1. Multi Agent Approach for Time Based Vehicle Arrangement in Reputed Taxi Companies.
6037PS – D. A. P. Peiris
Supervisors
Mr. D.D.A. Gamini
Mr. B. Hettige

2. Introduction
Taxi service is supporting to national transportation system to reduce their work load and make comfortable transport experience to customers. Last few years, new software architecture for managing the taxi service at the tactical and operational level has emerged.
It views the taxi service as composed of a set of intelligent software agents, each responsible for one or more activities in the taxi service and each interacting with other agents in the planning and execution of their responsibilities. Agents really helpful to minimize the complexity of problem generated and scalability of agent help to making reliable decision and self organize the system.

3. Why?
Number of reputed taxi company in colombo district – about 12
Number of taxies on colombo per day
01) budget taxies - more than 1100
02) car - more than 750
03) van - more than 250
Number of approximate hires per day in colombo – more than 8500
Approximate worth per day 12.5 million
Witness of this situation – Last year (2015) Multi billions company of UBER, PickMe, HIRE1 and Vgo are established in Sri Lanka. All of these companies are technical companies but not traditional taxi companies.

4. Problems of traditional system
More than 6% of hire cancelation ratio per day.
More than 34% of lost millage per vehicle.
More than 45% of average waiting time per vehicle per hire. (27 min)
More than 12% of average waiting time per customer per hire. (20 min)
More than 47% of average time duration waiting on dispatch queue for dispatch per hire. (9 min)

5. Solution Steps – According to L. R.
Develop the vehicle tracking and monitoring system
Develop the intelligent driver mobile app for communicate with drivers
Develop the interactive client mobile app to getting client all requirement easily.
4) Multi agent base management system for manage the each and every expectable and un expectable situation base on prior knowledge.

6. Solution

7. Associated Technologies
NMEA, GPS data protocol for vehicle tracking and monitoring system
Android Technology for driver and client mobile app development
Google Cloud Messaging (GCM) architecture for server client communication
Java Agent Development Environment (JADE) for managing complexity of this problem and re scheduling the exiting system without hassle.

8. Vehicle Tracking & Monitoring System

9. GPS data analysis for driver mobile app
Speed Graph of Taxi

10. GPS data analysis for driver mobile app
Ignition Graph of Taxi

11. State Analysis of Vehicle moving, Driver and Hire

12. State and Driver Messages
Moving State
Driver State
Hire State
Message to Driver 1
None
Are you free to getting hires? 2 3
Accept new job? 4
Are you at the place? 5
Did You start the hire?
Any 6
Hire has been canceled! 7
Did you finish the hire?
Are you going to waiting? 8
Did you stop waiting?

13. Intelligent Driver App

14. Interactive Client App

15. Agent Architecture

16. Automated Dispatching
Selecting taxi for dispatching
Re arrange the taxis for economical dispatching
Re-arrange the waiting taxis for new hires
Apply the ride sharing to new bookings
Apply the booking sharing to new bookings

17. Selecting Taxi for Dispatching - Agent

18. Selecting Taxi for Dispatching - Real
Taxi : Cab35209
EDF :
Taxi : Cab43304
EDF :
Taxi : Cab43814
EDF : 2.356
PL : #
PT : :45:00
DL : #
VT : Regular
VM : None
VIP : None
Lan : English
RD : None
RS : 1
BS : 0
Taxi : Cab35181
EDF : 3.215
Taxi : Cab43815
EDF : 3.34
Taxi : Cab35176
EDF :

19. Selecting Taxi for Dispatching - Real
Taxi : Cab35209
EDF :1.3725
Taxi : Cab43304
EDF :
Taxi : Cab43814
EDF : 2.356
PL : #
PT : :45:00
DL : #
VT : Regular
VM : None
VIP : None
Lan : English
RD : None
RS : 1
BS : 0
Taxi : Cab35181
EDF : 3.215
Taxi : Cab43815
EDF : 3.34
Taxi – Cab35176
EDF –

20. Waiting Taxi arranging to New Hire - Real
ID : 1727
PL : #
PT : :20:00
DL : #
VT : None
VM : None
VIP : None
Lan : None
RD : None
RS : None
BS : None
ID : 1684
PL : #
PT : :10:00
DL : #
DV : Cab43314
ASW : 1h 5min
Taxi : Cab43314
ABI : 1684
CBI : 1727
EDF :

21. Waiting Taxi arranging to New Hire - Real
ID : 1727
PL : #
PT : :20:00
DL : #
DV : Cab43314
ASW : 0 min
ID : 1684
PL : #
PT : :10:00
DL : #
DV : Cab43314
ASW : 1h 5min
Taxi : Cab43314
ABI : 1727
PBI : 1684
CBI : None

22. Re-arranging Taxi - Agent

23. Re-arranging Taxi - Real
Taxi : Cab43315
ABI : 1745
CBI : None
Taxi : Cab35181
ABI : 1734
CBI : None
ERF1 : 3.456
ID : 1745
PL : #
PT : :54:00
DL : #
DV : Cab43315
ASW : 0 min
ID : 1734
PL : #
PT : :52:00
DL : #
DV : Cab35181
ASW : 0 min

24. Re-arranging Taxi - Real
Taxi : Cab43315
ABI : 1734
CBI : None
Taxi : Cab35181
ABI : 1745
CBI : None
ID : 1734
PL : #
PT : :52:00
DL : #
DV : Cab35181
ASW : 0 min
ID : 1745
PL : #
PT : :54:00
DL : #
DV : Cab43315
ASW : 0 min

25. Ride Sharing - Agent

26. Ride Sharing - Real AF : 3 ID : 1812 PL : 6.866503# 79.876399
PT : :02:00
DL : #
VT : None
VM : None
VIP : None
Lan : None
RD : None
RS : 1
BS : None
DV : Cab35796
ID : 1814
PL : #
PT : :03:00
DL : #
VT : None
VM : None
VIP : None
Lan : None
RD : None
RS : 1
BS : None
Taxi : Cab35796
ABI : 1812
CBI : None

27. Ride Sharing - Real ID : 1812 PL : 6.866503# 79.876399
PT : :02:00
DL : #
VT : None
VM : None
VIP : None
Lan : None
RD : None
RS : 1
BS : None
DV : Cab35796
ID : 1814
PL : #
PT : :03:00
DL : #
VT : None
VM : None
VIP : None
Lan : None
RD : None
RS : 1
BS : None
DV : Cab35796
Taxi : Cab35796
ABI : 1812, 1814
CBI : None

28. Booking Sharing - Agent

29. Booking Sharing - Real ID : 1871 ID : 1857 PL : 6.876952#79.864693
PT : :15:00
DL : #
VT : None
VM : None
VIP : None
Lan : None
RD : None
RS : None
BS : 1
ID : 1857
PL : #
PT : :14:00
DL : None
VT : None
VM : None
VIP : None
Lan : None
RD : None
RS : 0
BS : 0
DV : Cab35796
AF : 2
Taxi : Cab43814
ABI : None
CBI : None
Taxi : Cab35796
ABI : 1857
CBI : 1871

30. Booking Sharing - Real ID : 1857 PL : 6.877549#79.866410
PT : :14:00
DL : None
VT : None
VM : None
VIP : None
Lan : None
RD : None
RS : 0
BS : 0
DV : Cab35796
ID : 1871
PL : #
PT : :15:00
DL : #
VT : None
VM : None
VIP : None
Lan : None
RD : None
RS : None
BS : 1
DV : Cab35796
Taxi : Cab43814
ABI : 1871
CBI : None
ID : 1871
PL : #
PT : :15:00
DL : #
VT : None
VM : None
VIP : None
Lan : None
RD : None
RS : None
BS : 1
DV : Cab43814
Taxi : Cab35796
ABI : 1857
CBI : None

31. Evaluation Booking cancellation ratio reduce to 8% to 0.6%
Average waiting time for dispatching reduce to 2 to 25 seconds
Re arrangement of dispatched taxis increased to 0.9% to 8.1%
Waiting vehicle arrange to new hires increased to 0.22% to 13.3%
Ride sharing increase to 0.4% to 7.7%
Booking sharing apply to 6.1% for all bookings.

32. Conclusion
Referring historical data of client is powerful weapon arranging taxis
Handling complexity and re scheduling the real time systems can manage with multi agent systems.
Ride sharing within known client is good approach to resole the sharing limited resource.
Booking sharing is good approach to reduce to client hail time on road and utilize the resources maximally.

33. Acknowledgement
I am grateful to thank Radiant AC Cabs PVT LTD Company and their employees to providing their actual to us top to bottom.
I am grateful to thank George Rzevski, (Professor Emeritus, Complexity Science and Design, The Open University, UK +44 (0) , for providing many tactic for managing above problem theoretically and practically.

34. Thank You & Questions ???