sustainability

Article Fire Evacuation in Metro Stations: Modeling Research on the Effects of Two Key Parameters

Chen Wang * and Yanchao Song Intelligent Transportation Research Center, Southeast University, Nanjing 210096, China; [email protected] * Correspondence: [email protected]

 Received: 13 December 2019; Accepted: 15 January 2020; Published: 17 January 2020 

Abstract: Metro lines have undergone a rapid development in China and a large number of metro stations have also been built. The passenger traffic volume has reached or exceeded the designed capacity in some big cities such as Beijing and Shanghai. The safety evacuation problem within metro stations under emergency has become a worldwide concern. In this study, BuildingEXODUS was employed as the simulation platform and a in Shanghai was selected for model development. Based on field survey data, the evacuation process in different fire cases was simulated, so as to evaluate the effects of two parameters (i.e., and automatic checkers) on evacuation performance. The research found that the use of two stopped escalators (normal metro stations have two) as fixed evacuation passages is effective and essential for safety evacuation. However, it surprisingly decreases the evacuation efficiency if using only one stopped as the fixed evacuating passage. The evacuation efficiency can be improved by opening the automatic ticket checkers compared with maintaining normal status. Removing the automatic ticket checkers does not pose any difference in improving evacuation efficiency.

Keywords: fire evacuation; metro station; escalators; automatic ticket checkers; evacuation efficiency

1. Introduction With the rapid development of urbanization, large-scale metro lines have been constructed in many cities of China. By 2020, the total metro mileage will reach over 8500 km in China [1]. However, metro passenger flow has also been rapidly increasing in many large cities such as Beijing and Shanghai, where passenger demand can even reach 130% of the original capacity [2]. Since a large number of people could potentially gather around metro stations, trampling and casualties would occur when emergencies happen. Many incidents [3,4] that occurred in metro stations have caused serious casualties and property losses. Thus, safe metro evacuation should be considered an important research topic. Studies related to metro evacuation mainly focused on identifying the factors affecting evacuation, and developing the simulation modeling methods of evacuation [2]. The factors affecting evacuation include occupant factors (e.g., walking speed, occupant density, exit selecting, etc.), parameters (e.g., exit width, stair/lift width, etc.), and environmental factors (e.g., fire and smoke etc.). Jiang et al. [5] studied passenger flow characteristics such as maximum walking speed and the width of staircase utilized per person at staircase in metro stations. Lei et al. [6] studied the influence rules of occupant density and exit width on evacuation efficiency. He et al. [7] conducted an investigation on evacuation behaviors of occupants in metro stations. Zia et al. [8,9] examined three factors that could affect metro evacuation efficiency: potential map, evacuees’ familiarity of the exits, and exits usage. Due to safety concerns and the complexity of logistics, the studies of in metro stations are difficult to be conducted at fields. Thus, the simulation modeling methods are often developed and used by researchers [10,11]. As for metro simulation, many models [12] have been used for evacuation modeling, such as BuildingEXODUS [13], Pathfinder 2011 [14], STEPS [15], etc.

Sustainability 2020, 12, 684; doi:10.3390/su12020684 www.mdpi.com/journal/sustainability Sustainability 2020, 12, 684 2 of 11

Some simulation models are proposed or improved by scholars to simulate the evacuation process. They focused on various aspects about evacuation, such as behavioral rules of evacuees including path choice [16], dynamic characteristics of exits during evacuation [17], as well as the efficiency of simulation [18]. As mentioned above, metro emergency evacuation could be affected by a number of factors. In large cities, such as Shanghai, metro stations are normally very large so that building factors could play important effects on evacuation. Thus, in this study, two parameters (i.e., escalators and automatic ticket checkers) were examined in order to evaluate the capacity of metro stations and improve fire evacuation efficiency. The findings are expected to provide valuable information for metro managers for emergency evacuation.

2. Method Simulation modeling methods are often used in the performance-based evacuation design [10,11] due to safety concerns and the complexity of logistics of conducting field research. BuildingEXODUS was employed in this study to evaluate the evacuation performance in a metro station. BuildingEXODUS is a fine network model which can simulate both emergency evacuation and normal circumstance in complex structures. Two-dimensional grid of nodes constructs the simulated environment typically composed by floors, stairways, exits, and occupants determined by an individual set of heuristics of rules [19]. The model provides four operation sub-models to simulate evacuation process: geometry, occupant, scenario, and simulation sub-models. Every sub-model will be used in order to simulate one evacuation situation. It should be noted that the reliability of evaluation results partly depends on the accuracy of model input, such as geometric parameters and behavioral data. Under this condition, the model input in this study has been carefully calibrated and validated based on actual field data. Thus, it is believed that the findings in this study are reliable and provide valuable information for safety design, as well as emergency management of a metro station.

3. Model Case Study is one of the most advanced metro systems in China. By 2014, 548 kilometers of metro lines and 337 stations were constructed and the daily average number of passengers transported by metros is 5 million [20]. The real volume of passenger transport at some metro stations in Shanghai is higher than the rated capacity and the evacuation passage may not satisfy the requirement of emergency evacuation. Thus, it is important to evaluate the evacuation capacity of metro stations and study the effects of key parameters on evacuation performance of metro stations.

3.1. The Metro Station The metro station considered in this study is an of and line 10 located in Shanghai, China. It is a typical station with two floors underground. The first floor is the platform layer composed of one island platform and two lanes on either side of it (see Figure1a). The train of each line is composed of 8 cars and each car has five doors. The second floor is the hall level where passengers leave the station or transfer metro line. There are four groups of automatic ticket checkers on the hall level (see Figure1b) and the width of each ticket checker is 0.5 m. The first floor and the second are connected by two in the middle of the platform and two escalators as well as two stairs on both sides of the platform. The sizes of the stairs are all 2.5 m 16 m and the sizes of the two × escalators are all 1 m 12 m. The probable escape direction is represented in Figure1. × SustainabilitySustainability2020 2020, 12, 12, 684, x FOR PEER REVIEW 33 ofof 11 12

(a) Sketch layout of platform layer.

(b) Sketch layout of hall level.

FigureFigure 1. 1.Sketch Sketch of of the the metro metro station. station.

3.2.3.2. Model Model Input Input Calibration Calibration BeforeBefore applying applying simulation, simulation, a a set set of of simulation simulation parameters parameters is is required. required. InIn thisthis study,study, field field data data werewere collected collected to to calibrate calibrate those those simulation simulation parameters. parameters. The The underlying underlying assumption assumption is is that that those those are are ableable to to considerably considerably reflect reflect human human behaviors behaviors under under emergency emergency in in metro metro stations. stations. TheThe total total number number of of evacuated evacuated occupants occupants isis an an important important input input parameter, parameter, which which should should be be carefullycarefully calibrated. calibrated. InIn orderorder toto testtest the the evacuation evacuation capacity capacity of of the the station, station, the the maximum maximum gathered gathered passengerpassenger should should be be taken taken as as the the total total number number of of evacuated evacuated occupants. occupants. The The passenger passenger flow flow of of South South ShanxiShanxi Road Road stationstation waswas recordedrecorded in October 2014 (31 (31 days) days) at at one-hour one-hour intervals intervals and and processed processed as asaverage average hourly hourly flow flow (shown (shown in in Figure Figure 22).). As FigureFigure 22 shows, shows, the the passenger passenger flow flow in in one one day day is is unbalancedunbalanced and and significantly significantly divided divided into into morning morning peak, peak, flat flat peak, peak, and and evening evening peak. peak. The The maximum maximum gathergather passenger passenger number number is is 6718 6718 which which appears appears between between 18:00~19:00. 18:00~19:00. AccordingAccording toto the the passenger passenger flowflow statistics, statistics, the the maximum maximum section section of of passenger passenger flow flow is is 39,456 39,456 persons persons/hour./hour. The The train train in in Shanghai Shanghai metrometro line line 1 1 is is equipped equipped with with 8 8 . vehicles. Eighteen Eighteen pairs pairs of of trains trains arrive arrive at at this this station station at at evening evening peak peak hour.hour. Based Based on on the the above above analysis, analysis, the the maximum maximum gathered gathered passenger passenger in in the the station station can can be be figure figure out out asas follows: follows: (a)(a) The The maximum maximum passenger passenger capacity capacity of one of trainone train at evening at evening peak hour: peak 39,456 hour:/ (1839,456/(182) = 1096 × 2) persons. = 1096 × (b) Thepersons. maximum gathered passenger on the platform can be calculated as follows: 6718/(18 2) = × 373 persons. (b) The maximum gathered passenger on the platform can be calculated as follows: 6718/(18 × 2) = (c) The373 numberpersons. of working staffs in South Shanxi Road is 5 persons. (c) Gender The number and age of areworking two important staffs in South simulation Shanxi parameters, Road is 5 persons. which classify occupants into several groups with different walking speed, responsiveness, and flexibility. The two parameters were determined based on field survey data and literature data: Males: 10–18: 7%, 19–29: 11%, 30–50: 33%, 51–80: 3%; Females: 10–18: 5%, 19–29: 13%, 30–50: 25%, 51–80: 3%. According to previous studies, walking speed can be influenced by visibility in the case of fire. When occupants are walking in the condition of heavy handicapped visibility, the fast walking speed of occupants on the floor had a range of 0.22–1.08 m/s, and the walking speed at the stairs was 0.53 m/s [21]. The above walking speeds were employed in this study due to the worst case should be considered when analyzing evacuation capacity in metro stations. Note that, the fastest walking speed on the floor (i.e., 1.08 m/s) employed in this study is lower than the previous research (e.g., 1.20 m/s in [22]) probably due to the worse visibility. SustainabilitySustainability2020 ,202012, 684, 12, x FOR PEER REVIEW 4 of 124 of 11

8000 Number of occupants on the train Number of occupants getting off the train 7000 Total number of occupants 6000

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1000 TIME INTERVAL 0 05:00~6:00 06:00~7:00 07:00~8:00 08:00~9:00 09:00~10:00 10:00~11:00 11:00~12:00 12:00~13:00 13:00~14:00 14:00~15:00 15:00~16:00 16:00~17:00 17:00~18:00 18:00~19:00 19:00~20:00 20:00~21:00 21:00~22:00 22:00~23:00 23:00~24:00

Figure 2. Passenger flow statistics at South Shanxi Road station. Figure 2. Passenger flow statistics at South Shanxi Road station. 3.3. Experiment Settings In orderGender to analyze and age theare evacuationtwo important capability simulation of thepara platformmeters, which as well classify as the occupants effect of keyinto componentsseveral (i.e., elevatorgroups with and automaticdifferent walking ticket checkers)speed, responsive on evacuationness, and effi flexibility.ciency, we The considered two parameters three di ffwereerent fire determined based on field survey data and literature data: Males: 10–18: 7%, 19–29: 11%, 30–50: 33%, cases and multiple evacuation strategies (as shown in Figure3). For fire cases: 51–80: 3%; Females: 10–18: 5%, 19–29: 13%, 30–50: 25%, 51–80: 3%. According to previous studies, Casewalking 1: Firespeed has can occurred be influenced on the by platform.visibility in the case of fire. When occupants are walking in the Whencondition a fire of heavy has occurred handicapped on the visibility, platform, the trains fast walking should speed be arranged of occupants to pass on throughthe floor thehad stationa withoutrange a stop.of 0.22–1.08 Occupants m/s, onand the the platform walking speed must beat evacuatedthe stairs was to the0.53concourse. m/s.[21] The In above this case, walking the total numberspeeds of evacueeswere employed is 378 persons.in this study due to the worst case should be considered when analyzing Caseevacuation 2: Fire capacity has occurred in metro instations. a train Note which that, arrives the fastest at thewalking station. speed on the floor (i.e., 1.08 m/s) Whenemployed a fire in this occurs study in is a lower train, than if a trainthe previous on the re othersearch line (e.g., is 1.20 also m/s pulling in [22]) into probably the station, due to the staff shouldworse inform visibility. the driver to stop or pass through the station. Thus, the occupants in the burning train and on the platform must evacuate to the concourse. In this case, the total number of evacuees should 3.3. Experiment Settings be: 1096 + 373 + 5 = 1474 (persons). CaseIn 3: order Fire hasto analyze occurred the in evacuation a train when capability two trains of the are platform in the station.as well as the effect of key components (i.e., and automatic ticket checkers) on evacuation efficiency, we considered When a fire occurs in a train and another train is also arriving at the station, all occupants in the three different fire cases and multiple evacuation strategies (as shown in Figure 3). For fire cases: two trains and on the platform must be evacuated to the concourse. In this case, the total number of Case 1: Fire has occurred on the platform. evacuees should be: 1096 2 + 373 + 5 = 2570 persons. When a fire has occurred× on the platform, trains should be arranged to pass through the station Aboutwithout evacuation a stop. Occupants strategies, on the stairs platform and must escalators be evacuated were considered to the concourse. as evacuation In this case, passages the total from trainsnumber or platform of evacuees to the is concourse.378 persons. In order to analyze the effect of and automatic ticket checkers onCase the 2: evacuationFire has occurred efficiency, in a train six evacuation which arrives strategies at the station. with a combined use of elevators, stairs, and ticketWhen checkers a fire were occurs simulated. in a train, if The a train details on the are othe shownr line in is Tablealso pulling1. into the station, the staff Threeshould basic inform evacuation the driver strategies to stop or (i.e.,pass S1,through S2, and the S3) station. were Thus, simulate the occu to evaluatepants in thethe effectsburning of train different use ofand escalators on the platform on evacuation must evacuate efficiency, to the under concourse. three fire In this cases case, (see the Table total1 number). For those of evacuees strategies, should to avoid be: 1096 + 373 + 5 = 1474 (persons). circuit short and electric fire, all escalators were assumed to stop running. For strategy 1 (i.e., S1), no Case 3: Fire has occurred in a train when two trains are in the station. escalator was used as a fixed evacuation passage, and occupants were only allowed to escape through When a fire occurs in a train and another train is also arriving at the station, all occupants in the stairs.two For trains strategy and on 2 (i.e., the platform S2), one must escalator be evacuated and all stairs to the were concourse. used asIn fixedthis case, evacuation the total passagesnumber of while the otherevacuees escalator should is outbe: 1096 of use. × 2 This+ 373 strategy+ 5 = 2570 can persons. be considered as an “unbalanced” evacuation strategy. For strategy 3 (i.e., S3), two escalators and all the stairs were used as fixed evacuation passages. Both S1 and S3 can be geographically considered as “balanced evacuation”. Note that the total evacuation time was calculated as the time that all occupants move from their initial locations to the end of escalators or stairs in concourse. Sustainability 2020, 12, 684 5 of 11 Sustainability 2020, 12, x FOR PEER REVIEW 5 of 12

Fire location Train fire Platform fire

Evacuees Occupants in one train Occupants in two train and on the platform and on the platform

Evacuation routes One escalator Two escalators stairs and stairs and stairs

State of automatic Automatic ticket Automatic ticket No ticket checkers are checkers are automatic ticket checkers nomal open checkers

FigureFigure 3. Di3. ffDifferenterent cases cases of of fire fire andand corresponding evacuation evacuation situations. situations.

About evacuation Tablestrategies, 1. Summary stairs and of escalators evacuation were settings considered in thisstudy. as evacuation passages from trains or platform to the concourse. In order to analyze theService effect Condition of elevators of and automatic ticket Occupants Service Condition Strategycheckers on Fire the Case evacuation efficiency, six evacuation strategiesAutomatic with Ticket a combined Evaluationuse of elevators, Goal (Person) of Escalators stairs, and ticket checkers were simulated. The details are shownCheckers in Table 1. Three basicCase 1evacuation 378 strategiesNone (i.e., escalatorS1, S2, isand S3) were simulate to evaluate the effects of _ differentS1 useCase of 2escalators 1474on evacuationused efficien as fixedcy, under three fire cases (see Table 1). For those Case 3 2570 evacuation passage Test the effects of service strategies, to avoid circuit short and electric fire, all escalators were assumed conditionto stop running. of escalators For on Case 1 378 One escalator is used strategy 1 (i.e., S1), no escalator was used as a fixed evacuation passage, and occupantsevacuation were efficiency only S2 Case 2 1474 as fixed evacuation _ under different fire allowed to escapeCase 3 through 2570 stairs. For strategypassage 2 (i.e., S2), one escalator and all stairs were used as conditions. fixed evacuationCase 1passages 378while the otherTwo escalators escalator are is out of use. This strategy can be considered as anS3 “unbalanced”Case 2 evacuation 1474 strategy. Forused strategy as fixed 3 (i.e., S3), two_ escalators and all the stairs were used as fixedCase evacuation 3 passages. 2570 Bothevacuation S1 and passages S 3 can be geographically considered as “balanced evacuation”.Case Note 1 that the 378total evacuation time was calculated as the time that all occupants move S4 Case 2 1474 Normal from their initial locations to the end of escalators or stairs in concourse. Test the effects of service Case 3 2570 Strategy 4–6 were considered forTwo examining escalators arethe effects of different usage conditionof automatic of automatic ticket Case 1 378 checkers on evacuation efficiency underused three as fixed fire cases. In S4, the service conditionticket of checkers automatic on S5 Case 2 1474 Open evacuation passages evacuation efficiency ticket checkersCase was 3 set to 2570 be normal. In S5, all automatic ticket checkers wereunder fully di ffopenerent fireand conditions. occupants couldCase 1directly pass 378 through. In S6, all automatic ticket checkers were removed. Not that forS6 S4 to S6, Casetwo 2escalators 1474 were used as fixed evacuation passages.None Case 3 2570

Strategy 4–6 were considered for examining the effects of different usage of automatic ticket checkers on evacuation efficiency under three fire cases. In S4, the service condition of automatic ticket checkers was set to be normal. In S5, all automatic ticket checkers were fully open and occupants could directly pass through. In S6, all automatic ticket checkers were removed. Not that for S4 to S6, two escalators were used as fixed evacuation passages.

3.4. Results and Discussion

3.4.1. Effects of Escalators on Evacuation Escalators and stairs were identified as the bottleneck of metro stations [23,24]. According to the Chinese metro design standards, all evacuees must evacuate to a safe place from the metro platform in Sustainability 2020, 12, 684 6 of 11 six minutes (including one minute of response time) [25]. This rule is the so called “five-minute rule”. The evacuation performance of escalators and stairs were simulated and evaluated. As mentioned above, case 1, case 2, and case 3 correspond to three basic cases of fire, respectively. When a fire occurs on the platform or in a train, all occupants on the platform should be evacuated through stairs. The elevators will turn off or be used as fixed evacuation passage. Nine scenarios were simulated to investigate the effects of different service conditions of escalators on evacuation time, and the simulation results are shown in Table2. The total evacuation time (exclude one minute of response time) refers to the time that all the occupants evacuate from their initial location to the end of escalators or stairs in concourse.

Table 2. Total evacuation time for Strategy 1 to Strategy 3 (S1 to S3).

Occupants Total Evacuation Relative Fire Case Strategy OPS (Person) Time (s) Effectiveness (%) S1 378 123 - 0.381 Case 1 S2 378 125 1.6 0.396 − S3 378 88 28.5 0.130 S1 1474 425 - 0.420 Case 2 S2 1474 428 0.71 0.525 − S3 1474 295 30.6 0.260 S1 2570 735 - 0.454 Case 3 S2 2570 756 2.9 0.558 − S3 2570 488 33.6 0.267

As shown in Table2, the total evacuation time of case 1 satisfied the “five-minute rule”, indicating all evacuation strategies fulfill the demand of safe evacuation when a platform fire happens. For fire case 2, the total evacuation time of S3 met the requirement of “five-minute rule” while the other two evacuation scenarios did not. This indicates that when a train fire happens and only one train is in the station (i.e., case 2), the use of two fixed escalators is more effective and essential for safe evacuation. Regarding case 3, no evacuation strategies ensured a safe evacuation. Nevertheless, the use of both the stopped escalators (i.e., strategy 3) significantly reduced the total evacuation time (reduce by 33.6%), compared to the other two strategies. What is more, the use of both stopped escalators is more effective when train fire happens, compared to platform fire cases (30.6% or 33.6% vs. 28.5% in Table2). Thus, it is necessary to use escalators as fixed evacuating passage when a train fire happens. Taking strategy 1 as the baseline strategy, the other two strategies (i.e., S2 and S3) are compared to S1 for relative evacuation effectiveness. It was observed that the total evacuation time of S3 is much lower than that of S1, which indicates that the use of both stopped escalators has an enhanced effect on reducing the total evacuation time (by 28.5%). This is similar for case 2 and case 3, that the use of both escalators improved the evacuation efficiency by 30.6% and 33.6%, respectively. As for S2 (i.e., using only one stopped escalator as fixed evacuating passage), the total evacuation time is a bit higher than S1 for case 2 and case 3. This implies that using one stopped escalator did not increase but decreased the evacuation efficiency, compared to no usage of escalators. This phenomenon can be further explained by analyzing the optimal productivity statistics (OPS): Pn (TET EETi) i=1 − OPS = , (1) (n 1)TET − where n is the number of used exits, EETi is the time of the last occupant evacuates from exit i, and TET is the total evacuation time and TET is equal to the maximum value of EETi. The OPS represents the balance degree of service time of all the employed exits (i.e., stair and/or escalator in this study). The range of OPS is from 0 to 1 and the lower OPS is, the more balanced service time the used exits achieve. If OPS is 0, it indicates a very balanced use of all exits which have an equal service time. While if OPS is 1.0, it represents a very unbalanced use of exits that at least one is unused. Sustainability 2020, 12, 684 7 of 11

As shown in Table2, the OPS of S2 is a bit higher than that of S1 (i.e., 0.395 vs. 0.381) for fire case 1. This shows a more unbalanced use of exits for S2, which resulted in longer evacuation time. Similar results can be found for fire case 2 (0.525 vs. 0.420) and case 3 (0.558 vs. 0.454). It can be observed from the simulation process that occupants tend to evacuate through the nearest stairs and/or escalators. AsSustainability such, the 2020 combined, 12, x FOR use PEER of stairREVIEW and escalator had a higher evacuation efficiency compared to8 only of 12 using stairs for evacuation. For S2, at the late stage of evacuation, the part of the area with only stairs inand use stairs could can be muchbe used. more This crowded unbalanced than usage the other cond areaition where could both create escalators a bottleneck and stairs and thus can bedecrease used. Thisthe unbalancedoverall evacuation usage conditionefficiency. could What create is more, a bottleneck a strong positive and thus correlation decrease thewas overall identified evacuation between effievacuationciency. What time is and more, OPS a strong (see Table positive 2). Thus, correlation the evacuation was identified efficiency between can be evacuation improved time by passenger and OPS (seeorganization Table2). Thus, as well the as evacuation safe trainings e ffi ciencyto achieve can bea mo improvedre balanced by passengeruse of all evacuation organization passages as well (i.e., as safestairs trainings and/or toescalators). achieve a more balanced use of all evacuation passages (i.e., stairs and/or escalators). FigureFigure4 shows4 shows the the comparison comparison of di offf erentdifferent evacuation evacuation strategies. strategi Whenes. When two escalators two escalators were bothwere usedboth for used fixed for evacuationfixed evacuation passages, passages, the highest the highes evacuationt evacuation efficiency efficiency was achieved was achieved for all for three all three fire cases.fire cases. Interestingly, Interestingly, theevacuation the evacuation efficiency efficiency of S2 of wasS2 was initially initially higher higher than than that that of of S1 S1 at at the the early early stage,stage, for for all all three three fire fire cases. cases. However, However, at at the the late late stage, stage, the the evacuation evacuation e ffiefficiencyciency of of S2 S2 became became lower lower thanthan that that of of S1. S1. As As mentioned mentioned above, above, the the use use of of exits exits became became largely largely unbalanced unbalanced at at the the late late stage stage of of evacuationevacuation under under three three fire fire cases, cases, resulting resulting in in a relativelya relatively low low evacuation evacuation effi efficiency.ciency.

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Figure 4. Cont. SustainabilitySustainability2020 2020, 12, 12, 684, x FOR PEER REVIEW 89 of of 11 12

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EVACUATED OCCUPANTS (PERSON) S1.3 S2.3 S3.3 0 0 200 400 600 800 EVACUATION TIME (S) (c) Evacuation Time of S1, S2, and S3 for Fire Case 3.

FigureFigure 4. 4.E ffEffectsects of of escalators escalators on on performance performance of of platform platform evacuation evacuation in in di differentfferent cases cases of of fire. fire.

3.4.2.3.4.2. E ffEffectsects of of Automatic Automatic Ticket Ticket Checkers Checkers on on Evacuation Evacuation AutomaticAutomatic ticket ticket checkers checkers enable enable metro metro stations stations to to deal deal with with passenger passenger flow flow e ffiefficientlyciently under under normalnormal circumstance. circumstance. However, However, they they could could also also be be bottlenecks bottlenecks under under emergency emergency conditions. conditions. Thus, Thus, thethe eff effectect of of automatic automatic ticket ticket checkers checkers on on metro metro evacuation evacuation should should be be carefully carefully evaluated. evaluated. TheThe total total evacuation evacuation time time in in this this section section was was calculated calculated as as the the time time all all occupants occupants were were evacuated evacuated fromfrom their their initial initial positions positions to to the the automatic automatic ticket ticket checkers. checkers. Nine Nine experiments experiments were were simulated simulated to to investigateinvestigate the the eff ectseffects of automatic of automatic ticket ticket checkers checke on evacuationrs on evacuation (see Table (see3). BasedTable on 3). the Based simulation on the results,simulation S4 had results, the longest S4 had evacuation the longest time evacuation than S5 andtime S6 than for allS5 and fire cases.S6 for Thisall fire indicates cases. This that indicates when a firethat happens when ina afire train happens or on the in platform,a train or automatic on the platform, ticket checkers automatic will decrease ticket checkers evacuation will effi decreaseciency ifevacuation they are still efficiency in normal if they status. are The still evacuationin normal status. efficiency The wasevacuation largely efficiency improved was (about largely 28% improved to 38%) when(about the 28% automatic to 38%) ticket when checkers the automatic are fully ticket open checke (i.e., S5).rs are Strategy fully open 6 did (i.e., not S5). result Strategy in an obvious6 did not improvementresult in an obvious over strategy improvement 5 (28.8% vs.over 30.7%, strategy 36.0% 5 (28.8% vs. 39.4%, vs. 30.7%, and 38.5% 36.0 vs.% vs. 39.9% 39.4%, in Table and 338.5%). This vs. finding39.9% wasin Table consistent 3). This with finding previous was consistent literature [with8]. previous literature [8]. According to Figure 5, the evacuation efficiency of S6 is slightly better than S5 at the beginning. Table 3. Total evacuation time in S4 to S6 (S4 to S6). However, the efficiency of the two strategies are almost the same at the end of evacuation process. During simulations, the occupant densityOccupants initially Totalincreased Evacuation and then decreasedRelative around automatic Fire Case Strategy ticket checkers. Thus, the effect of automatic(Person) ticket checkersTime as (s) bottlenecksEffectiveness should also (%) be large at the beginning when the occupantS4 density 378is increasing. However, 153 such bottleneck - effect was not that large for theCase whole 1 evacuationS5 process. 378 109 28.8 S6 378 106 30.7 S4Table 3. Total 1474 evacuation time in S4 480 to S6 (S4 to S6). - Case 2 S5 1474 307 36.0 Fire Occupants Total Evacuation Time Relative Effectiveness Strategy S6 1474 291 39.4 Case (Person) (s) (%) S4 2570 825 - CaseS4 3 S5378 2570 153 507 38.5 - Case 1 S5 S6378 2570 109 496 39.9 28.8 S6 378 106 30.7 S4 1474 480 - According to Figure5, the evacuation e fficiency of S6 is slightly better than S5 at the beginning. Case 2 S5 1474 307 36.0 However, the efficiency of the two strategies are almost the same at the end of evacuation process. S6 1474 291 39.4 During simulations, the occupant density initially increased and then decreased around automatic ticket checkers. Thus,S4 the effect of2570 automatic ticket checkers 825 as bottlenecks should also be - large at the beginningCase 3 when theS5 occupant density2570 is increasing. However, 507 such bottleneck effect was 38.5 not that large for the whole evacuationS6 process.2570 496 39.9 Sustainability 2020, 12, 684 9 of 11 Sustainability 2020, 12, x FOR PEER REVIEW 10 of 12

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FigureFigure 5. Evacuation 5. Evacuation performances performances for for Strategy Strategy 4 to 4 Strategyto Strategy 6. 6.

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4. Conclusions Metro stations are public transportation infrastructure, where a large number of people could gather around. The passenger traffic volume has reached or exceeded the designed transport capacity in many big cities in China. Serious incidents happening in metro stations would cause serious casualties and property losses. Thus, the safety evacuation in metros stations has drawn great public attention. Given that China has entered the stage of rapid construction of metro network, the evacuation capacity of a metro station should be carefully evaluated. In this study, a metro station in Shanghai, China was selected for simulation modeling. First, a simulation model was developed based on the actual layout of the station. Then, passenger flow data were collected, based on which important simulation parameters such as passenger demand and occupant parameters were calibrated. After that, three fire cases and multiple evacuation strategies with different usage of escalators and automatic ticket checkers were considered and simulated based on the simulation model. According to the research results, the normal capacity of the metro station can satisfy a safe evacuation when a platform fire happens. However, additional capacity should be required to ensure a safe evacuation when a train fire happens. Under this circumstance, the use of two stopped escalators as fixed evacuation passages could be considered as effective and essential for safe evacuation. However, an unbalanced usage of escalators as evacuation passages could even decrease evacuation efficiency, compared to using stairs only. The evacuation efficiency can be further improved by fully opening automatic ticket checkers instead of maintaining them at normal status. Removing automatic ticket checkers does not have additional effects on improving evacuation efficiency. In general, this study provides valuable information for facility design and emergency evacuation in metro stations in China.

Author Contributions: Conceptualization, C.W.; methodology, C.W., and Y.S.; software, Y.S.; validation, C.W., and Y.S.; resources, C.W.; data curation, C.W., and Y.S.; writing—original draft preparation, C.W., and Y.S.; writing—review and editing, C.W., and Y.S. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by Shanghai Pujiang Program (15PJC093). Acknowledgments: The authors appreciate research efforts from Qingyuan Ma, Hao Liu. Conflicts of Interest: The authors declare no conflict of interest.

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