Investigating the Dynamics of Pedestrian Flow through Different Transition Bottlenecks
3. Results and Discussions
Captured by 12 digital cameras, the motion information of pedestrians was obtained and analyzed, including pedestrian coordinates (x, y) and transit time (t). Based on these data, the average speed, motion trajectory, and density of pedestrians within the bottlenecks were calculated. In this experiment, the pedestrian efficiencies of three bottleneck types (right-angle, straight, and curved) were evaluated from the recorded pedestrian data. First, the results were obtained from time-spent comparisons among single pedestrians and whole pedestrian systems in the three bottlenecks. Then, the pedestrians’ speed in three bottlenecks was calculated and compared based on the pedestrians’ coordinate data. Finally, the trajectory of pedestrians at bottleneck corridors was reproduced, and the concept of pedestrian neighbors was defined using the triangulation principle. On this basis, Voronoi diagrams were drawn, and the pedestrian densities of three bottlenecks were obtained. In general, the operational efficiency of bottlenecks can be well assessed by comparing the time spent, speeds, and densities of pedestrians.
3.1. Passing Time in Bottleneck Corridors
Obviously, the efficiency of the right-angle bottleneck might be the highest when a single pedestrian is processed, but its passing speed dropped significantly as the pedestrian flow increased. Thus, it was not efficient when a large number of pedestrians were processed. Conversely, when dealing with a single pedestrian, the performance of the curve bottleneck was not outstanding, but with the increasing pedestrian flow, especially when the crowd barrier was formed, the processing speed of the curve bottleneck was insignificantly affected by the crowd barrier. It can be more suitable for hubs to handle heavy pedestrian traffic and reduce pedestrian pressure.
3.2. Pedestrian Speed in Bottleneck Corridors
Speed is the key factor that directly reflects pedestrian movement. A higher walking speed indicates better performance in the bottleneck, meaning that more pedestrians can be evacuated in a shorter period. To study the running capacity of different bottleneck corridors during the experiment, pedestrians were considered crowded when their walking speed was zero or close to it. By observing pedestrian behavior, we were able to analyze their movement capacities. However, we excluded the first 2 m of pedestrian movement, as this is the start-up phase, and focused on the subsequent processing after the pedestrian’s response and start-up time were confirmed.
3.2.1. Speed Distribution of Crowds
Pedestrians upstream and downstream of the bottleneck are highly different in terms of their pedestrian motion characteristics. When analyzing the characteristics of pedestrians in the bottleneck corridor, the overall process was represented by a single characteristic image, which may cause large errors. To better understand how pedestrian speed was affected by the type of bottleneck, we divided the corridor into three regions and studied the pedestrian characteristics separately in different sections to achieve the desired purpose, which will be discussed in detail in the next section.
3.2.2. Lateral Velocity Distribution
The analysis of pedestrian transit time and speed at different bottlenecks revealed varying pedestrian flow efficiency. The curve bottleneck exhibited the highest pedestrian flow efficiency due to the shortest transit time and fastest speed of pedestrians. On the other hand, the right-angle bottleneck had the lowest pedestrian flow efficiency because of the longest transit time and slowest speed of pedestrians. The straight-line bottleneck fell in between these two categories.
Further analysis of the change in the pedestrian average speed at bottleneck areas revealed that the curve bottleneck had the least fluctuation in pedestrian average speed. To delve deep into this finding, the motion trajectories of pedestrians in the bottleneck corridors were analyzed, and a detailed analysis will be presented in the following section.
3.3. Pedestrian Trajectory
3.4. Pedestrian Density Distribution
In this study, more than forty participants were divided into three groups to study pedestrian dynamic behaviors in different types of bottlenecks. Participants in each group were instructed to walk at a predefined speed through a right-angle bottleneck, straight bottleneck, and curve bottleneck, respectively. The efficiency of the bottlenecks was evaluated based on four indicators, namely, pedestrian time spent, speeds, trajectories, and densities. The results indicated that pedestrians were guided by the bottleneck structures, leading to the formation of self-organized patterns in the bottleneck corridors. Particularly, the curve bottleneck proved to be the most effective among the three types, with a notable reduction in pedestrian density, an increase in pedestrian speed, and a shorter time spent by pedestrians, especially at a pedestrian rate of 0.5–1.25 people/s. Therefore, the curve bottleneck can be set at the traffic bottleneck to relieve the traffic pressure at the pedestrian traffic hub, effectively solve the congestion phenomenon, and avoid stampede accidents to the greatest extent.
To be practical for traffic design, our proposed methodology should be efficient enough for real-time implementation. Unfortunately, empirical evaluation is not feasible owing to the unavailability of a voluminous trajectory database. In this experiment, we only explored the influence of bottleneck types on pedestrian flow efficiency. However, various interaction behaviors between pedestrians may also impact a bottleneck’s ability to handle them. Therefore, future research should analyze the impact of bottlenecks on pedestrian flow efficiency in conjunction with their interaction behaviors to garner more comprehensive insights.
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