Examining effect of architectural adjustment on pedestrian crowd flow at bottleneck

• Bottleneck jamming and complex movement can delay pedestrians, foster impatience and pushing, and contribute to stampede risk.Source: §1 · p. 2
• Prior models and non-human experiments suggest architectural adjustments may improve exit outflow, but human studies have largely focused on exit width.Source: §1 · p. 3
• The study uses controlled human experiments to examine how architectural adjustments within a given escape area affect pedestrian outflow and to provide data relevant to evacuation models.Source: §1 · p. 3

2.1 Simulations of crowd egress at bottlenecks

• Simulations predicted that obstacles can improve outflow, but their effects varied with placement, size, and pedestrian behavior; models also disagreed about some exit-position effects.Source: §2.1 · pp. 3–4
• Granular-flow studies likewise found that obstacle position and aperture affect flow, supporting further empirical study of obstacle size and distance from the exit.Source: §2.1 · pp. 4–5

2.2 Empirical data of egress dynamics at bottlenecks

• Human bottleneck experiments commonly studied width, while ethical and safety constraints limited human studies to non-panic conditions; non-human experiments examined obstacle effects under stress or panic.Source: §2.2 · p. 5
• Prior organism studies found that obstacle and exit-position effects can depend on configuration, but had not systematically tested both factors together with human participants.Source: §2.2 · pp. 5–6

3.1.1 Experimental setup

• The setup varied middle versus corner exits, obstacle presence, column diameters of 60 or 100 cm, and distances of 60, 80, or 100 cm from the exit.Source: §3.1.1 · pp. 6–7

3.1.2 Participants

• The 50 student volunteers performed rational, non-pushing trials; real panic behavior was excluded for ethical and safety reasons.Source: §3.1.1 · p. 7, §3.1.2 · p. 9

3.1.1 Experimental setup

• 84 runs covered 14 exit-and-obstacle setups, two desired-speed levels, and three repetitions, with participant locations randomized between repetitions.Source: §3.1.1 · p. 7

3.1.3 Experimental procedure

• Before each repetition, coaches randomized participant positions; participants were told their speed and destination but not the study aims, and rested between repetitions.Source: §3.1.3 · pp. 10–11

3.1.4 Data extraction

• PeTrack automatically extracted trajectories from 25-fps videos, and exit line-crossing times were used to derive time headways.Source: §3.1.4 · p. 11, Figure 2 · p. 12

3.2.1 Total evacuation time and mean time headway

• Evacuation timing is anchored to passage at the measuring segment, with the first and last passage times and the pedestrian count specified.These quantities define the timing basis for total evacuation time and mean time headway.Source: §3.2.1 · p. 12

3.2.2 Definition of flow

• Exit flow is the number of pedestrians passing the segment per unit time; mean time headway and exit width are used to derive specific flow rate.The specific flow rate is expressed in pedestrians per second per meter.Source: §3.2.2 · p. 12
• The measures also include relative efficiency (RE) for specific flow rate.Source: §3.2.2 · p. 12

4.1 Exit time and flow

• Setup #11 (corner exit, φ=60 cm, D=100 cm) was best: 19.4% relative efficiency (3.18 Ped/s/m) in normal walking and 32.7% (4.47 Ped/s/m) in slow running.Source: §4.1 · p. 14
• The least efficient designs were #2 (middle, 60 cm obstacle, D=60 cm) at −10.6% relative efficiency in normal walking and #5 (middle, 100 cm obstacle, D=60 cm) at −5.6% in slow running.Source: §4.1 · p. 14
• Corner exits had lower mean headway and higher specific flow and relative efficiency than middle exits under the same obstacle condition.Obstacles were more beneficial at corner exits, and obstacle size and distance affected performance in most tested exit-speed categories.Source: §4.1 · pp. 13–15
• Specific flow was always higher in slow running than normal walking, so the experiments showed faster-is-faster rather than faster-is-slower.The authors note that stronger competitive behavior and greater threat require further verification.Source: §4.1 · p. 15

4.2 Time headway distribution

• As desired speed increased, time-headway dispersion and skewness increased while the median and overall box position decreased slightly.Source: §4.2 · p. 15

4.3 Power–law analysis of time headway

• The fitted power laws estimated α and the lower bound min Δt, and all experiment datasets passed the Kolmogorov–Smirnov goodness-of-fit tests.Source: §4.3 · p. 17
• Layouts with better outflow, such as corner exits, had higher power-law exponent α values than less efficient layouts.The authors interpret higher α as indicating a better egress state and lower likelihood of long clogs.Source: §4.3 · p. 17

5. Discussion and Conclusion

• 3.18±0.34 Ped/s/m was measured with a corner exit and a 60 cm column 100 cm away, versus 2.63 ± 0.20 Ped/s/m with a middle-wall exit.A 60 cm column 60 cm from a middle exit yielded 2.57±0.09 Ped/s/m, equal to the obstacle-free middle exit; obstacle performance depended on size and location.Source: §5 · p. 19
• Columns may stabilize flow and increase throughput, but can reduce architectural value or exit visibility, and may affect perceptions of door functionality.The paper identifies people’s perceptions of obstacles and door functionality as an area for future study.Source: §5 · p. 19
• Slow running always produced higher flow rates than normal walking, and the experiments showed faster-is-faster rather than faster-is-slower behavior.The authors suggest faster-is-slower may be more prevalent under strong competition and greater threat, warranting further scrutiny.Source: §5 · pp. 19–20
• Higher power-law headway exponents were associated with flows less prone to clogging, supporting exponent-based analysis of clogging events.The authors report that identifying clogging events depends on the exponent α value.Source: §5 · p. 20
• The study’s approach can support bottleneck scenario analysis and simulation-model testing; future work should examine merging or diverging corridors and stairs.The authors also recommend further study of similarities and differences across biological entities to inform crowd-safety design.Source: §5 · p. 20