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A macroscopic passenger flow simulation model based on system dynamics is proposed in this paper. It considers the key factors influencing the dynamics of passenger flow from a holistic perspective of the stations and then models the dynamic change in the number of passengers. Firstly, the transmission of passenger flow for a general many-to-many relation between nodes are presented. When the sum of sending capacities heading for a downstream node is less than the receiving capacity of this node, the aggregation of stranded passengers will form the queuing part of the node. The results coming from a passenger flow simulation of a subway station in Beijing show that the proposed model performs well by comparing it with the real data. It can be applied to describe the dynamic change in the number of passengers and the level of service for the facilities. [ABSTRACT FROM AUTHOR]

An analytical model is proposed to simulate the passenger flow in a subway station using the ordinary differential equation with the average passenger density in the facilities as the state variable. In order to realize the well-organized inbound process, a linear programming-based feedback control model (LFCM) is proposed to compute the optimal feedback passenger inflows of various facilities and velocities to improve the level of service. In order to deal with the unsolvable LFCM, which is caused by the cyclic operation characteristic of a subway station, a network-switch mechanism is incorporated to the LFCM to improve the performance of control model. Finally, a small numerical example is used to illustrate the features of our proposed model. [ABSTRACT FROM AUTHOR]

The normal operation of a integrated hub station is of great significance for the safe operation of the entire city's transportation network. Accurately monitoring the passenger flow operation status of the station is the fundamental basis for achieving scientific management and control of passenger flow. In response to the urgent need for accurate and real-time detection of passenger flow in station passageways, a Yolov7-based improved Deep-Sort algorithm is proposed to detect and track bi-directional passenger flow in the passageways of integrated hub stations. Based on the Yolov7 detection algorithm, the SimAM attention mechanism was introduced to improve the accuracy of detecting passenger flow in the passageways. On the basis of the Deep-Sort tracking algorithm, the Kalman Filter (KF) method was optimized to make the tracking box of the target more accurate. Meanwhile, the Fast-ReID method was used to improve the long-term tracking of targets, thereby improving the value of IDF1. This algorithm can help to achieve real-time and accurate detection and tracking of bi-directional passenger flow in station passageways. In the event of an abnormal situation, the station staff can react rapidly to improve the station's operational safety. [ABSTRACT FROM AUTHOR]

Corridor with corner may be the potential bottleneck in subway station, and walking behavior of passengers around corner is random. In this study, walking process of passenger around corner is divided into five phases according to field survey, i.e., pre-turning straight-going, ready-turning, turning, distance-adjusting and post-turning straight-going. An advanced social force model is proposed to model the turning behavior of passenger around corner, taking visual angle, walking preference and steering force into consideration. To improve walking efficiency, the influences of geometry of facility, walking preference of passengers and arrival rate of passenger flow are investigated. Results show when angle of corner is less than 120°, the walking speed slows down sharply and walking time extends. To improve the walking efficiency, passengers can be guided to walk in lines orderly. The maximum of throughput can be obtained with proper arrival rate. Once the volume of passengers exceeds the facility capacity, effects of "stop-and-go" and "faster is slower" will occur around corner. • Analyzing and demonstrating the walking process of passengers around corner. • Modeling movement of turning passengers with advanced social force model. • Verifying the proposed model with controlled experiments. • Quantifying arrival rate and corner angle influencing on walking efficiency. [ABSTRACT FROM AUTHOR]

With the widespread implementation of smart cards and with more travel details being recorded, travel patterns can be studied more precisely and deeply. Although considerable attention has been paid to travel patterns, the relationship between travel patterns and the functional structure of a city is yet to be well understood. In this research, we study this relationship by analysing metro passenger trip data (in Beijing and Shenzhen in China and London in the United Kingdom), and we present two unprecedented findings. First, through averaging, a linear relationship is found to exist between individual travel distance and the distance between the origin and the city centre. The underlying mechanism is a travel pattern we call “ring aggregation”, i.e., the daily movement of city passengers is aggregated into a ring (with approximately equal distances to the city centre). Then, for commuting trips, the daily travel pattern can be regarded as switching between the outer residential ring and the inner work ring. Second, this linear relationship and the ring aggregation pattern seem to be exclusive characteristics of metro systems (and may also fit other moderate- and long-distance transportation modes) but do not apply to short-distance transportation modes, such as bicycles and taxis. This finding implies that the ring aggregation pattern is a product of the relationship between travel patterns and the city functional structure at a large scope. [ABSTRACT FROM AUTHOR]

Turning junction of subway station is bottleneck being prone to congestion. Speeds of passengers fluctuate in these zones, which will diminish walking efficiency of the passengers and level of service (LOS) of facility. This paper explores the correlation between junction width and walking efficiency of passengers in subway station. Firstly, walking trajectories of passengers at junctions are abstracted from video footages with object detection and tracking algorithm. The parameters of walking behaviors of passengers in conditions with various junction widths are measured. With the calibrated turning social force model (TSFM), walking processes of passengers are simulated, and the optimal widths of junctions are estimated. Results show that the farther away from the inner turning boundary edge (TBE) is, the earlier the individual starts to turn. When junction width is more than 3 m, the walking efficiency will not be higher with junction widening during peak hours. The optimal width of junction is 5.41 m in the passenger-merging scenario with mean arrival rate of 1.67 ped ⋅ s−1. • Abstracting passengers' trajectories based on deep learning algorithm. • Turning trajectory is symmetrical to the turning center. • Exploring the correlation between junction width and walking efficiency. • Turning angular speed of passenger is calibrated to be 29.6 degree/s. • In merging flow scenario with 1.67 ped/s, the passage should be about 5.41 m wide. [ABSTRACT FROM AUTHOR]

As bottlenecks of walking facilities in subway stations, merging passages are prone to congestion when passengers walk and evacuate under daily operation and emergency conditions. The general social force model (SFM) can accurately reproduce the self-organization phenomena of passenger crowds, such as the strip and lane formation. However, the SFM cannot model the overtaking behaviors of individuals who try to avoid collisions with the preceding walkers. To depict the walking behaviors of passengers in merging passages, the SFM is improved by considering the overtaking behaviors of passengers (OSFM) in this paper. Firstly, the trajectories of heterogeneous passengers are abstracted from video footages including the processes of overtaking behaviors. Next, the principle of overtaking, which leads passenger to detour with the shortest route and avoid colliding with the preceding passenger, is put forward to reproduce the overtaking processes of heterogeneous passengers in merging passages. The OSFM is verified to be more accurate than the social force model with only a centripetal force appended (ISFM). Then, the probability of overtaking behavior is estimated based on analysis of the simulation scenarios with various population densities. Finally, some simulation experiments of heterogeneous passengers with different arrival intervals in the merging passages are conducted based on the OSFM. The results show that when population density is below 0.08 ped/m2 or exceeds 1.56 ped/m2, the overtaking behavior scarcely occurs, but when the density is in the range of 0.25–0.4 ped/m2, the overtaking behaviors are mostly likely to occur. The probability of overtaking behavior will decrease with the density increasing when the density exceeds 0.4 ped/m2. What is​ more, the total passing time and walking speeds are more sensitive to the change of layouts of merging passages when the arrival interval of passengers obeys exponential distribution. • Examining the correlation between overtaking probability and population density. • Exploring the walking efficiency of heterogeneous passengers in merging passage. • Overtaking behavior mainly occurs in the density range of 0.25–0.4 ped/m2. • Passing time and walking speeds are sensitive to the change of junction layouts. [ABSTRACT FROM AUTHOR]