Nusrat AliIndian Institute of Technology Roorkee India
Application of agent based modelling for service quality assessment of airport terminal building
Dr. E. Rajasekar, Aromal Thampan, Kapil SinhaIndian Institute of Technology Roorkee, India
Speaker : Authors :
INDIAN INSTITUTE OF TECHNOLOGY ROORKEE
1
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 2
INTRODUCTION
QUANTITY FACTOR
LOS A LOS B
40% 65% 95% Max. Occupancy
LOS C LOS D LOS E LOS F
Flows Delays Comfort
• Temporal Factors (Processing Time)• Spatial Factors (Distances/Density)
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 3
OBJECTIVE
• Evaluate the dynamics of passenger occupancy at Check-in zone of terminal building for different level of services
• Estimate and compare the passenger density profiles and waiting time through ABM
Service Time
No. of Services
Passenger Density
Passenger Waiting Time
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 4
DETAILS OF THE STUDY
Chennai Domestic Terminal, India | Large Sized Airport
ENTRANCE ZONE
CHECK-IN ZONE
SECURITY ZONE
CONCESSION ZONE
WAITING ZONE
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 5
Flight Agent
PASSENGER SEQUENCEDEPARTURE PROCESS
Check-in Counter SecurityHoldrooms
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 6
PASSENGER SEQUENCEARRIVAL PROCESS
Flight Agent Arrival Concourse Baggage Claim
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 7
DENSITY MAPCHENNAI DOMESTIC TERMINAL
Departure Floor Level Arrival Floor Level
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 8
Check-in area
Security wait
Security check
Check-in zones
Check-in wait
CHECK-IN AREACHENNAI DOMESTIC TERMINAL
Application of agent based modelling for thermal comfort and energy efficiency studies in transport terminal buildings.Kapil Sinha 9
MODEL SUMMARY
Dwell Time
Check-In Counter
32282420161284
7
6
5
4
3
2
1
0
Service TimePassenger Arrival Rate
Walking Time
Concourse
21181512963
600
500
400
300
200
100
0
Dwell Time
Check-In Counter
32282420161284
7
6
5
4
3
2
1
0
Dwell Time
Check-In Counter
32282420161284
7
6
5
4
3
2
1
0
Service Time
Service Time
Counter 1
Counter 2
Counter 3
CHECK-IN AREA
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 10
0
2
4
6
8
10
12
14
16
9:00 9:15 9:30 9:45 10:00 10:15 10:30 10:45 11:00
Num
ber o
f pas
seng
er
Time29-Sep 30-Sep
MODEL DESCRIPTIONAGENT MODELLING
Walking Speed (metre/seconds)µ=0.7, σ=0.37
Decision variablesGenderFlight numberClassStorage variables
Waiting TimeWalking Time
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 11
Service points Probability distribution Distribution parameters (units in seconds)
Entry gate Normal Mean = 14.50, Stnd = 5.715
Check-in entry Gamma Shape = 5.937, Scale = 1.768
Self check-in Weibull Shape = 2.393, Scale = 39.25
Assisted self check-in Loglogistic Location = 3.229, Scale = 0.1422
Baggage screening Weibull Shape = 1.075, Scale = 59.86
Baggage after screening Lognormal Location = 4.121, Scale = 0.38
Check-in counter Logistic Location = 79.12, Scale = 18.87
Security b4 screening Weibull Shape = 1.596, Scale = 129.2
Security screening Normal Mean = 35.64, Stnd = 56.371
Security after screening Normal Mean = 30.55, Stnd = 17.17
Boarding process Loglogistic Location = 0.9783, Scale = 0.1670
Baggage belt Weibull Shape = 1.284, Scale = 498.3
Entry Queueing Normal Mean = 46.02, Stnd = 15.82
Check-in Queueing Weibull Shape = 0.7315, Scale = 1148
Security Queueing Weibull Shape = 2.225, Scale = 66.33
Boarding Queueing Weibull Shape = 1.332, Scale = 250.4
MODEL DESCRIPTIONSERVICE POINTS (FIELD STUDY DATA)
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 12
MODEL DESCRIPTIONDECISION MODEL FOR CHOOSING CHECK-IN COUNTER
Using Conditional Output
Using PedSelectOutput For Decision Modelling
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 13
MODEL DESCRIPTIONCheck-in Counter modelled as PedService
SPATIAL MODEL STOCHASTIC MODEL
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 14
• Process time : Weibull(1.49, 2.22, 1.02) in minutes
• No. of counters : 26
• Process time : Weibull(1.8, 3.0, 2.02) in minutes
• No. of counters : 26
• Process time : Weibull(1.8, 3.0, 2.02) in minutes
• No. of counters : 18
LEVEL OF SERVICES SCENARIOSCHENNAI DOMESTIC TERMINAL
LOS E
LOS C
LOS A
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 15
LEVEL OF SERVICE ECHENNAI DOMESTIC TERMINAL
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 16
LEVEL OF SERVICE CCHENNAI DOMESTIC TERMINAL
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 17
LEVEL OF SERVICE ACHENNAI DOMESTIC TERMINAL
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 18
LEVEL OF SERVICE ETYPICAL WEEKDAY DENSITY PROFILE
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 19
LEVEL OF SERVICE CTYPICAL WEEKDAY DENSITY PROFILE
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 20
LEVEL OF SERVICE ATYPICAL WEEKDAY DENSITY PROFILE
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 21
CROWDING COMPARISONTYPICAL WEEKDAY DENSITY PROFILE
LOS CLOS E
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 22
CROWDING COMPARISONTYPICAL WEEKDAY DENSITY PROFILE
LOS C LOS A
Application of agent based modelling for service quality assessment of airport terminal buildingNusrat Ali 23
Cases Mean St. Dev
LOS A 8.732 5.402
LOS C 22.81 15.123
LOS E 50.466 29.213
LOS ELOS CLOS A
100
80
60
40
20
0
Wai
ting
Tim
e (m
in.)
WAITING TIME AT CHECK-IN ZONETYPICAL WEEKDAY DENSITY PROFILE
WAITING TIME (in minutes)
Nusrat AliIndian Institute of Technology Roorkee India
Application of agent based modelling for service quality assessment of airport terminal building
[email protected]+91 7500636766
Speaker : Contact :
INDIAN INSTITUTE OF TECHNOLOGY ROORKEE
24
Questions and Comments
