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Speedy Agent Car: The Prototype. Agent Technology : Final Project Lecturer: Prof. Ho Cheng-Seen Presented by: M9215801 - Irfan Subakti NTUST, June 7 th 2004. Overview. Agent Implementation Fuzzy sets theory on Agent Case study: GPS supported car  Speedy Agent Car’s prototype

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Speedy agent car the prototype
Speedy Agent Car: The Prototype

Agent Technology: Final Project

Lecturer: Prof. Ho Cheng-Seen

Presented by:

M9215801 - Irfan Subakti

NTUST, June 7th 2004


  • Agent Implementation

  • Fuzzy sets theory on Agent

  • Case study: GPS supported car  Speedy Agent Car’s prototype

  • Development possibilities


  • To show the implementation of agent

  • Here, this agent empoweredfuzzy set theory

Implementation of agent
Implementation of Agent

  • Agent: A computing entity that performs user delegated tasks autonomously

  • Characteristics:

    • Delegation

    • Communication skills

    • Autonomy

    • Monitoring

    • Actuation

    • Intelligence

  • We implemented agent in order to support user on maintain speed and distance between their cars.

  • Supported by fuzzy set theory and work autonomously, thinking by itself but can monitored as well. Also it delegated for most part activities, and communicate via GPS services. User can actuate this agent or just turn off.

Knowledge of speedy agent car
Knowledge of Speedy Agent Car

  • Regarding fuzzy sets theory in Agent Technology subject, it’s interesting to implement some theory into real world (i.e., programming language).

  • Knowledge of Speedy Agent Car, defined by:

    • IF Distance is Narrow AND Speed is Slow THEN Command=KeepSpeed

    • IF Distance is Narrow AND Speed is Fast THEN Command=SlowDown

    • IF Distance is Wide AND Speed is Slow THEN Command=SpeedUp

    • IF Distance is Wide AND Speed is Fast THEN Command=KeepSpeed

Knowledge of speedy a car cont d
Knowledge of Speedy A. Car (cont’d)

  • Explanation:

    • 'Narrow' are between 0 ~ 30 m

    • 'Wide' are between 10 ~ more than 30 m

    • 'Slow' are between 0 ~ 70 km/hours

    • 'Fast' are between 30 ~ more than 70 km/hours

    • All the max index set to value MaxIdx (e.g., 100) to make it convenient.

    • Remember that index are between 0 ~ MaxIdx

    • But the number of index is MaxIdx + 1

    • 'KeepSpeed' are between -10 ~ 10 km/hours2

    • 'SlowDown' are between -10 ~ 0 km/hours2

    • 'SpeedUp' are between 0 ~ more than 10 m/hours2


  • Here, Car1 is in front of Car2. We are in Car2.

  • All we have to do is maintain our car (Car2) regarding speed of Car1 and distance between our car and Car1.

  • We can trait our car to do something (i.e., command) whether keep our current speed, slow down with decelerate our speed or speed up with step on the gas.

Algorithm continued
Algorithm (continued)

  • Defined fuzzy sets of:

    • DistanceNarrow & Wide

    • SpeedSlow & Fast

    • CommandKeepSpeed, SlowDown & SpeedUp

  • Random acceleration of Car1, set speed of Car1 and update position of Car1.

  • Find distance between Car1 & Car2.

  • From speed of Car1 and distance between two cars, apply 4 rules above to get command that Car2 have to do (whether KeepSpeed, SlowDown or SpeedUp).

  • Updategraph and values during process, also position of Car2.


  • Below are graphs that depict fuzzy sets about Distance, Speed and Command.

Running program
Running Program

Animation of Car1 & Car2. Car2 that always maintain it’s speed & distance to Car1.

Values obtained during running. It corresponds to Car1 & Car2

Animation of graph obtained by program from rule #1, #2, #3, #4 & Final Result.

Graph of Distance, Speed & Command. It come from knowledge that user defined.

Result and evaluation
Result and Evaluation

  • From this prototype, we succeed to implement fuzzy set theory into an agent that maintenancespeed and distance of a car, regarding with another car.

  • This is an prototype, so we assumed that position and speed of another car obtained by GPS service.

  • Actually this is just simulation, for a real implementation, we have to consider:

    • GPS

    • Hardware implementation

    • Sophisticated coordination between involved parts

    • Regulations from government

    • Community supported

    • Feasibility study by many parties

Development possibilities
Development Possibilities

  • Here we just concerning about the position of car in front or behind another car, we can develop to all possibilities of position on the road.

  • Another things were possibly:

    • Moving object on the road, not just cars.

    • Obstacles on the road

    • Traffic light arrangement

    • Traffic jam resolution

    • Distribution of flows on multiple path on the road

    • Effective traveling path

    • For common transportation: on the land, water or on the air

    • Military system

Thank you for your attention
Thank You!For Your Attention … 