Location-based taxi service in wireless communication environment

Federal University of Minas Gerais

Location-Based Taxi Service in WirelessCommunication Environment

Aloizio Pereira da [email protected]

School of Information Technology and Engineering (SITE)University of Ottawa, April 2003

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[email protected]


Contents

1. The Problem2. The Simulator3. Experimental Results4. Conclusions

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The Problem

Context

• Mobile users appear at different locations randomly over time• They need to be transported to different destination points• There is a fleet of taxi that performs the transport

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The Problem Federal University of Minas Gerais

Objective

• Allocation Algorithm– To define which taxi should be assigned⇒ mobile user– To minimize the running distance and time of both

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The Simulator

• Applet form and a stand-alone application• Java 2 SDK 1.3.1 on a SuSe Linux 7.1 platform• It is responsable for:

1. generating new requests according to statistical distribution2. running the taxi allocation algorithm3. assigning taxis to mobile users4. updating the current dispatching situation

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The Simulator Federal University of Minas Gerais

Simulator Components

• Map• Approaches• Time Management• Mobile Users• Taxis• User Interface

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Map

• Euclidean area⇒ rectangular grid 300 pixels X 300 pixels• road map of Belo Horizonte’s central region• scale is 1:12000• area 3.36 km x 3.36 km square• road network⇒ directed graph

– each edge depicts an one-way road– each node depicts an intersection– weights⇔ edges⇒ distance– avenues and street⇒ speed limits– each edge ≡ avenue or street⇔ θ angle

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Approaches Federal University of Minas Gerais

Current Approach Modelling

zone 1zone 2

zone 3 zone 4

queue of zone 1

zone 1

zone 3

taxi_i

taxi_i

zone 4

handofffirst

handoffsec.drop off

Fig.1 and Fig.2: Zone Layout

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New Approach Federal University of Minas Gerais

: GPS

: Mobile User : Gateway : Taxi

RFTS

5.1 : AM = assignmentMatrix()

3 : Getdatalocation()

1 : taxilocation = GetTaxilocation()

5 : RunAssignmentalgorithm(SDM,RM)

: AssignmentAlgorithm: Floyd−Warshall Algorithm

6.2 : send(MUDP)

4 : RunFloyd(mulocation, taxilocation)

4.2 : RM = routeMatrix()

4.1 : SDM = distanceMatrix()

6.3 : send(ACK)6.1 : send(ACK)

6 : send(TDP)

1.1 : mulocation = GetMulocation()

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Taxi Assignment Problem Model

Minn∑i=1

m∑j=1

di,jXi,j (1)

subject to

n∑i=1

Xi,j = 1 j ∈ 1,2, . . . ,m (2)

m∑j=1

Xi,j ≤ 1 i ∈ 1,2, . . . ,n (3)

Xi,j ∈ 0,1 (4)

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T_1

T_2

T_3

T_4

T_5

T_6

. . .

1st 2nd 3rd 4th time window´s number

800s

400s

200s

600s

L

0s

Assignment Process

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Time Management

• discrete time steps• time horizon⇒ the entire day⇒ 24 hours• a day is divided into five periods:

Periods Interval Time Probability %early-morning 00:00 - 06:00 10late-morning 06:00 - 12:00 38lunch-time 12:00 - 14:00 05early-afternoon 14:00 - 17:00 40late-afternoon 17:00 - 24:00 07

Table: Service request probabilitydefinition per periods

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Mobile Users

• arrival process⇒ Poisson model• interarrival time⇒ Exponential distribution• random location⇒ random destination

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Simulator Components Federal University of Minas Gerais

Mobile Users

SERVICE WAITING

DROPOFF

request taxi service allocated taxi

no allocated taxi

taxi arrivalat mobileuser origin

taxi arrivalat mobile userdestination

end of service

REQUIRINGNEW−USER IN−TRANSIT

Fig: Mobile users states transition diagram

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Taxis

• random location• each taxi⇒ carry one mobile user at a time• taxis speed⇔ speed limit allowed on the road map• the driving method does not follow any standard movement

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Simulator Components Federal University of Minas Gerais

Taxis

WAITING PICKUP

DROPOFF

scheduledaction

action future

allocatedmobile user

taxi arrival at mobile userdestination

Fig: Taxis states transition diagram

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User Interface

• The interface consists of three sections:– the left portion⇒ setup simulation parameters– the central portion⇒ taxi service in action– the right portion⇒ information about the current simulation

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Simulator Components Federal University of Minas GeraisUser Interface

Fig: Simulator user interface

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Experimental Results

• Each simulation has been done for days of 24 hours• Terminologies definition

Pickup: a link that direct from the taxi’s current location to user’s originDropoff: a link that directs from the user’s origin to the user’s destinationTransport: Transport = Pickup + Dropoff

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Experimental Results Federal University of Minas Gerais

Average Total Distance Traveled for Both ApproachesPer Number of Users

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

0 1000 2000 3000 4000 5000

Average Total Distance Traveled (Km)

Number of Mobile Users

Current ApproachNew Approach

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Average Travel Time for Both Approaches Per Number of Users

100

150

200

250

300

350

400

0 1000 2000 3000 4000 5000

Average Travel Time (sec.)

Number of Mobile Users

Current ApproachNew Approach

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Average Pickup Time Per Different Time Windows

20

40

60

80

100

120

140

0 500 1000 1500 2000 2500 3000

Average Pickup Time (sec.)

Time Window (sec.)

New ApproachCurrent Approach

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Average Pickup Time For New Approach For Two SimulationRuns

Fig 1: Time Window = 1000 Fig 2: Time Window = 2000

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Conclusions

• The integration of taxi service with mobile environment• This work models and develops a distributed environment⇒ Mobile Users

and Taxis• We have compared the new approach with the current approach• Our results have showed gains with the new approach,

which is able to locate and dispatch the nearest taxi.

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Conclusions Federal University of Minas Gerais

• Without location technologies the current taxi companiescannot manage all of the vehicles• Location-based taxi service reduces cost and

provides minimum time and distance routing for pickup• Computing, wireless communications and location information

can be combined to provide location-based services.

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This Work Did Not Consider:

• demand forecasting• additional stochastic elements• transportation of multiple mobile users• direct communication between mobile users and taxis• strategy for other kinds of transportation

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END Thanks Federal University of Minas Gerais

Location-Based ServicesSchool of Information Technology and Engineering (SITE)

University of Ottawa, April 2003

Questions

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Location-based taxi service in wireless communication environment

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