1. Knowledge Modelling in Various
applications in Traffic Systems
Presented by : Yomna Hassan
Submitted to : Dr. Hesham Hassan

2.  Techniques of Knowledge Modelling
 Difference in knowledge modelling techniques
 Generic Tasks in Traffic Systems
 CommonKADS in Traffic Systems
 MAS CommonKADS
 DVO CommonKADS model
 Conclusions
Contents

3.  Generic Tasks
 CommonKADS
Techniques of Knowledge Modelling

4.  Generic Tasks focus mainly on knowledge part of the
system
 CommonKADS includes the organizational structure
of the whole system, tasks and communications, and
knowledge model.
 CommonKADS is more adaptive to existence of
intelligence within the system structure
Difference in knowledge modelling
techniques

5. CommonKADS in Traffic
Systems

6. CommonKADS
organization model
task model
agent model
knowledge-
intensive
task
communication
model
knowledge
model
design
model
requirements
specification
for interaction functions
requirements
specification
for reasoning functions
task selected in feasibility study
and further detailed in
Task and Agent Models

7. Knowledge Categories

8. Generic Traffic System

9.  In this modelling context, which reveals an activity based on experiences (i.e. cases) reusing
 locate the incident reusing activity into the global control activity.
 identify relevant descriptors of the incident case model.
 identify discriminant index to organize the case base.
 define a similarity metric for matching.
 register knowledge necessary to adapt solution part of the selected case, in order to
solve the current problem.
 Elicitation sessions of the expertise, in the control room, are based on different methods:
document analysis, interviews, repertory grids, traffic manager's activities analysis and
results of the activity (problem reports).
 Each method presents an own goal and allows, generally, to obtain a particular type of
knowledge. Therefore, it is necessary to use these methods concurrently, one cancelling out
the drawbacks of others taken apart, benefiting the qualities of each one
Knowledge Elicitation

10.  From interviews with traffic management experts, we
have found that a large part of their knowledge is
episodic. That is, the expert solves a new problem by
relating the current network situation to his previous
experiences.
 These experiences are sometimes specific incidents,
with real dates and places, and sometimes general
classes of similar occasions.
Knowledge Elicitation (Cont’d)

11. Traffic system Domain architecture

12. Task decomposition structure

13. primitive inferences of the
knowledge model

14.  Focus on human –computer not computer-computer
interactions
 A restricted form of dynamic task assignment can be
done
 Multi-partner transactions not dealt with naturally
 Therefore a new model: coordination model is
proposed
Disadvantages of CommonKADS in
Multi-agent systems

15.  MAS-CommonKADS extends the knowledge
engineering methodology CommonKADS with
techniques from object oriented and protocol
engineering methodologies.
MAS-CommonKADS

18. Mas commonkads

19.  Existence of dynamic traffic systems
 Crowd-sourcing dependent
Dynamic Virtual
Organization Creation for Traffic
Systems

20. The CommonKADS control structure
models for DVO identification and
formation phases

21. 1. Yassa, Morcous. "Utilizing CommonKADS as Problem-Solving and Decision-Making for
Supporting Dynamic Virtual Organization Creation." IAES International Journal of Artificial
Intelligence (IJ-AI) 3.1 (2014).
2. Davidsson, Paul. "Intelligent Transport and Energy Systems Using Agent
Technology." Twelfth Scandinavian Conference on Artificial Intelligence: SCAI 2013. Vol. 257.
IOS Press, 2013.
3. Gascuena, Jose M., and Antonio Fernández-Caballero. "On the use of agent technology in
intelligent, multisensory and distributed surveillance." Knowledge Engineering Review 26.2
(2011): 191-208.
4. Abreu, Bruno, et al. "Video-based multi-agent traffic surveillance system."Intelligent
Vehicles Symposium, 2000. IV 2000. Proceedings of the IEEE. IEEE, 2000.
5. Caulier, Patrice, and Bernard Houriez. "A case-based reasoning approach in network traffic
control." Systems, Man and Cybernetics, 1995. Intelligent Systems for the 21st Century., IEEE
International Conference on. Vol. 2. IEEE, 1995.
6. Dieng, Rose, et al. "Building of a corporate memory for traffic-accident analysis." AI
magazine 19.4 (1998): 81.
7. Molina, Martin, J. O. S. E. F. A. HERN Á, and JOS É. CUENA. "A structure of problem-solving
methods for real-time decision support in traffic control."International Journal of Human-
Computer Studies 49.4 (1998): 577-600.
8. Iglesias, Carlos A., et al. "A methodological proposal for multiagent systems development
extending CommonKADS." Proceedings of the 10th Banff knowledge acquisition for
knowledge-based systems workshop. Vol. 1. 1996.
References