Knowledge Modeling in Various applications in Traffic Systems

Knowledge Modelling in Various applications in

Traffic SystemsPresented by : Yomna Hassan

Submitted to : Dr. Hesham Hassan

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

Generic Tasks CommonKADS

Techniques of Knowledge Modelling

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

CommonKADS in Traffic Systems

CommonKADS

organization modeltask model

agent model

knowledge-intensive

task

communicationmodel

knowledgemodel

designmodel

requirementsspecification

for interaction functions

requirementsspecification

for reasoning functions

task selected in feasibility studyand further detailed in Task and Agent Models

Knowledge Categories

Generic Traffic System

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

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)

Traffic system Domain architecture

Task decomposition structure

primitive inferences of the knowledge model

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

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

MAS-CommonKADS

Mas commonkads

Existence of dynamic traffic systems Crowd-sourcing dependent

Dynamic Virtual Organization Creation for Traffic Systems

The CommonKADS control structure models for DVO

identification and formation phases

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