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Experimental Study of Pedestrian Flow in a Fire-protection Evacuation Walk
Available online at www.sciencedirect.com
ScienceDirect Procedia Engineering 71 (2014) 343 – 349
Experimental Study of Pedestrian Flow in a Fire-protection Evacuation Walk Xiao-dong Liua, Wei-guo Songa,*, Fei-zhou Huoa,b, Zi-gang Jiangc b
a State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230026, China Department of Civil and Architectural Engineering, City University of Hong Kong, Hong Kong 999077, China c Dongying Fire Brigade of Shangdong Province, Dongying 257091, China
Abstract As modern society develops rapidly, underground buildings are springing up all over the city, it is very essential to study pedestrian flow in the underground corridor. An evacuation experiment was conducted in a fire-protection evacuation walk in an underground market. Passing time, walking velocity, walking preference, and specific flux in the experiment are carefully analyzed. The influences of different layouts of obstacles in the corridor and pedestrian flow direction on the corridor evacuation are emphatically studied. The results include comparisons between each scene in the unidirectional and bidirectional flow, which can provide suggestions for designers and managers.
© 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license © 2014 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the Academic Committee (http://creativecommons.org/licenses/by-nc-nd/3.0/). of ICPFFPE 2013. Peer-review under responsibility of School of Engineering of Sun Yat-Sun University Keywords: evacuation experiment, pedestrian flow, corridor, obstacle
1. Introduction In the current fire technical codes of China, it is generally regulated that there are at least two safety exits in each fire compartment within buildings, and the width of safety exits should not be smaller than the calculated width in this compartment. However, when the underground building is very large, it is so difficult to meet the fire regulation that there are not enough safety exits linked directly to the outside space in the ground. Considering these characteristics of underground buildings, Code for Fire Protection Design of Civil Air Defence Works in China defines fire-protection evacuation walk that it is a kind of walking facility equipped with fire protection measures and used to evacuate people to outdoor space safely [1]. This means that managers could utilize the fire-protection evacuation walk in the underground building to lengthen the safe evacuation distance when the situation is limited. In fact, there are currently numerous fireprotection evacuation walks in underground buildings in big cities. Therefore, it is very essential to study pedestrians’ walking behaviors in these kinds of corridors. In the experimental study, unidirectional pedestrian flow in the corridor with and without bottlenecks has often been investigated [2-4]. However, much less data are available for the bidirectional flow [5, 6], especially with different layouts of the corridor. For the study of simulations, there are many computational models concerning unidirectional and bidirectional flow in corridors. Some of them can reflect pedestrians’ many behaviors, such as lane formation in the bidirectional flow [7], right-hand walking preference [8]. To study pedestrians’ walking behaviors in the corridor with different layouts, and provide the first-hand data for computational evacuation models and evacuation guidance for the designers and managers, we conducted an evacuation experiment in a corridor. The influences of different layouts of obstacles in the corridor and pedestrian flow direction on the
* Corresponding author. Tel.: +86-551-63606415; fax: +86-551-63601669. E-mail address: [email protected]
1877-7058 © 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Peer-review under responsibility of School of Engineering of Sun Yat-Sun University doi:10.1016/j.proeng.2014.04.049
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corridor evacuation are emphatically studied. Detailed analysis of passing time, walking velocity, walking preference, and specific flux are given. 2. Experiment Setting The experiment was conducted in a fire-protection evacuation walk in a big underground market in east China. Based on the practical situation, only one part of the corridor is regarded as the object of our study. This study area is 9 meters long, 4 meters wide, and 3 meters high. As Fig.1(b), we designed four kinds of corridor layout, and both unidirectional and bidirectional pedestrian flow experiments are carried out. In scene 1, there are no obstacles in the corridor. In scene 2, there are two parallel partition fences in the middle of the corridor, both of which are 2 meters long, and 1 meter high. In scene 3, there are two square tables in the middle. The table is 0.7 meter long and 1 meter high. In scene 4, the obstacle in the middle of the corridor becomes bigger. It is the combination of the two tables in scene 3, and its length is 1.4 meters, width is 0.7 meter, and height is 1 meter.
(a) A snapshot from the experiment
(b) The layout of obstacles in the corridor
Fig. 1. The sketch map of the scenes in the experiment
There are 60 experiment participants in total, all of which are the staff of the market and most of them are women. In each scene, we conducted both unidirectional and bidirectional pedestrian flow experiment. In the unidirectional flow experiment, 60 participants walk from one side of the corridor to the other side. In the bidirectional flow experiment, there are 30 participants in each side of the corridor and they are required to begin to walk through the corridor at the same time. During the experiment process, obstacles are impenetrable, so participants cannot pass through or jump over them, and they can only walk around them. In the top of the corridor, we installed 1 HD camera in each side to record the whole experiment process. 3. Results and discussions Firstly, we make synchronous process to the videos recorded by 2 cameras. Then, one picture is captured at every two sequential frames (The frame rate of videos is 25 frames per second). We make further analysis on these captured pictures. When counting the evacuation time of every experiment, the start time is defined as the first person to enter the corridor and the end time is defined as the last person to leave the corridor. Only a part of the study area is regarded as the measurement area when calculating pedestrian’s velocity within the corridor. This area is 3.6 meters long, 4 meters wide in the middle of the corridor. 3.1. Passing time Evacuation time in each scene is obtained after data process, see Table 1. As we can see from Table 1, the evacuation time in each scene varies a lot, which means that the layout of obstacles exerts influence on evacuation in the corridor. For example, it takes the longest time in scene 3 no matter in the unidirectional or bidirectional flow. This implies that irrational design of corridors can deeply impede pedestrian evacuation. With unexpected emergencies happen in this kind of structure of corridors, the evacuation efficiency may be significantly influenced and casualties may occur. It should be noted that there are 60 participants in one side of the corridor at the beginning of the simulation of the unidirectional flow and only 30
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participants in each side of the bidirectional flow. Before the experiment begins, the length of the waiting queue in the unidirectional flow is longer and more crowd than that in the bidirectional flow. Therefore, rigorously speaking, the passing time of unidirectional and bidirectional flow should not be compared. It is found that several obvious lanes of pedestrian flow are formed in the bidirectional flow. This lane formation is one kind of self-organized phenomena in pedestrian dynamics, which has been proved to exist in the bidirectional flow by many researchers [7]. For instance, there are two lanes of pedestrian flow in each direction in scene 1, see Fig 2. In the bidirectional flow, there are 4 lanes in scene 1, 3, 4, and 5 lanes in scene 2. While in the unidirectional flow, lanes are only formed in scene 2, 3, 4, and these lanes are mainly formed by the obstacles in the corridor. The lane formation in the bidirectional flow may stem from the walk mechanism that pedestrians prefer to avoid collision with the opposite direction pedestrians and follow with the same direction ones, which can improve pedestrian movement efficiency and ultimately shorten the evacuation time in the bidirectional flow. Table 1. Passing time in each scene. Scene
Unidirectional flow (s)
Bidirectional flow (s)
Scene 1 Scene 2 Scene 3 Scene 4
19.68 19.36 21.2 19.56
16.92 16.68 19.68 18.4
Fig. 2. Lane formation in the corridor
3.2. Walking velocity The frame when pedestrians enter and leave the measurement area are firstly recorded, and then the actual time one pedestrian spends on crossing this area is calculated according to the frame, at last the actual velocity can be obtained by dividing the length of this area by the actual time. The velocity distribution under the situation of unidirectional and bidirectional flow are obtained by statistical analysis, see Fig 3. We further analyzed the velocity in each scene, and achieved the mean velocity, maximum velocity, minimum velocity, standard deviation and other parameters, see Table 2. Table 2. The velocity parameters in each scene. Scene Scene 1 Scene 2 Scene 3 Scene 4
Uni Bi Uni Bi Uni Bi Uni Bi
Mean 1.1408 1.1192 1.1122 1.0499 1.1656 0.9649 1.2811 0.9457
Sd 0.1850 0.1843 0.1264 0.1985 0.1268 0.2871 0.1028 0.2302
Max 1.6667 1.6071 1.5000 1.6667 1.5517 2.0455 1.5517 1.6667
Min 0.9184 0.8036 0.9184 0.7258 0.8654 0.6429 1.0465 0.6081
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According to the data analysis of Fig 3, it is found that on the whole the mean velocity in the unidirectional flow is bigger than that in the bidirectional flow and the velocity distribution is more centralized. As shown in Table 2, the mean velocity in the unidirectional flow is also much bigger in every scene, and the standard deviation in the unidirectional flow is obviously smaller in every scene except scene 1. Among them, the standard deviation in scene 3 is the biggest, which means the velocities in scene 3 are the most dispersedly distributed. Pedestrians in the bidirectional flow may meet the opposite pedestrians, especially in the sudden narrow area in the corridor, which can be regarded as the bottleneck. Take the situation of scene 3 for instance, in order to avoid collisions with obstacles and opposite pedestrians, pedestrians may slow down and even stop for a while.
(b)
(a)
Fig. 3. The distribution of velocity: (a) Velocity in the unidirectional flow; (b) Velocity in the bidirectional flow
By careful observation of the recorded videos, we found that pedestrians in the front walk faster than the following pedestrians. This velocity tendency is further studied by statistical analysis of the relationship between each pedestrian’s velocity (Fig 4) and the mean velocity (Table 3) against the entrance time. This phenomenon may result from that there is more free space for the front pedestrians, and when they reach the middle of the corridor, there are not so many pedestrians. But as time passes, there are more pedestrians in the corridor, so it becomes very crowd in the middle and pedestrians have to decelerate. At last, when most of people walk out the corridor, the pedestrians in the last have more space, thus the velocities of these last pedestrians increase a little. By comparing Fig 4(a) and Fig 4(b), we can find that the difference of velocities in the bidirectional flow is more obvious. The reason may be that when reaching the middle of the corridor, pedestrians in the bidirectional flow not only avoid the obstacles but also the opposite pedestrians, the congestion degree is much heavier. Therefore, pedestrians in the middle order may confront more obstructions and the velocity deceleration is more apparent. Table 3. The mean velocity (calculated every two seconds) against the entrance time. Time Unidirectional flow Bidirectional flow
(a)
<2s 1.2865 1.2005
2—4s 1.1537 1.0006
4—6s 1.1055 0.9479
6—8s 1.1298 0.9152
8—10s 1.1436 0.9035
>10s 1.1738 0.9375
(b)
Fig. 4. The distribution of velocity against the entrance time: (a) Velocity in the unidirectional flow; (b) Velocity in the bidirectional flow
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3.3. Walking preference In daily life, pedestrians may incline to walk on a certain side of the road, for instance pedestrians in China prefer to walk on the right-hand side. However, will this tendency or pedestrians’ walking habit change when a different arrangement of obstacles exists on the road? The walking preferences of each pedestrian were collected and detailed analysis was made. At first, due to the different layouts of the corridor, we redefined pedestrians’ walking preference. The right or left preference is similar to the routine definition of right-hand or left-hand preference, that is, pedestrians prefer to walk on the right-hand or left-hand side of the corridor. However, in scene 2 and 3, there are not only pedestrians walking on the right or left side, but also some walking through the interval between obstacles in the middle part of the corridor. We defined this situation as pedestrians’ middle preference. To summarize, there are three different walking preferences, i.e. right, left and middle preference. First, we analyzed pedestrians’ walking preference in the unidirectional flow and bidirectional flow separately.
(a)
(b) Fig. 5. The walking preference in each scene: (a) Walking preference in the unidirectional flow; (b) Walking preference in the bidirectional flow
The walking preference in the unidirectional flow is shown in Fig 5(a). In scene 1, the distribution of pedestrians in the corridor is relatively uniform because there are no obstacles in the corridor. The number of pedestrians preferring to walk on the right or left part of the corridor is almost the same. In scene 2 and 3, the corridor is divided into three parts by obstacles, and pedestrians walking on the middle part occupy the largest proportion. The proportion of middle walking preference is 47% and 44% separately, and the proportion of right and left walking preference gets little difference. In scene 4, the corridor is divided into two parts by obstacles. Pedestrians walking on the right occupy a larger proportion. The proportion of right and left walking preference is 55% and 45% separately. Fig 5(b) demonstrates the walking preference in the bidirectional flow. In scene 1, there are two lanes of pedestrian flow in each direction, and there is no obvious difference between the two walking preferences. The situation in scene 2 and 3 is rather similar. The proportion of right walking preference is the largest in the two scenes, both of which is 40%. Then is the proportion of middle walking preference, the proportion in scene 2 and 3 is 33% and 34% respectively. The proportion of left walking preference occupies the smallest in both scenes. In scene 4, the proportion of right walking preference is significantly larger than that of left walking preference. The proportion is 62% for the right walking preference and 38% for the left. Then, we analyzed the reasons for these outcomes. In the unidirectional flow, owing to no interference from the opposite pedestrians, there are more pedestrians preferring to walk on the middle of the corridor, for the purpose of avoiding collision with walls on the sidle sides. When pedestrians just have two choicesˈthat is right or left preference, there are more pedestrians preferring to walk right handˈwhich may stem from pedestrians’ daily habits. In the bidirectional flow, the situations change a lot when compared with the unidirectional flow. Pedestrians with right walking preference occupy the largest proportion in the bidirectional flow. Due to interference from the opposite pedestrians, the middle preference is not the smartest choice for pedestrians because it will be very crowded if pedestrians in both directions choose to walk on the middle part. In order to achieve a good profit, most pedestrians prefer to follow the daily walking habit that walking on the right hand side. When the corridor only has two partsˈthe proportion of right walking preference is also larger. It is not difficult to understand this phenomenon since following the daily walking habit can contribute to few collisions with the opposite pedestrians.
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3.4. Specific flux The specific flux is defined as the number of pedestrians that cross a certain spot divided by the width of the corridor and the time this process takes. In this experiment, the specific flux is calculated on the central line of the corridor, and pedestrians in the two directions are counted in the bidirectional flow. The results are shown in Fig 6. It is not surprising to notice that the maximum flux exist in the bidirectional flow because two streams of pedestrians flow walk across the central line at the same time. From Fig 6(a) and Fig 6(b), we can see that the specific flux rises in the earlier stage and then drops in the later stage. This is consistent with the entry and departure of the pedestrian flow. In general, specific flux in the situations of the bidirectional flow is bigger than that in the unidirectional flow except scene 3. In the situations in the unidirectional flow, pedestrian’s walking behaviors are not influenced by the opposite pedestrians, so there are no obvious differences between the four scenes. However, in the bidirectional flow, the flux is lower than the other three ones in total. This can be explained by the special layout of obstacles in scene 3. There are two tables in the middle of the corridor, which may confuse pedestrians a lot. Unlike scene 1 and scene 4, pedestrians in scene 2 and 3 have three choices, move to the right, left or middle part of the corridor. Furthermore, as the obstacles in scene 3 located in a limited area compared with obstacles in scene 4. This may arise more conflicts between pedestrians in the two directions in scene 3 as many pedestrians have to make sudden decisions in a short time.
(a)
(b) Fig. 6. The specific flux in each scene: (a) Specific flux in the unidirectional flow; (b) Specific flux in the bidirectional flow
4. Conclusions In order to study the pedestrian evacuation in the fire-protection evacuation walk, an experiment was conducted in an underground market. The results of passing time, walking velocity, walking preference, and specific flux are mainly presented. Detailed comparisons between each scene in the unidirectional and bidirectional flow are given. It is found that irrational layout of obstacles can greatly influence the pedestrian evacuation in the corridor with the long passing time, slow velocities and low specific flux. Damages and casualties may occur when fire or other emergencies happen in the corridor with irrational layout of obstacles. Therefore, managers should avoid these kinds of corridor layout. Lane formation is found in the bidirectional flow, which can improve the evacuation efficiency by avoiding the opposite pedestrians and following the same direction pedestrians. From the statistical analysis, we get the conclusion that velocity in the unidirectional flow is on average larger than that in the bidirectional flow, and the former one is more centralized. The entrance time also has influence on pedestrian’s velocity, that is, pedestrians in the front walk faster than the following pedestrians in crowd situations. As previous study, pedestrians in China have right walking preference in the corridor without middle part. However, the conclusion changes a lot in the situations of the corridor with the middle part. In the unidirectional flow, pedestrians walking on the middle part occupy the largest proportion. While in the bidirectional flow, the middle walking preference occupies the second and the biggest one is the right walking preference.
Acknowledgements This work is supported by the Key Technologies R&D Program of China during the 12th Five-year Plan Period (2011BAK03B02), the National Basic Research Program of China (2012CB719705), the National Natural Science Foundation of China (51120165001), and Fundamental Research Funds for the Central Universities (WK2320000014).
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References [1] Office of Civil Air Defence of the People's Republic of China, 2009. Code for Fire Protection Design of Civil Air Defence Works(GB50098-2009), China planning press [2] D. Helbing, L. Buzna, A. Johansson, T. Werner, 2005. Self-organized pedestrian crowd dynamics: Experiments, simulations, and design solutions, Transportation Science 39, p. 1-24. [3] T. Kretz, A. Grünebohm, M. Schreckenberg, 2006. Experimental study of pedestrian flow through a bottleneck, Journal of Statistical Mechanics: Theory and Experiment 2006, p. 10014. [4] A. Seyfried, O. Passon, B. Steffen, M. Boltes, T. Rupprecht, W. Klingsch, 2009. New insights into pedestrian flow through bottlenecks, Transportation Science 43, p. 395-406. [5] M. Isobe, T. Adachi, T. Nagatani, 2004. Experiment and simulation of pedestrian counter flow, Physica A: Statistical Mechanics and its Applications 336, p. 638-650. [6] T. Kretz, A. Grünebohm, M. Kaufman, F. Mazur, M. Schreckenberg, 2006. Experimental study of pedestrian counterflow in a corridor, Journal of Statistical Mechanics: Theory and Experiment 2006, p. 10001. [7] J. Ma, W. Song, J. Zhang, S. Lo, G. Liao, 2010. k-Nearest-Neighbor interaction induced self-organized pedestrian counter flow, Physica A: Statistical Mechanics and its Applications 389, p. 2101-2117. [8] L. Yang, J. Li, S. Liu, 2008. Simulation of pedestrian counter-flow with right-moving preference, Physica A: Statistical Mechanics and its Applications 387, p. 3281-3289.
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Experimental Study of Pedestrian Flow in a Fire-protection Evacuation Walk Xiao-dong Liua, Wei-guo Songa,*, Fei-zhou Huoa,b, Zi-gang Jiangc b
a State Key Laboratory of Fire Science, University of Science and Technology of China, Hefei 230026, China Department of Civil and Architectural Engineering, City University of Hong Kong, Hong Kong 999077, China c Dongying Fire Brigade of Shangdong Province, Dongying 257091, China
Abstract As modern society develops rapidly, underground buildings are springing up all over the city, it is very essential to study pedestrian flow in the underground corridor. An evacuation experiment was conducted in a fire-protection evacuation walk in an underground market. Passing time, walking velocity, walking preference, and specific flux in the experiment are carefully analyzed. The influences of different layouts of obstacles in the corridor and pedestrian flow direction on the corridor evacuation are emphatically studied. The results include comparisons between each scene in the unidirectional and bidirectional flow, which can provide suggestions for designers and managers.
© 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license © 2014 The Authors. Published by Elsevier Ltd. Selection and peer-review under responsibility of the Academic Committee (http://creativecommons.org/licenses/by-nc-nd/3.0/). of ICPFFPE 2013. Peer-review under responsibility of School of Engineering of Sun Yat-Sun University Keywords: evacuation experiment, pedestrian flow, corridor, obstacle
1. Introduction In the current fire technical codes of China, it is generally regulated that there are at least two safety exits in each fire compartment within buildings, and the width of safety exits should not be smaller than the calculated width in this compartment. However, when the underground building is very large, it is so difficult to meet the fire regulation that there are not enough safety exits linked directly to the outside space in the ground. Considering these characteristics of underground buildings, Code for Fire Protection Design of Civil Air Defence Works in China defines fire-protection evacuation walk that it is a kind of walking facility equipped with fire protection measures and used to evacuate people to outdoor space safely [1]. This means that managers could utilize the fire-protection evacuation walk in the underground building to lengthen the safe evacuation distance when the situation is limited. In fact, there are currently numerous fireprotection evacuation walks in underground buildings in big cities. Therefore, it is very essential to study pedestrians’ walking behaviors in these kinds of corridors. In the experimental study, unidirectional pedestrian flow in the corridor with and without bottlenecks has often been investigated [2-4]. However, much less data are available for the bidirectional flow [5, 6], especially with different layouts of the corridor. For the study of simulations, there are many computational models concerning unidirectional and bidirectional flow in corridors. Some of them can reflect pedestrians’ many behaviors, such as lane formation in the bidirectional flow [7], right-hand walking preference [8]. To study pedestrians’ walking behaviors in the corridor with different layouts, and provide the first-hand data for computational evacuation models and evacuation guidance for the designers and managers, we conducted an evacuation experiment in a corridor. The influences of different layouts of obstacles in the corridor and pedestrian flow direction on the
* Corresponding author. Tel.: +86-551-63606415; fax: +86-551-63601669. E-mail address: [email protected]
1877-7058 © 2014 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). Peer-review under responsibility of School of Engineering of Sun Yat-Sun University doi:10.1016/j.proeng.2014.04.049
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Xiao-dong Liu et al. / Procedia Engineering 71 (2014) 343 – 349
corridor evacuation are emphatically studied. Detailed analysis of passing time, walking velocity, walking preference, and specific flux are given. 2. Experiment Setting The experiment was conducted in a fire-protection evacuation walk in a big underground market in east China. Based on the practical situation, only one part of the corridor is regarded as the object of our study. This study area is 9 meters long, 4 meters wide, and 3 meters high. As Fig.1(b), we designed four kinds of corridor layout, and both unidirectional and bidirectional pedestrian flow experiments are carried out. In scene 1, there are no obstacles in the corridor. In scene 2, there are two parallel partition fences in the middle of the corridor, both of which are 2 meters long, and 1 meter high. In scene 3, there are two square tables in the middle. The table is 0.7 meter long and 1 meter high. In scene 4, the obstacle in the middle of the corridor becomes bigger. It is the combination of the two tables in scene 3, and its length is 1.4 meters, width is 0.7 meter, and height is 1 meter.
(a) A snapshot from the experiment
(b) The layout of obstacles in the corridor
Fig. 1. The sketch map of the scenes in the experiment
There are 60 experiment participants in total, all of which are the staff of the market and most of them are women. In each scene, we conducted both unidirectional and bidirectional pedestrian flow experiment. In the unidirectional flow experiment, 60 participants walk from one side of the corridor to the other side. In the bidirectional flow experiment, there are 30 participants in each side of the corridor and they are required to begin to walk through the corridor at the same time. During the experiment process, obstacles are impenetrable, so participants cannot pass through or jump over them, and they can only walk around them. In the top of the corridor, we installed 1 HD camera in each side to record the whole experiment process. 3. Results and discussions Firstly, we make synchronous process to the videos recorded by 2 cameras. Then, one picture is captured at every two sequential frames (The frame rate of videos is 25 frames per second). We make further analysis on these captured pictures. When counting the evacuation time of every experiment, the start time is defined as the first person to enter the corridor and the end time is defined as the last person to leave the corridor. Only a part of the study area is regarded as the measurement area when calculating pedestrian’s velocity within the corridor. This area is 3.6 meters long, 4 meters wide in the middle of the corridor. 3.1. Passing time Evacuation time in each scene is obtained after data process, see Table 1. As we can see from Table 1, the evacuation time in each scene varies a lot, which means that the layout of obstacles exerts influence on evacuation in the corridor. For example, it takes the longest time in scene 3 no matter in the unidirectional or bidirectional flow. This implies that irrational design of corridors can deeply impede pedestrian evacuation. With unexpected emergencies happen in this kind of structure of corridors, the evacuation efficiency may be significantly influenced and casualties may occur. It should be noted that there are 60 participants in one side of the corridor at the beginning of the simulation of the unidirectional flow and only 30
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participants in each side of the bidirectional flow. Before the experiment begins, the length of the waiting queue in the unidirectional flow is longer and more crowd than that in the bidirectional flow. Therefore, rigorously speaking, the passing time of unidirectional and bidirectional flow should not be compared. It is found that several obvious lanes of pedestrian flow are formed in the bidirectional flow. This lane formation is one kind of self-organized phenomena in pedestrian dynamics, which has been proved to exist in the bidirectional flow by many researchers [7]. For instance, there are two lanes of pedestrian flow in each direction in scene 1, see Fig 2. In the bidirectional flow, there are 4 lanes in scene 1, 3, 4, and 5 lanes in scene 2. While in the unidirectional flow, lanes are only formed in scene 2, 3, 4, and these lanes are mainly formed by the obstacles in the corridor. The lane formation in the bidirectional flow may stem from the walk mechanism that pedestrians prefer to avoid collision with the opposite direction pedestrians and follow with the same direction ones, which can improve pedestrian movement efficiency and ultimately shorten the evacuation time in the bidirectional flow. Table 1. Passing time in each scene. Scene
Unidirectional flow (s)
Bidirectional flow (s)
Scene 1 Scene 2 Scene 3 Scene 4
19.68 19.36 21.2 19.56
16.92 16.68 19.68 18.4
Fig. 2. Lane formation in the corridor
3.2. Walking velocity The frame when pedestrians enter and leave the measurement area are firstly recorded, and then the actual time one pedestrian spends on crossing this area is calculated according to the frame, at last the actual velocity can be obtained by dividing the length of this area by the actual time. The velocity distribution under the situation of unidirectional and bidirectional flow are obtained by statistical analysis, see Fig 3. We further analyzed the velocity in each scene, and achieved the mean velocity, maximum velocity, minimum velocity, standard deviation and other parameters, see Table 2. Table 2. The velocity parameters in each scene. Scene Scene 1 Scene 2 Scene 3 Scene 4
Uni Bi Uni Bi Uni Bi Uni Bi
Mean 1.1408 1.1192 1.1122 1.0499 1.1656 0.9649 1.2811 0.9457
Sd 0.1850 0.1843 0.1264 0.1985 0.1268 0.2871 0.1028 0.2302
Max 1.6667 1.6071 1.5000 1.6667 1.5517 2.0455 1.5517 1.6667
Min 0.9184 0.8036 0.9184 0.7258 0.8654 0.6429 1.0465 0.6081
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According to the data analysis of Fig 3, it is found that on the whole the mean velocity in the unidirectional flow is bigger than that in the bidirectional flow and the velocity distribution is more centralized. As shown in Table 2, the mean velocity in the unidirectional flow is also much bigger in every scene, and the standard deviation in the unidirectional flow is obviously smaller in every scene except scene 1. Among them, the standard deviation in scene 3 is the biggest, which means the velocities in scene 3 are the most dispersedly distributed. Pedestrians in the bidirectional flow may meet the opposite pedestrians, especially in the sudden narrow area in the corridor, which can be regarded as the bottleneck. Take the situation of scene 3 for instance, in order to avoid collisions with obstacles and opposite pedestrians, pedestrians may slow down and even stop for a while.
(b)
(a)
Fig. 3. The distribution of velocity: (a) Velocity in the unidirectional flow; (b) Velocity in the bidirectional flow
By careful observation of the recorded videos, we found that pedestrians in the front walk faster than the following pedestrians. This velocity tendency is further studied by statistical analysis of the relationship between each pedestrian’s velocity (Fig 4) and the mean velocity (Table 3) against the entrance time. This phenomenon may result from that there is more free space for the front pedestrians, and when they reach the middle of the corridor, there are not so many pedestrians. But as time passes, there are more pedestrians in the corridor, so it becomes very crowd in the middle and pedestrians have to decelerate. At last, when most of people walk out the corridor, the pedestrians in the last have more space, thus the velocities of these last pedestrians increase a little. By comparing Fig 4(a) and Fig 4(b), we can find that the difference of velocities in the bidirectional flow is more obvious. The reason may be that when reaching the middle of the corridor, pedestrians in the bidirectional flow not only avoid the obstacles but also the opposite pedestrians, the congestion degree is much heavier. Therefore, pedestrians in the middle order may confront more obstructions and the velocity deceleration is more apparent. Table 3. The mean velocity (calculated every two seconds) against the entrance time. Time Unidirectional flow Bidirectional flow
(a)
<2s 1.2865 1.2005
2—4s 1.1537 1.0006
4—6s 1.1055 0.9479
6—8s 1.1298 0.9152
8—10s 1.1436 0.9035
>10s 1.1738 0.9375
(b)
Fig. 4. The distribution of velocity against the entrance time: (a) Velocity in the unidirectional flow; (b) Velocity in the bidirectional flow
Xiao-dong Liu et al. / Procedia Engineering 71 (2014) 343 – 349
3.3. Walking preference In daily life, pedestrians may incline to walk on a certain side of the road, for instance pedestrians in China prefer to walk on the right-hand side. However, will this tendency or pedestrians’ walking habit change when a different arrangement of obstacles exists on the road? The walking preferences of each pedestrian were collected and detailed analysis was made. At first, due to the different layouts of the corridor, we redefined pedestrians’ walking preference. The right or left preference is similar to the routine definition of right-hand or left-hand preference, that is, pedestrians prefer to walk on the right-hand or left-hand side of the corridor. However, in scene 2 and 3, there are not only pedestrians walking on the right or left side, but also some walking through the interval between obstacles in the middle part of the corridor. We defined this situation as pedestrians’ middle preference. To summarize, there are three different walking preferences, i.e. right, left and middle preference. First, we analyzed pedestrians’ walking preference in the unidirectional flow and bidirectional flow separately.
(a)
(b) Fig. 5. The walking preference in each scene: (a) Walking preference in the unidirectional flow; (b) Walking preference in the bidirectional flow
The walking preference in the unidirectional flow is shown in Fig 5(a). In scene 1, the distribution of pedestrians in the corridor is relatively uniform because there are no obstacles in the corridor. The number of pedestrians preferring to walk on the right or left part of the corridor is almost the same. In scene 2 and 3, the corridor is divided into three parts by obstacles, and pedestrians walking on the middle part occupy the largest proportion. The proportion of middle walking preference is 47% and 44% separately, and the proportion of right and left walking preference gets little difference. In scene 4, the corridor is divided into two parts by obstacles. Pedestrians walking on the right occupy a larger proportion. The proportion of right and left walking preference is 55% and 45% separately. Fig 5(b) demonstrates the walking preference in the bidirectional flow. In scene 1, there are two lanes of pedestrian flow in each direction, and there is no obvious difference between the two walking preferences. The situation in scene 2 and 3 is rather similar. The proportion of right walking preference is the largest in the two scenes, both of which is 40%. Then is the proportion of middle walking preference, the proportion in scene 2 and 3 is 33% and 34% respectively. The proportion of left walking preference occupies the smallest in both scenes. In scene 4, the proportion of right walking preference is significantly larger than that of left walking preference. The proportion is 62% for the right walking preference and 38% for the left. Then, we analyzed the reasons for these outcomes. In the unidirectional flow, owing to no interference from the opposite pedestrians, there are more pedestrians preferring to walk on the middle of the corridor, for the purpose of avoiding collision with walls on the sidle sides. When pedestrians just have two choicesˈthat is right or left preference, there are more pedestrians preferring to walk right handˈwhich may stem from pedestrians’ daily habits. In the bidirectional flow, the situations change a lot when compared with the unidirectional flow. Pedestrians with right walking preference occupy the largest proportion in the bidirectional flow. Due to interference from the opposite pedestrians, the middle preference is not the smartest choice for pedestrians because it will be very crowded if pedestrians in both directions choose to walk on the middle part. In order to achieve a good profit, most pedestrians prefer to follow the daily walking habit that walking on the right hand side. When the corridor only has two partsˈthe proportion of right walking preference is also larger. It is not difficult to understand this phenomenon since following the daily walking habit can contribute to few collisions with the opposite pedestrians.
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3.4. Specific flux The specific flux is defined as the number of pedestrians that cross a certain spot divided by the width of the corridor and the time this process takes. In this experiment, the specific flux is calculated on the central line of the corridor, and pedestrians in the two directions are counted in the bidirectional flow. The results are shown in Fig 6. It is not surprising to notice that the maximum flux exist in the bidirectional flow because two streams of pedestrians flow walk across the central line at the same time. From Fig 6(a) and Fig 6(b), we can see that the specific flux rises in the earlier stage and then drops in the later stage. This is consistent with the entry and departure of the pedestrian flow. In general, specific flux in the situations of the bidirectional flow is bigger than that in the unidirectional flow except scene 3. In the situations in the unidirectional flow, pedestrian’s walking behaviors are not influenced by the opposite pedestrians, so there are no obvious differences between the four scenes. However, in the bidirectional flow, the flux is lower than the other three ones in total. This can be explained by the special layout of obstacles in scene 3. There are two tables in the middle of the corridor, which may confuse pedestrians a lot. Unlike scene 1 and scene 4, pedestrians in scene 2 and 3 have three choices, move to the right, left or middle part of the corridor. Furthermore, as the obstacles in scene 3 located in a limited area compared with obstacles in scene 4. This may arise more conflicts between pedestrians in the two directions in scene 3 as many pedestrians have to make sudden decisions in a short time.
(a)
(b) Fig. 6. The specific flux in each scene: (a) Specific flux in the unidirectional flow; (b) Specific flux in the bidirectional flow
4. Conclusions In order to study the pedestrian evacuation in the fire-protection evacuation walk, an experiment was conducted in an underground market. The results of passing time, walking velocity, walking preference, and specific flux are mainly presented. Detailed comparisons between each scene in the unidirectional and bidirectional flow are given. It is found that irrational layout of obstacles can greatly influence the pedestrian evacuation in the corridor with the long passing time, slow velocities and low specific flux. Damages and casualties may occur when fire or other emergencies happen in the corridor with irrational layout of obstacles. Therefore, managers should avoid these kinds of corridor layout. Lane formation is found in the bidirectional flow, which can improve the evacuation efficiency by avoiding the opposite pedestrians and following the same direction pedestrians. From the statistical analysis, we get the conclusion that velocity in the unidirectional flow is on average larger than that in the bidirectional flow, and the former one is more centralized. The entrance time also has influence on pedestrian’s velocity, that is, pedestrians in the front walk faster than the following pedestrians in crowd situations. As previous study, pedestrians in China have right walking preference in the corridor without middle part. However, the conclusion changes a lot in the situations of the corridor with the middle part. In the unidirectional flow, pedestrians walking on the middle part occupy the largest proportion. While in the bidirectional flow, the middle walking preference occupies the second and the biggest one is the right walking preference.
Acknowledgements This work is supported by the Key Technologies R&D Program of China during the 12th Five-year Plan Period (2011BAK03B02), the National Basic Research Program of China (2012CB719705), the National Natural Science Foundation of China (51120165001), and Fundamental Research Funds for the Central Universities (WK2320000014).
Xiao-dong Liu et al. / Procedia Engineering 71 (2014) 343 – 349
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