (To be implemented)
3. IMO Number (Lloyd’s Register Number) (To be implemented)
4. Maritime Mobile Service Number (To be implemented)
5. ETA (To be implemented)
6. Destination (To be implemented)
Thesis Scope
• Identify and track the intent of surface contacts• Borrowing the ideas and techniques suggested
for identifying air threats in the Air Defense Laboratory (ADL) and use them to identify asymmetric maritime threats
• The thesis does not cover the issue of track detection i.e. assumes perfect instantaneous detection with 100% reliability
• The issue of interdiction when a potentially hostile track has been identified is also beyond the scope of this thesis
Some Concepts
• Traffic Separation Scheme (TSS)
• Security Zones for HVUs
• Security Zones for Restricted Areas
• Areas-To-Be-Avoided (ATBA)
• Safe Speed Limits
Skip Concepts
Traffic Separation Scheme (TSS)
• A TSS is a sea lane with a predefined traffic direction
• A TSS may also has a predefined safe speed (for prudent seamanship)
• A violation occurs when a track is traveling against traffic direction or is traveling at an excessive speed
Security Zones for HVUs
• Every High Value Unit (e.g. cruise liner, tanker) have their own predefined multiple security zones
• Only some type of tracks (e.g. Police Coast Guards) are allowed within these security zones
• Each security zone is defined with an alert time threshold (represents a measure of urgency when these zones have been infringed)
Radius = 0.2nm, Alert Time = 15min
Radius = 0.5nm, Alert Time = 10min
Radius = 0.8nm, Alert Time = 5min
Security Zone Violation Example
A A security zone violationsecurity zone violation occurs i.e. a track is occurs i.e. a track is coming in coming in too near,too near, too too soonsoon,, if an if an unauthorized unauthorized tracktrack has has
1.1. a a CPACPA (Closest Point of (Closest Point of Approach) within a zone, Approach) within a zone, andand
2.2. a a TCPATCPA (Time to CPA) Time to CPA) below alert time below alert time thresholdthreshold
TCPA = 3min
CPA
Radius = 0.2nm, Alert Time = 15minRadius = 0.5nm, Alert Time = 10minRadius = 0.8nm, Alert Time =
5min
““Too near! Too soon!”Too near! Too soon!”
Security Zones for Restricted Areas (Static HVUs)
• Restricted areas (e.g. harbor, oil refineries, military installations) can have their own predefined multiple security zones
• Only some type of tracks (e.g. Police Coast Guards) are allowed within security zones
• Each security zone is defined with an alert time threshold
Radius = 0.2nm, Alert Time = 15min
Radius = 0.5nm, Alert Time = 10min
Radius = 0.8nm, Alert Time = 5min
Areas-To-Be-Avoided (ATBA)
• Restricted areas (e.g. harbor, oil refineries, military installations)
• Only allow certain types of tracks (e.g. Police Coast Guards) or certain types of track activity within these areas
• An ATBA violation occurs when an unauthorized track intrudes into a restricted area
Safe Speed Limits
• Some locations or restricted areas (e.g. harbor) may only allow tracks to travel at predefined speed limits
• Speed limits can be defined for different track types
• A violation occurs when a track exceeds any of these speed limits
The Compound Multi-agent System
• A compound multi-agent system (MAS) designed for surface contact intent tracking
• Each surface contact is represented by a track agent
• Every track agent has a nested MAS (“Russian Doll”)
Anatomy of a Track Agent
Speed Threshold Violation Agent
Friendly Intent Agent
Neutral Intent Agent
Potentially Hostile Intent Agent
Unknown Intent Agent
Track Flag Data Ticket
Track Origin Data Ticket
Track Destination Data Ticket
Track Position Data Ticket
Track Activity Data Ticket
Track Comm Data Ticket
Track ESM Data Ticket
Track Heading Data Ticket
Track Speed Data Ticket
TSS Heading Violation
Agent
Speed Violation
Agent
Location Agent
ATBA Zone Track Activity Violation Blend
ATBA Zone Track Type
Violation Blend
Security Zone Violation
Blends
Speed Threshold Violation Blend
Speed Violation
Blend
TSS Heading Violation
Blend
Composite Agents
Reactive Agents
Track Type Data Ticket
Cognitive Agents
Area-To-Be-Avoided (ATBA) Violation Agent
Security Zone Violation
Agent
Security Zone Violation
Blends
The Compound Multi-agent System cont…
• Agents in the nested MASs continuously process incoming information about their respective surface contacts
• Agents communicate and co-ordinate in order to discover the likely intent of surface contacts
Conceptual Blending
• Conceptual Blending1 is a theory about how humans process the information coming from the environment and how humans rationalize the events happening around them
• Blending is a set of mental operations for combining cognitive models in a network of mental spaces
• Mental spaces are small conceptual packets
1. Gilles, F., Turner, M., The Way We Think, Basic Books, New York, 2002
Conceptual Blending cont…
• Mental spaces are connected to long-term schematic knowledge called “frames” e.g. – The frame of sailing along a ferry route, or – The frame of traveling inside a maritime traffic
separation scheme (TSS), – Long-term specific knowledge such as a memory of
an event such as past track incursions into Area-To-Be-Avoided (ATBA) zones.
• Mental spaces are interconnected in working memory which can be modified dynamically
Conceptual Blending cont…
• Building a conceptual integration network involves setting up several mental spaces.
• Two input mental spaces with cross-space mapping to connect counterparts in these input mental spaces
• However not all elements and relations from the input spaces are projected into the blend.
• Generic spaces are used for the generic structures they contain to guide the selective projection of elements from the input spaces into blended spaces
• The blended space is the mental space where, during blending, the structure from the input mental spaces is projected onto, represented by the dotted lines
Blend
Generic Space
Input Space 1
Input Space 2
A Basic Conceptual Integration Network
Conceptual Blending cont…
• Any mental space can participate in multiple networks.• Complex integration networks can be built with arrays of
mental spaces that are connected through blending operations.
Conceptual Blending Examples
• Example of how a Security Zone violation is detected
Blend
Generic Space
Track High Value Unit
Track CPA(Closest Point of Approach)
Security Zone Radius
CPA < Security Zone Radius
Security Zone Violation
Track TCPA(Time to CPA)
Security Zone Alert TimeTime Vital Relation
TCPA < Security Zone Alert Time
Identity Vital Relation Allowed Track TypesTrack TypeTrack Type ≠ Allowed Track Types
Distance Vital Relation
Conceptual Blending Examples
• Example of how a ATBA Zone Track Activity violation is detected
Blend
Generic Space
Track ATBA Zone
Track Activity Allowed
Activity Type
Activity Vital Relation
Track Activity ≠ Allowed Activity Type
ATBA Zone Track Activity Violation
Activity Vital Relation
Location Vital RelationTrack Location Zone
Name
Track Location = Zone Name
The CMAS Library
• The communication and coordination among many different agents in the nested MAS is achieved using the Connector-based Multi-agent Simulation Library (CMAS) [John Hiles, NPS]
• The basic elements for agent communication and control within the CMAS framework are connectors.
• The agents use these connectors to externalize portions of their internal states into the multi-agent environment.
• Connectors are like plugs and receptacles that can be extended or retracted
• Signaling and coordination between the two agents occur when there are matching pairs of plug-receptacle connectors and the connectors get connected
• Stimergy (communication through change of local environment) among agents
Agent 1
Agent 2
Retracted connector
Extended response connector (Receptacle)Plug-
Receptacle match Extended stimulus
connector (Plug)
A MAS of MASs (“Russian Doll”)
• A track agent appears as a single agent that exists in another external MAS environment
• In this external MAS environment, there is a layer of regional agents that monitor behaviors of all track agents
• Two types of regional agents detect coordinated behavior that resembles an impending swarm or a “wolf-pack attack
Detection of Coordinated (Swarm/ “Wolf-pack”) Attack on a moving HVU
If two or more track have If two or more track have 1.1. CPAsCPAs to a HVU to a HVU (High Value Unit)
that are that are very closevery close e.g. 0.1 nm, e.g. 0.1 nm, andand
2.2. TCPAsTCPAs violations against the same HVU that are about to occur within a very short period of time e.g. 5 mins
““Too near!Too near! Too soon! Too many!”Too soon! Too many!”
The MAS will consider multiple near-simultaneous security zone violations a possible sign of an impending coordinated attack i.e. too near, too soon, too many
Note: A “wolf-pack” attack is a common maritime terrorist attack tactic comprising of a cluster of small terrorist craft approaching and surrounding a larger target craft from multiple directions simultaneously
Detection of Coordinated (Swarm/Wolf-pack) Attack on a static HVU
If two or more track have If two or more track have 1.1. CPAsCPAs to a restricted location to a restricted location
(static HVU) that are very close (static HVU) that are very close e.g. 0.1 nm, ande.g. 0.1 nm, and
2.2. TCPAsTCPAs violations against the same location that are about to occur within a very short period of time e.g. 5 mins
““Too near!Too near! Too soon! Too many!”Too soon! Too many!”
The MAS will consider this a possible sign of an impending coordinated attack i.e. Too near, Too soon, Too many
Anatomy of a Regional Agent
Swarm Detection (Location)
Agent
Swarm Detection (Track)Agent
Swarm Detection (Location) Blend
Swarm Detection (Track) Blend
Track Agent 1
Security Zone (Track)
Violation Blend
Swarm Detection (Track)
Weighting Agent
Swarm Detection (Location)
Weighting Agent
Track Agent 2
Swarm Detection (Track)
Weighting Agent
Swarm Detection (Location)
Weighting Agent
Regional Agent 1
Regional Agent 2
Security Zone (Location)
Violation Blend
Security Zone (Location)
Violation Blend
Cognitive Agents
Security Zone (Track)
Violation Blend
Conceptual Blending Examples
• Example of how a Coordinated Attack (Swarm/Wolf-pack) by 2 or more different tracks on the same HVU is detected by a Regional Agent
Blend
Generic Space
Security Zone
Violation Blend A
CPA(A) CPA(B)
HVU(A) == HVU(B)
Swarm Detection Blend
TCPA(A)TCPA(B)
Time Vital Relation
(CPA(A) – CPA(B)) < CPA_DIFFERENCE_THRESHOLD
Identity Vital Relation HVU (B)HVU (A)
(TCPA(A) – TCPA(B)) < TCPA_DIFFERENCE_THRESHOLD
Security Zone
Violation Blend B
Track BTrack A
Distance Vital Relation
Too much of a coincidence?
The Intent Agent
• The top layer of agents of the nested MAS environment inside a track agent
• Each intent agent has a corresponding intent model• Four intent agents:
1. Friendly,
2. Neutral,
3. Potentially Hostile, and
4. Unknown• Intent agents use information provided by internal
agents from the lower layers as well as from external regional agents
Anatomy of an Intent Agent
Track Type Track Flag Track Origin Track Destination Track CommTrack ESM
ATBA Zone Track Activity
Violation
ATBA Zone Track Type
Violation
Security Zone Violation
Speed Threshold Violation
Speed Violation TSS Heading Violation
WeightingStrategy
Weighting Agents
Swarm Detection (Track)
Swarm Detection (Location)
MARSEC Level(bias)
Competitive Intent Models
• An Intent agent is a composite agent– Family of weighting agents is responsible for obtaining
information • User-defined weights (similar to Threat Level Change
Ratings) assigned to each piece of track information (attributes and violations)
• The intent model in an intent agent is represented by a weighting strategy
• Weighting agents receive track information on track attributes and track violations and informs the weighting strategy
• Weighting strategy computes a weighted score using a set of user-defined weights
• The intent models will compete and the one with the highest score represents the current intent of the track
Weighting Biases based on Regional Intelligence
• Maritime Security (MARSEC) Levels
• Warning against unidentified potential threats
• Equivalent to HSAS• Heightens/Lowers the
“alertness” of the weighting strategies by applying biases to the computed weighted scores.
The VTS-C2 MAS System
Features of the VTS-C2 system• A Java-based mock C2
(Command & Control) system• Supports geo-rectified maps,
tactical overlays and symbol drawing, graphical and tabular displays of C2 information
• Shows graphics representing tracks, TSSes, and restricted areas
• Integrated CMAS-based (Connector-based Multi-agent Simulation Library) compound MAS
• Integrated Simkit-based DES (Discrete Event Simulation) simulator [Arnold Buss, NPS]
– Tracks are linear uniform movers with delays at waypoints
– Proximity sensors are used to report location of tracks
Capabilities of the VTS-C2 MAS
1. Ability to detect future incursions into the security zones of HVU (high value units)
2. Ability to detect future incursions into restricted areas e.g. cruise center, oil refineries, military installations
3. Ability to detect illegal activities in restricted areas e.g. fishing in non-fishing zone
4. Ability to detect TSS (traffic separation schemes) violations e.g. against traffic direction, stopping in TSS termination zones
5. Ability to detect speed violations in restricted areas e.g. harbor
6. Ability to detect atypical track behaviors e.g. excessive speed
7. Ability to perform surface threat assessment based on tracks’ attributes e.g. platform, flag, origin, ESM, destination
8. Ability to detect VTS (Vessel Traffic Service ) violations e.g. collision detection, wrong/unknown destination, no verbal communication
9. Ability to detect coordinated maneuvers/attacks e.g. swarm/”wolf-pack”
10.Ability to incorporate regional intelligence e.g. MARSEC levels
Capabilities of the VTS-C2 MAS cont…
System Architecture
Compound MAS
Java-basedVTS-C2 system
TSS Definitions(traffic direction, speed limits)
ATBA (Area-To-Be-Avoided) Definitions(allowed track types, allowed track activity)
Safe Speed Limits for each track type
Security Zone Definitions(CPA radius and alert time)
Pre-defined Information
Maritime Sensors(Simkit-based Discrete Event
Simulator)Safe Speed Limits for certain locations and zones
Hourly/Ad-hoc Reports(Police Coast Guards/ Military Patrols)
24-hour Offshore Advance Reports(International Maritime Organisation Standard Ship Reporting System)
Databases (Lloyds, ICA)
Track Position, Speed, Heading, Destination
Automatic Identification System
Track Type, Callsign, IMO Number (Lloyd’s Register Number), Maritime Mobile Service Number, ETA, Destination
To be implemented
Information Sources (MPA)
Ship Manifests(Cargo/ Crew/ Passenger information) (ICA)
MAS of MASs
MARSEC Level
Harbor Craft Transponder System
Anecdotal Anomalies Detection
Operational Anomalies Detection
Pre-defined Information Settings
Weight and Bias Settings
Agent Threshold Parameters
Intent Scores Information
Validation Process
• Four validation sessions held with four groups of surface warfare assessment experts or naval officers from the Republic of Singapore Navy (RSN) and the US Navy
• Participants have more than 100 years of harbor security, patrol or at-sea experience between them
• Participants are first briefed on the features of the MAS and the mock VTS-C2 system
• Participants are next presented with several discrete-event simulations on scenarios involving the Port of Singapore and the surrounding waterways
Validation Process cont…
• Each scenario features multiple surface contacts of different types, moving in an area that is populated with traffic separation schemes and restricted areas
• The scenarios will feature different kinds of hostilities that may exist but the participants are not told of the details in advance
VTS-C2 System Demo
Validation Scenarios
Skip Scenarios
Sample Scenario 1(TSS violations, Impending collision)
TSS violation (speed and heading) and an impending collision between a leisure craft and a cruise liner
Sample Scenario 2 (Coordinated attacks by multiple tracks)
Possible coordinated attack by two fishing vessels on SZone3
Sample Scenario 3 (Incursion into security zone around HVU)
Detected incursion by fishing vessel in the security zone around tanker
Validation Results
• Very encouraging responses from the participants – good “proof of concept” that demonstrates
how a decision support tool can help the decision maker identify potentially hostile contacts
• Officers from the RSN commented that the MAS can be an important decision support tool in their existing C2 systems
Validation Results cont…
• Some concerns:– Although the system is able to process large amount
of information, there may still be an overwhelming information glut
– Intent labels not semantically suitable according to operational doctrine if the MAS was to be integrated into an existing C2 system
– False alarms that may arise due to the heavy traffic conditions in the Port of Singapore compounded by clutter caused by non-moving surface contacts; Need to select weights carefully to reduce the number of false alarms; “False alarms is better than no alarms”
– System is highly dependent on accuracy and reliability of information sources e.g. sensors, humans etc.
Future Work To Be Done
• Need to fine-tune the MAS and verify that system works well against real world vessel traffic situations in the waters of Singapore.
– The system may be tested during maritime security experiments
• Further validation with objective measures of performance:
1. Type I (false negatives) and Type II (false positives) errors,2. Number of factors that the system can process as
compared to a human operator,3. Time taken by the system to identify hostilities as
compared to a human operator i.e. amount of lead time the system is able to provide in situations of hostilities
Future Work To Be Done cont…
• Detect more unusual track maneuvers1. Many maneuvers / zig-zags2. Suspicious course changes that seem to match the movement
of a HVU3. Monitor course/heading of tracks in more detail (e.g. in terms of
Steady and closing/opening or Turn to closing/opening)4. Hiding or evading from PCG/Military Patrols5. More co-ordinated activities among tracks e.g. Simultaneous
attacks on multiple HVUs or restricted areas• Additional VTS violations
1. Failure to submit Offshore Advance reports, and2. Wrong/unknown destinations
• Incorporate specific intelligence based on 1. track attributes e.g. track type, origin, activity; and2. historical data e.g. piracy reports
Future Work To Be Done cont…
• Beyond more than just rules, it is also possible to have complex cognitive agents that can learn and adapt:– automatically learn appropriate weight settings to reduce false
alarms, or – automatically “retire” agents that are producing too many false
alarms, or– Automatically re-adjust security zone radii according to traffic
conditions, or– have the ability to “forgive”, over time, tracks for their past
violations• Act as proxies to external entity/relationship engines,
information fusion/search engines or web services i.e. distributed intelligence– Pro-active search by agents for anecdotal anomalies i.e. form a
paper trail from information sources such as ship registries, sail plans, Offshore Advance reports, cargo/passenger manifests etc
Conclusion
• Thesis question 1 – “How can surface contact intent be modeled with a MAS for the identification of potentially hostile behaviors and potential threats in ports and waterways?”– A multi-agent system has been developed to track the intent of
multiple surface contacts moving in ports and waterways.– Four intent models have been developed based on VTS rules,
surface warfare threat assessment cues and track behaviors
• Thesis question 2 – “Will the models be sufficiently realistic to be used as a decision aid in maritime security?”– Face validation showed that the system can be a useful decision
support tool in the maritime security of Singapore