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Experimental Study on Crowd Flow Passing through Ticket Gates in Railway Stations
Available online at www.sciencedirect.com
ScienceDirect Transportation Research Procedia 2 (2014) 630 – 635
Pedestrian and and Evacuation Evacuation Dynamics 2014 (PED2014) The Conference on in Pedestrian (PED2014)
Experimental study on crowd flow passing through ticket gates in railway stations Kosuke Fujiia,*, Tomonori Sanoa a
Waseda University, Mikajima 2-579-15, Tokorozawa, Saitama 359-1192, Japan
Abstract Ticket gates in railway stations or stadiums and security gates in office buildings pose difficulties for evacuation in in case of fire. This paper focuses on the characteristics of a crowd passing through the ticket gates of Japanese railway stations. The characteristics of a crowd flow passing through ticket gates were identified, and numerical values were derived to estimate the evacuation time. A total of 48 subjects were asked to pass through a ticket gate with three passages and three different wide passages, where each width was the same as the sum of the three passage widths of the ticket gate. The crowd flow through the ticket gate was simulated with the pedestrian simulation model SimTread. The results of this study elucidated the flow rate through the ticket gates and the numerical values to calculate the time for evacuation planning. © 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). © 2014 The Authors. Published by Elsevier B.V. Peer-review of Department of Transport & Planning Faculty of Civil Engineering and Geosciences Peer-reviewunder underresponsibility responsibility of PED2014. Delft University of Technology Keywords: station; ticket gates; crowd flow; evacuation; width of narrow passage; experiment; simulation
1. Introduction 1.1 Background Narrow passages, such as ticket gates in railway stations or stadiums and security gates in office buildings, do not have enough width for pedestrians to pass through them compared to normal passages in the architecture like corridors. The dynamics of pedestrians passing through narrow passages are different from those of normal passages.
* Corresponding author. Tel.: +81-4-2947-7113 fax:.+81-4-2947-7113 E-mail address: [email protected]
2352-1465 © 2014 The Authors. Published by Elsevier B.V. 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 Department of Transport & Planning Faculty of Civil Engineering and Geosciences Delft University of Technology doi:10.1016/j.trpro.2014.09.105
631
Kosuke Fujii and Tomonori Sano / Transportation Research Procedia 2 (2014) 630 – 635
In particular, a crowd passing through narrow passages like ticket gates can cause accidents in the case of congestion. A crowd passing through ticket or security gates poses difficulties for evacuation; for example, evacuees may fail to escape in in case of fire. The studies about the dynamics of pedestrian’s movement were conducted (Hankin et al. (1958), Older (1968) and Navin et al. (1969)). Also, the relation between the body scale and the shoulder movement in passing through apertures (Warren et al. (1987)) and the dynamics of crowd flow (Daamen et al. (2007) and Seer et al. (2008)) were studied. This paper focuses on the characteristics of a crowd flow through the ticket gates of a Japanese railway station. In Japanese railway stations, all of the ticket gates are left open in in case of a fire. Evacuees can pass through without having to use a paper ticket or integrated circuit (IC) card. However, the ticket gates act as obstacles to the evacuation of people because they have narrow passages. 1.2 Simulation performance and problems The pedestrian simulation model SimTread was previously developed by the authors. It is a multi-agent model where each agent walks independently according to its activity rules. Each agent proceeds to its destination, which is defined by the user in advance, using the shortest route. Each agent is affected by obstacles and other agents around it and walks or stops to avoid them according to the situation (Kimura et al. (2009)). SimTread was validated with experimental data on crowd flow. It was shown to be able to reproduce crowd flow and predict the evacuation time for the evaluation of pedestrian movement in architectural plans in both normal and emergency situations. 2. Purpose The aim of this study was to identify the characteristics of a crowd flow passing through ticket gates and derive numerical values to estimate the evacuation time. In addition, the numerical values were examined with SimTread through a comparison of the experimental and simulation results. 3. Method 3.1 Experiment on crowd passing through ticket gates Experiments were carried out on the crowd flow of evacuees passing through the ticket gate of a railway station. In total, 48 subjects were asked to pass through a ticket gate with three passages and four automatic ticket checkers and three passage patterns for which the widths were the same as the sum of the passage widths of the ticket gate (Fig. 1). The subjects approached the ticket gate from various start positions and had various goals (Fig. 2). Two start positions and three goals were set. In one experiment trial, all subjects were given one start position. As experiment conditions, two one-goal cases, two two-goal cases, and one three-goal case combining all three goals were set. 2200 2200
1100
1650 1100
550
Plan (a)
1600
900
Elevation
2000
400
1600
1600
1650
Elevation
Plan (b)
Fig. 1. (a) Dimensions of ticket gate in experiment (unit: mm); (b) dimensions of three passage patterns (unit: mm)
632
Kosuke Fujii and Tomonori Sano / Transportation Research Procedia 2 (2014) 630 – 635
This experiment was simulating an evacuation, so the subjects could pass through the ticket gate without using a paper ticket or IC card. In the experiment, the width of each ticket gate passage was 550 mm. The each passage of the ticket gate was called “lane”. Model boxes made of wood were used to serve as the automatic ticket checkers. 3.2 Determining simulation parameters based on experiment The crowd flow through the ticket gate was simulated with SimTread. The simulation was run with the ticket gate and three passage patterns: 1100, 1650, and 2200 mm. Ten simulation trials were run for each passage pattern. The walking speed of the crowd was defined as the speed of one of the subjects at the head. Thus, the walking speed of the agents was the average of one of the subjects who walked at the head of the crowd. Based on video of the experiment, the constant walking speed of the agents was calculated from the walking speed after the first step. The average speed was calculated at 0.1 s intervals for one subject. The fastest walking speed of the agents was set to 1.23 m/s. 4. Results 4.1 Rules for subjects selecting one of multiple passages in ticket gates in experiment Fig. 3 shows the number of subjects that passed through each of the three lanes in the ticket gate according to the start and goal positions in the experiment. About 16 subjects passed through each of the three lanes in the ticket gate. The number of subjects passing through each lane did not differ based on the start position and goal. In addition, for each line in the initial position, the number of subjects passing through each lane of the ticket gate was counted by the start and goal positions and did not differ significantly. 2400
600
Pass line
2700
Ticket gate or Corridor
Position 2
From a passage to goals
Lane No.
4385
Corridor-passage
Ticket gate
2400
600
Position 2 Pass line
Position 1 Position 1 2400
(a)
600
Line No.
(b)
From a position area to a passage
(c)
Fig. 2. (a) Plan of experiment space; (b) line number of subjects and lane number of ticket gate; (c) examples of experiment
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Kosuke Fujii and Tomonori Sano / Transportation Research Procedia 2 (2014) 630 – 635
Fig. 4 shows the average number of subjects who passed through each lane and were in each line by the start positions in the experiment. The maximum of standard deviations was 1.18 persons and minimum was 0.1 persons. From a 95% confidence interval (= 1.96 times the standard deviation), the dispersion was small. Consequently, all of the 12 subjects in lines 1 and 4 passed through lanes 1 and 3, respectively, of the ticket gate. Four subjects in lines 2 and 3 passed through lanes 1 and 3, respectively. The remaining eight subjects in lines 2 and 3 passed through lane 2.
Persons
1
1
1
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
Persons
20 18 16 14 12 10 8 6 4 2 0
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
Persons
Persons
Persons
Persons
Persons
Persons
Persons
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
Line 1
1
Line 2
2 3 Lane
Line 3
Line 4
Fig. 3. Number of subjects passing through each lane for different positions and goals
Persons
1
2 3 Lane
Line 2
2 3 Lane
Line 3
2 3 Lane
Persons 1
Line 4
1
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
1
Persons 1
20 18 16 14 12 10 8 6 4 2 0
1
Persons
Persons
Persons
Persons
20 18 16 14 12 10 8 6 4 2 0
Persons
Line 1
Persons
20 18 16 14 12 10 8 6 4 2 0
Persons
Line 14
2 3 Lane
Line 1
Line 2
Fig. 4. Average number of subjects passing through each lane for different line positions
1
2 3 Lane
1
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
Line 3
Line 4
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Kosuke Fujii and Tomonori Sano / Transportation Research Procedia 2 (2014) 630 – 635
4.2 Flow rate and effective width of ticket gate in experiment
1.20 1.00 0.80 0.60
Lane 1
0.40
Lane 2
0.20
Lane 3
0.00 A
ABC
BC
B
A
Position 1
ABC
BC
B
C
Flow rate (person / s)
Flow rate (person / s)
Fig. 5 shows the average flow rates of the subjects passing through each of the three passages in the ticket gate by the start and goal positions. The flow rates for the different start and goal positions differed by 0.1 subject/s or less. The flow rates at each goal position were calculated for each start position. The difference between the maximum and minimum flow rates was 0.03 subject/s for position 1 and 0.05 subject/s for position 2. The differences for each position were small. Fig. 6(a) shows the average flow rates of the 1100, 1650, and 2200 mm passages and the average total flow rates of the ticket gate. The total flow rates were calculated for the ticket gate by one trial (the 48 subjects divided by the time for all of them to pass through the ticket gate by the start and goal positions). In a comparison of the four flow rates, the total flow rate of the ticket gate was between the flow rates of the 1650 and 2200 mm passages. The height of the ticket gate was 900 mm, which was below the subjects’ shoulders. The shoulders of the passing subjects passed over the ticket checker. The width between two ticket checkers was 550 mm. The subjects can be more difficult to pass through passages with the same width and walls that are higher than their shoulders than through the ticket gates. For the ticket checker is less than shoulder height, the passage widths regarded as a passage with walls that are higher than shoulder height should probably not be considered to be 550 mm. Based on the relation between the flow rates of the three passages and their width, a linear regression was found for the flow rate as a function of the width of a passage forming one corridor. These results are shown in Fig. 6(b). The total flow rate through the ticket gate was substituted in the regression equation, and the ticket gate with three passages was found to be equivalent to one passage with a width of about 1870 mm. The estimated width per passage accounting for the subjects’ shoulder movement was about 620 mm.
1.20 1.00 0.80 0.60
1.07
1.07
1.04
1.06
0.98
0.97
A
ABC
BC
B
A
ABC
0.40
0.98
1.00
0.95
BC
B
C
0.20 0.00
Position 2
Position 1
Position 2 Goal by position
Goal by position
(a)
(b)
4.00 3.50 3.00 2.50 2.00 1.50 1.00 0.50 0.00
3.16
3.04
3.55
1.85
Ticket gate
1100mm passage
1650mm passage
Types of passages (a)
2200mm passage
Flow rate流動量（人/s） < Fr > person / s
Flow rate (person / s)
Fig. 5. (a) Average flow rate in each lane for different positions and goals; (b) average flow rate in all lanes for different positions and goals
3.5 3
Fr = 0.257 + 0.00155 W 3.16
2.5 2 1.5 1000
1870
N = 14 r = 0.96 p < 0.0001
1400 1800 2200 通路幅（mm） Width < W > mm (b)
Fig. 6. (a) Average flow rate for different passages; (b) flow rate of passages forming one corridor as a function of their width
635
Frow rate (person / s)
Kosuke Fujii and Tomonori Sano / Transportation Research Procedia 2 (2014) 630 – 635 4.50
Experiment
4.00
SimTread
3.50 3.00 2.50 2.00 1.50
3.25
3.16
3.04
1.00
1.85
2.92
3.29
3.55
3.77
: Max speed (1.23m/s)
1.76
: Lower speed
0.50 0.00 Ticket gate (goal A, experiment)
Ticket gate (experiment)
1100mm passage
1650mm passage
1860mm passage
2200mm passage
Types of passages
(a)
or Avoidance
1860mm passage
: Stop walking (0m/s)
(b)
Fig. 7. (a) Average flow rate for each type of passage in experiment and simulation; (b) examples of simulation
4.3 Verification of flow rate and effective width of ticket gate by simulation Fig. 7(a) shows the average flow rates through the ticket gate and the three passages in the experiment and simulation. In the simulation, the average flow rate was taken from the average of 10 trials for each type of passages. The estimated width of 620 mm per lane taking into account the shoulder movement was found to be the same as the width of one corridor in terms of the flow rate. The average total flow rate through the ticket gate in the case of goal A in the experiment was the same as the flow rate of the 1860 mm passage in the simulation. That of the ticket gate in the case of all goals was lower than that in the case of goal A and the 1860 mm passage, but this difference may be random since the time to pass through was short. The width of 1860 mm was three times 620 mm and thus equivalent to the width of the ticket gate accounting for shoulder movement. Thus, the estimated width of 620 mm per lane is equivalent to the width of one corridor in terms of the flow rate. 5. Conclusion Experiments were performed to elucidate the characteristics of a crowd passing through a ticket gate for the evacuation of a railway station. The experimental results were verified through their reproduction using SimTread. The results were as follows: (1) In the case of a single crowd, the number of evacuees that passed through each of the three passages of the ticket gate did not differ with the start and goal positions. (2) In the case of a single crowd, the relation between the positions of the evacuees in the crowd and the number of evacuees passing through each of the three passages of the ticket gate did not differ with the start and goal positions. (3) In the case of a single crowd, the flow rate in one passage of the ticket gate did not differ by the goal position for each start position. (4) Based on the fact that the ticket checkers were below shoulder height, the width per passage of the ticket gate was equivalent to about 620 mm. (5) The SimTread results validated the estimated width of 620 mm per passage considering the shoulder movement in terms of the flow rate. References Hankin, B.D., Wright, R. A., 1958. Passenger Flow in Subways. Operational Research Quarterly, 9(2), pp.81-88. Older, S. J., 1968. Movement of Pedestrians on Footways in Shopping Streets. Traffic Engineering Control, pp.160-163. Navin, F. P. D, Wheeler, R. J., 1969. Pedestrian Flow Characteristics, Traffic Engineering, pp.30-33. Warren, W. H., Whang, S., 1987. Visual guidance of walking through apertures -body-scaled information for affordances-. Journal of Experimental Psychology: Human Perception and Performance, 13, pp.371-383. Daamen, W., Hoogendoorn, S. P., 2007. “Free Speed Distributions; Based on Empirical Data in Different Traffic Conditions,” Pedestrian and Evacuation Dynamics 2005, pp.13-25. Seer, S., Bauer, D., Brändle, N., Ray, M., 2008. “Estimating pedestrian movement characteristics for crowd control at public transport facilities.” 11th International IEEE Conference on Intelligent Transportation Systems, pp.742-737 Kimura, T., Sano, T., Hayashida, K., Takeichi, N., Minegishi, Y., Yoshida, Y., Watanabe, H., 2009. Representation of crowd in multi-agent model: Development of pedestrian simulation system SimTread. Journal of architecture and planning, 74(636), pp.371-377.
ScienceDirect Transportation Research Procedia 2 (2014) 630 – 635
Pedestrian and and Evacuation Evacuation Dynamics 2014 (PED2014) The Conference on in Pedestrian (PED2014)
Experimental study on crowd flow passing through ticket gates in railway stations Kosuke Fujiia,*, Tomonori Sanoa a
Waseda University, Mikajima 2-579-15, Tokorozawa, Saitama 359-1192, Japan
Abstract Ticket gates in railway stations or stadiums and security gates in office buildings pose difficulties for evacuation in in case of fire. This paper focuses on the characteristics of a crowd passing through the ticket gates of Japanese railway stations. The characteristics of a crowd flow passing through ticket gates were identified, and numerical values were derived to estimate the evacuation time. A total of 48 subjects were asked to pass through a ticket gate with three passages and three different wide passages, where each width was the same as the sum of the three passage widths of the ticket gate. The crowd flow through the ticket gate was simulated with the pedestrian simulation model SimTread. The results of this study elucidated the flow rate through the ticket gates and the numerical values to calculate the time for evacuation planning. © 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/). © 2014 The Authors. Published by Elsevier B.V. Peer-review of Department of Transport & Planning Faculty of Civil Engineering and Geosciences Peer-reviewunder underresponsibility responsibility of PED2014. Delft University of Technology Keywords: station; ticket gates; crowd flow; evacuation; width of narrow passage; experiment; simulation
1. Introduction 1.1 Background Narrow passages, such as ticket gates in railway stations or stadiums and security gates in office buildings, do not have enough width for pedestrians to pass through them compared to normal passages in the architecture like corridors. The dynamics of pedestrians passing through narrow passages are different from those of normal passages.
* Corresponding author. Tel.: +81-4-2947-7113 fax:.+81-4-2947-7113 E-mail address: [email protected]
2352-1465 © 2014 The Authors. Published by Elsevier B.V. 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 Department of Transport & Planning Faculty of Civil Engineering and Geosciences Delft University of Technology doi:10.1016/j.trpro.2014.09.105
631
Kosuke Fujii and Tomonori Sano / Transportation Research Procedia 2 (2014) 630 – 635
In particular, a crowd passing through narrow passages like ticket gates can cause accidents in the case of congestion. A crowd passing through ticket or security gates poses difficulties for evacuation; for example, evacuees may fail to escape in in case of fire. The studies about the dynamics of pedestrian’s movement were conducted (Hankin et al. (1958), Older (1968) and Navin et al. (1969)). Also, the relation between the body scale and the shoulder movement in passing through apertures (Warren et al. (1987)) and the dynamics of crowd flow (Daamen et al. (2007) and Seer et al. (2008)) were studied. This paper focuses on the characteristics of a crowd flow through the ticket gates of a Japanese railway station. In Japanese railway stations, all of the ticket gates are left open in in case of a fire. Evacuees can pass through without having to use a paper ticket or integrated circuit (IC) card. However, the ticket gates act as obstacles to the evacuation of people because they have narrow passages. 1.2 Simulation performance and problems The pedestrian simulation model SimTread was previously developed by the authors. It is a multi-agent model where each agent walks independently according to its activity rules. Each agent proceeds to its destination, which is defined by the user in advance, using the shortest route. Each agent is affected by obstacles and other agents around it and walks or stops to avoid them according to the situation (Kimura et al. (2009)). SimTread was validated with experimental data on crowd flow. It was shown to be able to reproduce crowd flow and predict the evacuation time for the evaluation of pedestrian movement in architectural plans in both normal and emergency situations. 2. Purpose The aim of this study was to identify the characteristics of a crowd flow passing through ticket gates and derive numerical values to estimate the evacuation time. In addition, the numerical values were examined with SimTread through a comparison of the experimental and simulation results. 3. Method 3.1 Experiment on crowd passing through ticket gates Experiments were carried out on the crowd flow of evacuees passing through the ticket gate of a railway station. In total, 48 subjects were asked to pass through a ticket gate with three passages and four automatic ticket checkers and three passage patterns for which the widths were the same as the sum of the passage widths of the ticket gate (Fig. 1). The subjects approached the ticket gate from various start positions and had various goals (Fig. 2). Two start positions and three goals were set. In one experiment trial, all subjects were given one start position. As experiment conditions, two one-goal cases, two two-goal cases, and one three-goal case combining all three goals were set. 2200 2200
1100
1650 1100
550
Plan (a)
1600
900
Elevation
2000
400
1600
1600
1650
Elevation
Plan (b)
Fig. 1. (a) Dimensions of ticket gate in experiment (unit: mm); (b) dimensions of three passage patterns (unit: mm)
632
Kosuke Fujii and Tomonori Sano / Transportation Research Procedia 2 (2014) 630 – 635
This experiment was simulating an evacuation, so the subjects could pass through the ticket gate without using a paper ticket or IC card. In the experiment, the width of each ticket gate passage was 550 mm. The each passage of the ticket gate was called “lane”. Model boxes made of wood were used to serve as the automatic ticket checkers. 3.2 Determining simulation parameters based on experiment The crowd flow through the ticket gate was simulated with SimTread. The simulation was run with the ticket gate and three passage patterns: 1100, 1650, and 2200 mm. Ten simulation trials were run for each passage pattern. The walking speed of the crowd was defined as the speed of one of the subjects at the head. Thus, the walking speed of the agents was the average of one of the subjects who walked at the head of the crowd. Based on video of the experiment, the constant walking speed of the agents was calculated from the walking speed after the first step. The average speed was calculated at 0.1 s intervals for one subject. The fastest walking speed of the agents was set to 1.23 m/s. 4. Results 4.1 Rules for subjects selecting one of multiple passages in ticket gates in experiment Fig. 3 shows the number of subjects that passed through each of the three lanes in the ticket gate according to the start and goal positions in the experiment. About 16 subjects passed through each of the three lanes in the ticket gate. The number of subjects passing through each lane did not differ based on the start position and goal. In addition, for each line in the initial position, the number of subjects passing through each lane of the ticket gate was counted by the start and goal positions and did not differ significantly. 2400
600
Pass line
2700
Ticket gate or Corridor
Position 2
From a passage to goals
Lane No.
4385
Corridor-passage
Ticket gate
2400
600
Position 2 Pass line
Position 1 Position 1 2400
(a)
600
Line No.
(b)
From a position area to a passage
(c)
Fig. 2. (a) Plan of experiment space; (b) line number of subjects and lane number of ticket gate; (c) examples of experiment
633
Kosuke Fujii and Tomonori Sano / Transportation Research Procedia 2 (2014) 630 – 635
Fig. 4 shows the average number of subjects who passed through each lane and were in each line by the start positions in the experiment. The maximum of standard deviations was 1.18 persons and minimum was 0.1 persons. From a 95% confidence interval (= 1.96 times the standard deviation), the dispersion was small. Consequently, all of the 12 subjects in lines 1 and 4 passed through lanes 1 and 3, respectively, of the ticket gate. Four subjects in lines 2 and 3 passed through lanes 1 and 3, respectively. The remaining eight subjects in lines 2 and 3 passed through lane 2.
Persons
1
1
1
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
Persons
20 18 16 14 12 10 8 6 4 2 0
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
Persons
Persons
Persons
Persons
Persons
Persons
Persons
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
Line 1
1
Line 2
2 3 Lane
Line 3
Line 4
Fig. 3. Number of subjects passing through each lane for different positions and goals
Persons
1
2 3 Lane
Line 2
2 3 Lane
Line 3
2 3 Lane
Persons 1
Line 4
1
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
1
20 18 16 14 12 10 8 6 4 2 0
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
1
Persons 1
20 18 16 14 12 10 8 6 4 2 0
1
Persons
Persons
Persons
Persons
20 18 16 14 12 10 8 6 4 2 0
Persons
Line 1
Persons
20 18 16 14 12 10 8 6 4 2 0
Persons
Line 14
2 3 Lane
Line 1
Line 2
Fig. 4. Average number of subjects passing through each lane for different line positions
1
2 3 Lane
1
2 3 Lane
20 18 16 14 12 10 8 6 4 2 0
Line 3
Line 4
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Kosuke Fujii and Tomonori Sano / Transportation Research Procedia 2 (2014) 630 – 635
4.2 Flow rate and effective width of ticket gate in experiment
1.20 1.00 0.80 0.60
Lane 1
0.40
Lane 2
0.20
Lane 3
0.00 A
ABC
BC
B
A
Position 1
ABC
BC
B
C
Flow rate (person / s)
Flow rate (person / s)
Fig. 5 shows the average flow rates of the subjects passing through each of the three passages in the ticket gate by the start and goal positions. The flow rates for the different start and goal positions differed by 0.1 subject/s or less. The flow rates at each goal position were calculated for each start position. The difference between the maximum and minimum flow rates was 0.03 subject/s for position 1 and 0.05 subject/s for position 2. The differences for each position were small. Fig. 6(a) shows the average flow rates of the 1100, 1650, and 2200 mm passages and the average total flow rates of the ticket gate. The total flow rates were calculated for the ticket gate by one trial (the 48 subjects divided by the time for all of them to pass through the ticket gate by the start and goal positions). In a comparison of the four flow rates, the total flow rate of the ticket gate was between the flow rates of the 1650 and 2200 mm passages. The height of the ticket gate was 900 mm, which was below the subjects’ shoulders. The shoulders of the passing subjects passed over the ticket checker. The width between two ticket checkers was 550 mm. The subjects can be more difficult to pass through passages with the same width and walls that are higher than their shoulders than through the ticket gates. For the ticket checker is less than shoulder height, the passage widths regarded as a passage with walls that are higher than shoulder height should probably not be considered to be 550 mm. Based on the relation between the flow rates of the three passages and their width, a linear regression was found for the flow rate as a function of the width of a passage forming one corridor. These results are shown in Fig. 6(b). The total flow rate through the ticket gate was substituted in the regression equation, and the ticket gate with three passages was found to be equivalent to one passage with a width of about 1870 mm. The estimated width per passage accounting for the subjects’ shoulder movement was about 620 mm.
1.20 1.00 0.80 0.60
1.07
1.07
1.04
1.06
0.98
0.97
A
ABC
BC
B
A
ABC
0.40
0.98
1.00
0.95
BC
B
C
0.20 0.00
Position 2
Position 1
Position 2 Goal by position
Goal by position
(a)
(b)
4.00 3.50 3.00 2.50 2.00 1.50 1.00 0.50 0.00
3.16
3.04
3.55
1.85
Ticket gate
1100mm passage
1650mm passage
Types of passages (a)
2200mm passage
Flow rate流動量（人/s） < Fr > person / s
Flow rate (person / s)
Fig. 5. (a) Average flow rate in each lane for different positions and goals; (b) average flow rate in all lanes for different positions and goals
3.5 3
Fr = 0.257 + 0.00155 W 3.16
2.5 2 1.5 1000
1870
N = 14 r = 0.96 p < 0.0001
1400 1800 2200 通路幅（mm） Width < W > mm (b)
Fig. 6. (a) Average flow rate for different passages; (b) flow rate of passages forming one corridor as a function of their width
635
Frow rate (person / s)
Kosuke Fujii and Tomonori Sano / Transportation Research Procedia 2 (2014) 630 – 635 4.50
Experiment
4.00
SimTread
3.50 3.00 2.50 2.00 1.50
3.25
3.16
3.04
1.00
1.85
2.92
3.29
3.55
3.77
: Max speed (1.23m/s)
1.76
: Lower speed
0.50 0.00 Ticket gate (goal A, experiment)
Ticket gate (experiment)
1100mm passage
1650mm passage
1860mm passage
2200mm passage
Types of passages
(a)
or Avoidance
1860mm passage
: Stop walking (0m/s)
(b)
Fig. 7. (a) Average flow rate for each type of passage in experiment and simulation; (b) examples of simulation
4.3 Verification of flow rate and effective width of ticket gate by simulation Fig. 7(a) shows the average flow rates through the ticket gate and the three passages in the experiment and simulation. In the simulation, the average flow rate was taken from the average of 10 trials for each type of passages. The estimated width of 620 mm per lane taking into account the shoulder movement was found to be the same as the width of one corridor in terms of the flow rate. The average total flow rate through the ticket gate in the case of goal A in the experiment was the same as the flow rate of the 1860 mm passage in the simulation. That of the ticket gate in the case of all goals was lower than that in the case of goal A and the 1860 mm passage, but this difference may be random since the time to pass through was short. The width of 1860 mm was three times 620 mm and thus equivalent to the width of the ticket gate accounting for shoulder movement. Thus, the estimated width of 620 mm per lane is equivalent to the width of one corridor in terms of the flow rate. 5. Conclusion Experiments were performed to elucidate the characteristics of a crowd passing through a ticket gate for the evacuation of a railway station. The experimental results were verified through their reproduction using SimTread. The results were as follows: (1) In the case of a single crowd, the number of evacuees that passed through each of the three passages of the ticket gate did not differ with the start and goal positions. (2) In the case of a single crowd, the relation between the positions of the evacuees in the crowd and the number of evacuees passing through each of the three passages of the ticket gate did not differ with the start and goal positions. (3) In the case of a single crowd, the flow rate in one passage of the ticket gate did not differ by the goal position for each start position. (4) Based on the fact that the ticket checkers were below shoulder height, the width per passage of the ticket gate was equivalent to about 620 mm. (5) The SimTread results validated the estimated width of 620 mm per passage considering the shoulder movement in terms of the flow rate. References Hankin, B.D., Wright, R. A., 1958. Passenger Flow in Subways. Operational Research Quarterly, 9(2), pp.81-88. Older, S. J., 1968. Movement of Pedestrians on Footways in Shopping Streets. Traffic Engineering Control, pp.160-163. Navin, F. P. D, Wheeler, R. J., 1969. Pedestrian Flow Characteristics, Traffic Engineering, pp.30-33. Warren, W. H., Whang, S., 1987. Visual guidance of walking through apertures -body-scaled information for affordances-. Journal of Experimental Psychology: Human Perception and Performance, 13, pp.371-383. Daamen, W., Hoogendoorn, S. P., 2007. “Free Speed Distributions; Based on Empirical Data in Different Traffic Conditions,” Pedestrian and Evacuation Dynamics 2005, pp.13-25. Seer, S., Bauer, D., Brändle, N., Ray, M., 2008. “Estimating pedestrian movement characteristics for crowd control at public transport facilities.” 11th International IEEE Conference on Intelligent Transportation Systems, pp.742-737 Kimura, T., Sano, T., Hayashida, K., Takeichi, N., Minegishi, Y., Yoshida, Y., Watanabe, H., 2009. Representation of crowd in multi-agent model: Development of pedestrian simulation system SimTread. Journal of architecture and planning, 74(636), pp.371-377.