TheSecurityScreeningProcessOptimizationbasedon ...TheSecurityScreeningProcessOptimizationbasedon...

The Security Screening ProcessOptimization based onCellularAutomatanModel

Zi-hui Zhang1 ， Hui-nan Zhu2 ，Gang He3 Xiu-fen Wang4*

1 Basic Science Department，Tianjin Agricultural UniversityTianjin 300384 China

2 Humanities Department，Tianjin Agricultural University

Tianjin, 300384 , China

3 Humanities Department，Tianjin Agricultural University

Tianjin, 300384 , China

4 Department of Computer Science and Information Engineering ,Tianjin Agricultural University, Tianjin, 300384 , China

*Corresponding author

AbstractAs the passenger throughput of airport is increasing,

the security check of airport is confronting great

pressure. In order to improve the efficiency of security

check, this paper is to simulate the queuing process of

security check through constructing cellular

automaton model in order to get the indexes that

influence security screening process. Here, we use

cellular automaton to simulate the security screening

process of different throughput. We can qualitatively

determine the bottleneck of the whole process. As to

the bottleneck, we can randomly shunt passengers

who are going to enter the bottleneck to reduce

congestion. Otherwise, different cultural backgrounds

generate different social norms which show the time

differences in security check. Therefore, we can

divide passengers into 3 types and they would be

shunted to 3 proprietary lanes. Later, after considering

passenger composition type, the efficiency of airport

staff, airlines’ costs and so on, we give some proposals

on how to optimize security screening process.

Key Words: passenger throughput, security

screening process, cellular automaton model,passenger shunt

1. Introduction

After the September 11 attacks, the airportsecurity checkpoints around the world are facingunprecedented pressure and challenges. It is stilla difficult problem to balance relation betweenthe requirements of passengers and the interestsof airlines, even if the airport security conditionhas been significantly improved throughout theworld.

According to the latest prediction data, thepassenger throughput of Chinese airport willmaintain an average annual growth rate ofaround 11.4%. Furthermore, there will need 13airports which annual passenger throughputexceeds 30 million, but now there are only 3.And there will need 6 airports which annualpassenger throughput around 20 million to 30million, but now there are only 2. Similarly,there will need 10 airports which annualpassenger throughput around 10 million to 20million, but now there are only 5[2]. From theabove data, we derive that the passenger

IJCSI International Journal of Computer Science Issues, Volume 14, Issue 3, May 2017 ISSN (Print): 1694-0814 | ISSN (Online): 1694-0784 www.IJCSI.org https://doi.org/10.20943/01201703.7077 70

2017 International Journal of Computer Science Issues

throughput will be more and more enormous.However, security checkpoint as an importantpart of affecting airport operation efficiency, ifwe can provide reliable solutions to reducewaiting time in this part, it will not only improveeconomic returns and security checkmanagement for airlines, but also decrease theflight delays and Improve passenger satisfaction.Therefore, it has very important practical

significance and application value to establish anoptimum screening process which is suitable formost of airports around the world.

2. Research Approaches

To begin with, we analyze the securityscreening process and derive the results asshown in the following figure.

Figure 1: The change of passenger speed in single lane1. We select passenger flow, density and speed in

each zone as the data base to establish the passengerthroughput simulation model via cellular automaton.Then explore the bottlenecks from these four zones.

2. With MATLAB software, we simulate thepassenger screening processes in different passengerthroughput. It can clearly show the congestions in eachzone and the relations between passenger flow, densityand speed. Then we can identify the bottlenecks.

3. After identifying the bottlenecks, we shuntpassengers in corresponding zone to ease congestion foroptimum process.

4. On the basis of shunt, we continue simulate thequeuing process in Zone A and B via cellular automatonand get the variation diagrams of passenger flow, densityand speed in these two zones.

5. We divide the passengers into three typesaccording to the difference of screening time whichcaused by different cultural norms. Via cellularautomaton model, we get passenger flow variationdiagram which is based on the increased throughput ofZone A, B, C.

6. On the basis of above research results, afterconsidering passenger type, airport officer efficiency andairlines’ costs, we provide some proposals about securityscreening procedures and management policies.

3. Research Assumptions

We make the following assumptions about thesolveing problem.

1. The screening speed of each security office isconsistent.

2. All security checkpoint equipment always canmaintain normal works.

2. Ignore the influences to screening time caused byindividual differences of age, gender and height.

4. No passengers jump in the queue.5. There is no emergency for subjective reasons.6. Passengers’ documents are valid. Do not consider

the situation of congestion caused by invalid documents.



4. Model building

Considering the passengers in time and space bothare discrete elements, passengers in security screeningprocess have a finite number of state changes. The spaceand time range also are local factors. All these conditionsare in accordance with the cellular automaton’s discretecharacter both in time and space. Therefore, we choosecellular automaton model to simulate the state ofpassengers in security screening process.

4.1Model building and solution of question one

In order to identify potential bottlenecks, wesimulate the process of passenger security screening viacellular automaton model and select suitable indexes tomeasure the efficiency of each procedure. Then wegradually increase the passenger throughput to observethe variation of passenger flow, density and speed as theincrease of passengers in each zone. From this, we canfind out the deficiencies in security screening processand analyze the internal cause for the followingimprovement.

4.1.1 Model building

Via cellular automaton, we can simulate thepassenger moving state. Thereby we define eachpassenger as a cellular length and determine theemergence time of passenger via Poisson distribution.Meanwhile, we determine several critical factors such asthe queuing rules, the security screening time, screeningrules and lanes in each zone. Specific rules are asfollows:1. The definition of passengerStep1: the determination of seat array

，

，

stands for the abscissa where passenger is instands for the ordinate where passenger is

xy in

A cellular represent a passenger.Step2: the probability of passenger's emergence time

, 1,2,...!

n

nP e nn

Step3: the definition of different passengers' probability

，

，

d

v

stands for the probability of suspicious passengersstands for probability probability of pre passengerP s

P

From the problem description, we get 45%tP

2. The definition of security screeningStep1: define the passenger screening position

,,

n

n

x stands for the position where passenger is iny stands for the lane where passenger is in

Step2: determine the queuing discipline

1,min( )n n nZ x x

3. The determination of queuingStep1: in order to prevent collision

max maxmin(0, , 0)v v v

Step2: the update of position in moving

1t tx x v t

Where tx stands for the position of passenger at

time t , v stands for the passengers moving speed.Step3: define the screening time

,,,

a

b

c

T stands for the screening time in Zone AT stands for the screening time in Zone BT stands for the screening time in Zone C

4.1.2 Model solution

According to the above rules used to simulatepassenger security screening process, we simulate thescreening process for several times via cellularautomaton model in MATLAB software as shown inFigure 2. In situations of different passenger throughput,we calculate the passenger flow, density and speed ineach zone. Finally, we identify potential bottlenecks thatdisrupt passenger throughput through comparing thecalculating results of the three indexes in each zone.



Figure 2: Illustration of four security screening lanesThrough the simulation in MATLAB software, we

get the three variation diagrams of Zone A, B, C which isbased on the change of passenger flow, density andspeed in situations of different throughput. Because thereis no congestion in pre-check lane shown via cellularautomata simulation, we don’t display the correspondingillustration in here.

Figure 3: The change of passenger flow in single laneAs can be seen from Figure 3, as the increase of

throughput, the passenger flow in Zone A, B, C both

increase first and the remain constant. Whereas,passenger flow of Zone A changes after Zone B, butpassenger flow in Zone B and C change almostsynchronously.

Figure 4: The change of passenger density in single laneAs we can see in Figure 4, with the increase of

throughput, the passenger density in Zone A, B, C bothchange steady first and then increase, at last keep stablechange again. The density in Zone B reaches thesaturation point before the saturation point appears inZone A.

Figure 5: The change of passenger speed in single laneAs we can see in Figure 5, with the increase of

throughput, the passenger speed in Zone C almostremains constant. The speed in Zone A and B both keep



stable first, and then decrease. Moreover, the speed inZone B decreases earlier than Zone A.

According to all above analysis, it shows that thepassenger flow, density and speed in Zone B affect thechange of these indexes in Zone A. The three indexes inZone A and C are both higher than in Zone C, also ZoneB is located after Zone A and before Zone C. Thus, ZoneB is the important factor of limiting the efficiency inZone A, and Zone B is the bottleneck of the wholesecurity screening process.

4.1.3 Model Test

According to the data gived in this problemdescription, we can derive the screening time in eachzone. Although these data are less, we still can calculatethe number of passenger in each zone in a certain timerange. Later, we compare this calculation results with thesimulatin results of our .

Table 1：Passenger flow contrast table

Realpassengertraffic

Simulationof passenger

traffic

Errorvalue

Zone A 538 516 4.00Zone B 428 406 5.14Zone C 418 400 4.31Zone D 70 68 2.86

As we can see in Table 1, in each security screeningzone, the error value between actual passenger flow andthe simulated passenger flow derived from cellularautomaton model is less 6%. Therefore, the simulationvia cellular automaton model is reliable and the model isbasically accurate.

4.2 Model building and solution of question two


Through the analysis of the first question, weidentify that the bottleneck of the whole securityscreening process is in Zone B. It already appearscongestion in Zone B when the passenger throughput isnot big, so the key to reduce waiting time is to improvethe passenger flow volume in Zone B. Hence we opentwo or more lanes to connect Zone A and Zone B, inorder to optimize the security screening process.

Step1: define the diffluence after Zone A

1

2

,,

b stands for the first shunt lane from Zone B to Zone Cb stands for the second shunt lane from Zone B to Zone C

Step2: The position after passing Zone A

1 1 ,max ,n a n a nx y z y z

Resume that the passenger position, emergencetime and moving speed are the same as in first question.Other conditions and rules equal, for Pre-Check lane, itis still a single lane and no shunt lane after Zone A.

4.2.2 Model solution

According to the above rules used to simulatepassenger security screening process and the new rule ofshunt in Zone B, we simulate the screening process forseveral times via cellular automaton model in MATLABsoftware as shown in Figure 6. In situations of differentpassenger throughput, we calculate the passenger flow,density and speed in each zone. At last, we compare thecalculating results of the three indexes in each zone withthe calculating results in first question, to see if there isanimprovement.

Figure 6: Illustration of security screening shunt lanesAs we can see in Figure 7, under the pattern of



shunt, as the increase of throughput, the passenger flowin Zone A and B both increase and the tendency ofchange are almost synchronous. Therefore, it is effectiveto randomly shunt passengers in two lanes after Zone Afor the improvement of security screening efficiency.Also, this pattern helps us to solve the bottleneck ofscreening process.

Figure 7: The variation diagram of each index in shuntsituation

4.3 Model building and solution of question three


It is well known that different parts of the worldhave their own cultural norms that shape the local rulesof social interaction. From the examples mentioned intask description, we know that it makes difference toscreening time under the influence of regionaldifferences. Therefore, we make simple classification onpassenger according to the different screening time. Andwe refine the cellular automaton simulation model on thebasis of the model in first question. As passengerthroughput gradually increase, we observe the change ofpassenger flow, density and speed in each zone andcompare with the observed results in second question, tosee if there is an optimization.Step1: define the passenger classification

1,2,3,

w

for the passenger who needs to be screened for long timefor the passenger who needs to be screened for medium timefor the passenger who needs to be screened for little ti e

Rm

According to the shunt of screening time, we divide all

passengers into three types and the emergenceprobability of each type is random. Every passenger canbe the one of these three types.Step2:define the emergence probability of different typepassengers

1

2

3

3

1 2

, 1, 2,

13

P stands for emergence probability of typeP stands for emergence probability of typeP stands for emergence probabil

Pity of ty

Ppe

P

Passengers are divided into three types according todifferent screening times, there are fast passengersmarked type 1, medium speed passengers marked type 2and slow passengers marked type3. After doing research,we know that their proportion is 2 :1: 2 , hence wemake the flow chart of shunt and classification insecurity screening as shown in Figure 8. It sets specificshunt lanes for corresponding classification ofpassengers to improve the efficiency of whole securityscreening process and increase the passenger throughputin airports.

Figure 8: The flow chart of shunt and classification insecurity screening

4.3 2 Model solution

According to the above rules used to simulatepassenger security screening process and the new rule ofspecific shunt, we simulate the screening process forseveral times via cellular automaton model in MATLABsoftware as shown in Figure 8. In situations of differentpassenger throughput, we calculate the passenger flow,density and speed in each zone.



Figure 9: The variation of indexes in situation of shunt and classificationAs we can see in Figure 9, as the increase of

throughput, the passenger flow, density and speed areboth bigger than those in the situation of only shunt andno classification. After shunting and then classify thepassenger, it not only can eliminate the influence onsecurity check caused by different social norms, but alsocan increase the passenger flow of the whole screeningprocess to improve passenger throughput of the airports.It has a good effect on the development of the airport inthe future.

5. Policies and Recommendations

According to the above results and the cellularautomaton simulations in MATLAB, we can see that thebottleneck of the whole screening process is in Zone B.Although the Pre-Check program can alleviate thisproblem, it still cannot completely solve the bottleneckin Zone B. For the task b and task c, we choose thediffluence approach and the approach of passengerclassification after diffluence, moreover, it can improvethe screening efficiency of the whole security screeningprocess through adopting these approaches. On the basisof the above research, we try to consider all aspects andmake the following proposals for the security managers.

1. Continue the implementation of Pre--Checkprogram and increase its publicity. It can reduce thewaiting time in Zone B to enhance the overall efficiency.

2. Investigate the current passenger throughput in

airport and predict the future passenger throughput forbetter modifications.

3. Learn about the efficiency problem of airportsecurity officers and try to facilitate communicationamong them.

4. Research the screening time of differentpassengers and make suitable classification for thediffluence security screening lanes.

5. Properly increase staffing and update screeningmachines when costs permit.

6. Formulate reasonable policies like the child whois under 12 can become Pre-Check passenger for free.

The above proposals have been already combinedwith our research results. At last, we sincerely hope theseproposals can help the optimization of airport securitycheckpoint.

6. Conclution

Airport is a bridge connecting the land traffic withthe air traffic, and the airport security checkpoint is animportant factor to its development. Especially forhighly congested airports, the increasingly seriouscongestion and increasing flight delays cause the greatloss to both passengers and airlines. Therefore, itrequires airlines to continuously improve the securityscreening process and establish a safe, efficient andconvenient checkpoint.

The airport security screening model simulated by



cellular automaton has high flexibility and universality.It can precisely simulate the each part of securityscreening process and make a comprehensive evaluationfor the screening procedures in the absence of data.Eventually, we find out the bottleneck in securityscreening process through it. This model can clearlyreveal the variation of passenger moving state. It is easyto set different parameters for the requirements ofdifferent airport situations, We do not use this model toconsider more details due to the limited time. It candivide the passengers’ security screening times into moretime segments for better diffluence in future. Thesituation of some passengers queue together as a groupcan be considered in this model, such as the touristgroups and family members. And it will break thePoisson distribution. It can set more constraintconditions in specific airport, such as airport officers,screening costs, different throughput and so on.

Acknowledgements： Innovative training programfor college students in Tianjin. Tianjin AgriculturalUniversity（201710061110）

References[1]Lei Ju. Design and Implementation of AirportSecurity Information System [D].TianJinUniversity.2013.5.(1).[2]Lu Xun. Research on the Planning and Simulation ofPassenger and Luggage Process at Airport Landside [D].Nanjing University of Aeronautics andAstronautics.2008.6.(1).[3]Liu Quan-ping. Study on Virtual Crowd Behaviorsbased on Multi-agent and Cellular Automat Model [D].National University of DefenseTechnology.2013.11.(11)-(13).[4]JI YunLI Hou-peng，FU Xin-yu. Analysis of AirportPassenger Flow Quantity Based on Compound PoissonProcess [J]. Chongqing Technol Business Univ. ( Nat SciEd), Vol.30 NO.5[5]JIAO Peng-peng. Forecasting Method and ItsMechanism of Impacts on A irport PassengerThroughput [J]. Journal ofTransportation System sEngineering and Information Technology,2005.5: Vol.5No.1



Date post:	30-May-2020
Category:	Documents
Upload:	others
View:	3 times
Download:	0 times

TheSecurityScreeningProcessOptimizationbasedon ...TheSecurityScreeningProcessOptimizationbasedon...

Documents