Pedestrian Movement Characteristics Research Articles

Experimental study on individual and crowd movement features around obstacles with different shape and size

Well-structured pedestrian experiments in a long corridor have been carried out to explore the influence of obstacle shape and size on individual and crowd level pedestrian movement characteristics. Results indicate that for individual pedestrians, the number of right-turning pedestrians and the target drift angle show clear changes with the increase of the obstacle size, while the speed only changes significantly when the obstacle size is greater than 1.5m. For the crowd movement scenarios, a small obstacle can speed up the pedestrian flow, then, with the increase of the obstacle size, the movement time increases. The increase rate has a relation with the obstacle shape. The obstacle shape influence becomes more obvious when the individual and crowd movement scenarios are compared. The results of this paper are expected to provide practical basis for modeling pedestrian under the influence of obstacle.

Pedestrian dynamics on slopes: Empirical analysis of level, uphill, and downhill walking

Pedestrian safety on inclined walking facilities merits greater attention than that on level surfaces. Crowd accidents and domino effects are more likely to occur on slope walkways, especially at high crowd densities, as in the tragic case of the 2022 Itaewon Halloween crowd crush in South Korea. However, experimental investigations of the pedestrian dynamics on slopes with varying inclinations are scarce. In this study, a controlled experiment involving 48 participants was conducted to investigate the differences in pedestrian movement characteristics during level, uphill, and downhill slope walking. A wide range of slope inclinations was considered, namely 0°, 3°, 7°, 12°, 17°, and 22°. The results demonstrated that walking speeds uphill are lower than those on flat terrains, and uphill speeds decrease with increasing inclination. In contrast, increased slope inclinations do not always correspond to reduced downhill speeds. Notably, at inclinations of 3° and 7°, the downhill speed exceeds that of level walking, suggesting that a mild downhill slope can facilitate faster movement. Compared with downhill walking, pedestrians exhibit more lateral motion and significantly lower speeds (p < 0.01) when walking uphill at the same inclination. However, the average flow rate during downhill walking is lower than those observed on flat ground and uphill terrain. This difference may be attributable to the lower pedestrian density during downhill walking to reduce the likelihood of falling. These findings can enhance the understanding of pedestrian dynamics on ramps and have significant implications for the design of safer inclined walking facilities and prevention of potential disasters on such walkways.

Impact of social distancing on disease transmission risk in the context of a pandemic.

Changes in pedestrian dynamics caused by social distancing policies place new demands on pedestrian motion modeling during the pandemic. This study summarizes pedestrian movement characteristics during the pandemic, based on which, the traditional floor-field cellular automata model was improved by introducing two floor fields related to pedestrian density to simulate social distancing in crowded places. Especially, the cumulative density field guides pedestrians in route selection, thereby compensating for the limitation of the previous models in which only local repulsion was considered. By selecting an appropriate combination of parameters, the desired social distancing behavior can be observed. Then, the rationality of our model is verified by the fundamental diagram. Moreover, to assess the influences of social distancing on the risk of disease transmission, we considered both person-person transmission and environment-person transmission. The simulation results show that although social distancing is effective in preventing interpersonal transmission, an increase in environmental transmission may somewhat offset this effect. We also examined the influence of individual motion heterogeneity on infection spread and found that the containment was the best when only patients complied with the social distancing restriction. The trade-off between safety and efficiency associated with social distancing was also initially explored in this study.

A comparative experimental study on the influence of bottleneck width on evacuation characteristics of pedestrian flow in funnel shape bottleneck and normal bottleneck

Previous studies have proposed that increasing bottleneck width help increase evacuation efficiency in normal bottleneck evacuation. However, the effect of funnel shape bottleneck coupled with bottleneck width on evacuation efficiency is still unknown. To improve the understanding of the influence of bottleneck width in funnel shape bottleneck evacuation on the movement characteristics of pedestrians, the funnel shape bottleneck evacuation experiment is carried out in this study. The movement characteristics of pedestrians passing through the funnel shape bottleneck versus the normal bottleneck are compared from the aspects of trajectories, fundamental diagrams, density profiles, speed distribution, flow, time interval, and quiescent time. Logarithmic function fits the relation between density and speed well both for funnel shape bottleneck and for normal bottleneck evacuation. Under the same density, the funnel shape bottleneck allows pedestrians to move faster than the normal bottleneck. For the same bottleneck width, the density in the funnel shape bottleneck is smaller than that in the normal bottleneck. The flow increases linearly with the increasing bottleneck width both in funnel shape bottleneck and in the normal bottleneck. When the bottleneck width is smaller than 1.31 m, the flow of funnel shape bottleneck is higher than that of the normal bottleneck. The funnel shape bottleneck reduces the occurrence and the lasting time of quiescent behaviors. The evacuation time decreases piecewise linearly with the increasing bottleneck width both for the funnel shape bottleneck and the normal bottleneck. The comparisons reveal that the funnel shape bottleneck increases evacuation efficiency under the smaller bottleneck width. The results obtained in this study describe the difference between the funnel shape bottleneck and the normal bottleneck, which is beneficial to safety managers and pedestrian facilities designers.

Emergency evacuation time model of nuclear power plant pedestrians

The construction of nuclear power plant is usually multi-phase. In the coexisting period of operation and construction, the types of pedestrian in nuclear power plant are complicated. Like Fukushima accident, nuclear power plant accident is dangerous and easy to cause mass panic. In order to improve the efficiency of emergency evacuation in nuclear power plant and accurately obtain the evacuation time of nuclear power plant pedestrians, a pedestrian evacuation time model is established. Firstly, by studying the general layout characteristics of nuclear power plant, nuclear power plant is divided into three areas, protected area, management area and construction area. Secondly, the pedestrian flow movement monitoring data of nuclear power plant are analyzed to obtain the pedestrian movement characteristics and speed-density curves of different locations(facilities) in different areas of the plant, which will provide data support for establishing the pedestrian evacuation time model of nuclear power plant. Thirdly, the evacuation time of nuclear power plant is divided into three parts: pedestrian reaction time, pedestrian walking time and pedestrian waiting time. The evacuation time model of nuclear power plant pedestrian is obtained by analyzing and modeling these three parts respectively. Finally, taking a nuclear power plant as an example, three types of evacuation areas are set up according to the layout characteristics and construction status of nuclear power plant. The model was used to calculate the evacuation time of different types of areas. Based on multi-agent pedestrian flow simulation method, emergency pedestrian flow simulation of three types of evacuation areas is obtained. The results of the model are compared with the simulation results, and it is found that the model has good matching in different nuclear power plant areas, which verifies the rationality and accuracy of the model.

Application of Machine Learning Techniques for Predicting Potential Vehicle-to-Pedestrian Collisions in Virtual Reality Scenarios

The definition of pedestrian behavior when crossing the street and facing potential collision situations is crucial for the design of new Autonomous Emergency Braking systems (AEB) in commercial vehicles. To this end, this article proposes the generation of classification models through the deployment of machine learning techniques that can predict whether there will be a collision depending on the type of reaction, the lane where it occurs, the visual acuity the level of attention, and consider the most relevant factors that determine the cognitive and movement characteristics of pedestrians. Thereby, the inclusion of this type of model in the decision-making algorithm of the AEB system allows for modulating its response. For this purpose, relevant information on pedestrian behavior is obtained through experiments made in an ad-hoc, Virtual Reality (VR) environment, using a portable backpack system in three urban scenarios with different characteristics. Database generation, feature selection, and k-fold cross-validation generate the inputs to the supervised learning models. A subsequent analysis of the accuracy, optimization, error measurement, variable importance, and classification capability is conducted. The tree-based models provide more balanced results for the performance metrics (with higher accuracy for the single decision tree case) and are more easily interpretable and adaptable to the algorithm. From them it is deduced the high importance of the reaction type and the relative position where it occurs, coinciding with the high significance of these factors in the analyzed collisions.

Experimental study on movement characteristics of pedestrians with different speeds

Crowd evacuation efficiency is related to the gait parameters of individuals. In this study, the gait parameters of individuals with different speeds, including step length, plantar pressure, and offset of barycenter, were recorded using a pressure distribution measurement treadmill. The gait characteristics of pedestrians with different motion states were analyzed. A physical model was built to describe the individual movement. The results showed that the critical speed for individual motion posture from walking to running was 1.4 m s−1, and the gait characteristics of a pedestrian differed significantly between the two motion postures. The step length increment began to decrease rapidly and the offset of the barycenter (front and rear position) began to increase when the speed was more than 1.4 m s−1, and the movement condition of an individual was changed from walking to running at this speed. The plantar pressure increased significantly when the speed of an individual was between 1.4 m s−1 and the speed at which the double support phase disappeared. These findings revealed the variation rules of the movement characteristics of individuals with different speeds, such as the step length, the plantar pressure, and the offset of the barycenter. The step length and the plantar pressure were quantified for the physical model, which could provide a reference for the further research of crowd simulation and the instability risk of individuals.

A kinetic theory model of human crowds accounting for visual attention

The visual attention of pedestrians has been rarely considered in studies of congestion prevention in long-distance passages. This paper proposes a kinetic theory model of human crowds accounting for visual attention to study congestion in long-distance passages. The population is divided into visual attention-shifting pedestrians (VAS pedestrians) and nonvisual attention-shifting pedestrians (non-VAS pedestrians). First, the movement characteristics of all pedestrians are analyzed based on observations and measurements obtained through controlled experiments. Moreover, a pedestrian flow model accounting for visual attention is built to transform the characteristics of pedestrian movement into a mathematical model. Finally, validation is done, and the density and the proportion of VAS pedestrians are selected as congestion warning parameters. Simulations are performed for a subway passage connected to stairs, and the effect of visual attention, the critical thresholds of congestion warning parameters, and the effects of implementing mitigation measures immediately after congestion occurs are assessed. The experimental results show that the movement characteristics of VAS pedestrians and non-VAS pedestrians are different. Simulation results show that the model is effective. Notably, visual attention has an impact on pedestrian movement, and using the density and the proportion of VAS pedestrians as early warning indicators is effective for preventing the occurrence of congestion, as demonstrated by the negative correlation between the two critical thresholds. This description of human groups provides quantitative guidelines for crowd management.

Experimental study on the movement characteristics of individuals through angled corridors with different speeds and directions

Understanding the movement characteristics of pedestrians is essential for the management of mass gatherings. In this work, a series of experiments were conducted to study the movement of individuals through angled corridors with sharp-turn and curved-turn sections. The influence of different angled-corridors on the offset of trajectory, speeds, and the turning point is studied. An inward offset for pedestrians around the turning sections is observed regardless of movement speeds and directions. It is also found that the distance to the turning points (the relative difference between the selected reference points and turning points) in running is greater than that in normal walking. For clockwise and anticlockwise movements, there are no significant differences for different radii when walking. The results can be used as validation bases and behaviour rules for the microscopic pedestrian models.

Evaluating the influence of approaching vehicles on pedestrian’s visual patterns and crossing behaviors at an uncontrolled crosswalk

The visual behaviors and movement characteristics of pedestrians are related to their surrounding potential safety hazards, such as approaching vehicles. This study primarily aimed to investigate the visual patterns and walking behaviors of pedestrians interacting with approaching vehicles. Field experiments were conducted at two uncontrolled crosswalks located at the Cuihua and Yanta roads in Xi’an, China. The visual performance of pedestrians was assessed using the eye tracking system from SensoMotoric Instruments (SMI). Moreover, motion trajectories of the pedestrians and approaching vehicles were obtained using an unmanned aerial vehicle. Subsequently, the visual attributes and movement trajectories of pedestrians and motion trajectories of approaching vehicles were statistically analyzed. The results showed that approaching vehicles distracted the fixation of crossing pedestrians significantly, and occupied 29.5% of the total duration of fixation; that is, pedestrians always directed more fixation points to the approaching vehicles compared to other stimuli. As a vehicle approached, pedestrians’ fixation shifted from other areas of interest to the vehicle. Moreover, an increase in the velocity of the vehicle and a closer distance between pedestrian and the vehicle resulted in an increase in the pedestrians’ duration of fixation on the approaching vehicle, and they implemented more saccades. Furthermore, approaching vehicle’s velocity and distance between pedestrian and approaching vehicle are not significantly associated with pedestrian’s movement attributes. These findings provide insights into the crossing behavior of pedestrians during pedestrian-vehicle interactions, which could assist future researchers and policy makers.

The movement characteristics of pedestrians on a single-file track at the uphill and downhill conditions

Ramps, as very common building structures, are widely used in railway stations, subways, shopping malls and other public places. In order to study the movement characteristics of pedestrians both uphill and downhill, we present a group of single-file movement experiments of pedestrians on a ramp with a 9° slope. It is found that in the free flow state, the average speed uphill and downhill is about 1.1 m s−1, while the average speed on the flat surface is about 1.4 m s−1. As the density increases, the critical densities at which the speed of pedestrians begins to decrease going uphill and downhill are both slightly higher than that on the flat surface. We also propose a step-based model considering different step frequencies and step lengths of pedestrians to simulate the movement on the ramp. Compared with the experimental results, it is shown that the model can reproduce the pedestrian’s walking behavior on the ramp well.

Surrogate-Assisted Fine Particulate Matter Exposure Assessment in an Underground Subway Station.

With the increase in subway travelers, the air quality of underground enclosed spaces at subway stations has attracted much more attention. The study of pollutants exposure assessment, especially fine particulate matter, is important in both pollutant control and metro station design. In this paper, combining pedestrian flow analysis (PFA) and computational fluid dynamics (CFD) simulations, a novel surrogate-assisted particulate matter exposure assessment method is proposed, in which PFA is used to analyze the spatial-temporal movement characteristics of pedestrians to simultaneously consider the location and value of the pedestrian particulate generation source and their exposure streamline to particulate matter; the CFD model is used to analyze the airflow field and particulate matter concentration field in detail. To comprehensively consider the differences in the spatial concentration distribution of particulate matter caused by the time-varying characteristics of the airflow organization state in subway stations, surrogate models reflecting the nonlinear relationship between simulated and measured data are trained to perform accurate pedestrian exposure calculations. The actual measurement data proves the validity of the simulation and calculation methods, and the difference between the calculated and experimental values of the exposure is only about 5%.

Experimental Study on Unidirectional Pedestrian Descending and Ascending Stair With a Fixed Obstacle

Staircase is one of the most essential vertical passageway for pedestrians’ timely evacuation, and has distinct constraint on pedestrians’ movement characteristics when compared with corridors and hallways. During evacuation, temporary obstacles can be observed on stairs, e.g., the abruptly stopped pedestrians or the luggage of pedestrians discarded. It is noticed that studies on the effect of obstacles on pedestrian dynamics mainly focused on planar locomotion, the impact of obstacle on the movement characteristics of pedestrians ascending and descending stairs have not been systematically studied yet. Therefore, in this study, a series of unidirectional pedestrian avoid obstacle movement experiments on staircase under controlled laboratory conditions were performed. The avoidance characteristic of pedestrians is observed from trajectory diagram. Target drift angle towards left and right is further calculated and analyzed. The study found that target drift angle curve occur to relatively large fluctuations to avoid obstacle of a pedestrian rather than not appear to obvious variety to avoid obstacle of a suitcase. Meanwhile, the change trend of target drift angle towards left and right for scenarios S3 and S4 is consistent with results of scenarios S1 and S2. Then, an interesting discovery indicates that the pedestrians will accelerate after passing obstacles whether it is ascending process or descending process. Finally, the obstacle of a pedestrian will accelerate the movement efficiency in ascending process from results of flow rates, but the result is contrary to that of descending process. The systematic experimental data can not only be used for the verification and validation of pedestrian models but also can provide a benchmark for the design of related facilities aiming at improving traffic efficiency.

A framework to evaluate the accessibility, visibility, and intelligibility of green-blue spaces (GBSs) related to pedestrian movement

The planning of green-blue spaces (GBSs) requires considering the pedestrian needs in their walking routes for improving the walking experience. Incorporating the quantitative spatial characteristics of pedestrian movement is essential for pedestrian-friendly urban planning, which however received insufficient attention. Based on the space syntax theory, this study provided three indicators – accessibility, visibility, and intelligibility – to demonstrate the needs of physical access, visual access, and spatial cognition, respectively, in pedestrian movement. Measuring these three indicators, this study exemplified the planning of pedestrian-friendly GBSs using Guangzhou, China as a case study. Spatial design network analysis was used to quantify heterogeneous values of accessibility, visibility, and intelligibility of each GBS throughout the city. Moreover, we used principal component analysis to identify the leading indicators based on their weightings and then to calculate the scores to compare these three aspects of GBSs. The measurements of accessibility, visibility, and intelligibility of each GBS were then averaged across urban administrative districts for evaluating city-scale GBSs. The findings showed that GBSs in central districts were most accessible and visible but least intelligible. In contrast, the overall intelligibility of GBSs throughout the city was the greatest but the visibility was the least. Furthermore, intelligibility, as a more important factor than accessibility and visibility, should be particularly emphasized in future planning of pedestrian-friendly GBSs. Pedestrians from the central districts of Guangzhou city were most satisfied with the walking experience, in terms of accessing to, viewing, and cognizing the GBSs. ‘Yuexiu’, ‘Huadu’, and ‘Nansha’ districts were found as the key places where improved accessibility, visibility, and intelligibility were particularly needed to improve the GBS pedestrian-friendliness throughout the city. In summary, this study not only demonstrated a human-scale GBS evaluation framework for improving the human walking experience but also provided empirical evidence for building pedestrian-friendly green-blue spaces at the city scale.

An experimental study on the movement characteristics of a social group in unidirectional flow

Investigating the pedestrian dynamics can help researchers and managers design pedestrian facilities more reasonably and develop crowd management plans scientifically. Researches show that most pedestrians in the crowd are a social group that has an impact on pedestrian movement characteristics in normal and emergency situations. In this study, a series of unidirectional-flow experiments are carried out to investigate the influence of a two-people social group with a strong relationship on pedestrian flow via changing corridor structures and components of the crowd. It is found that there are significant statistical differences between social groups and individuals at the micro-level, such as personal space. However, such differences are not reflected in the macro level, the presence of the social group has no significant impact on pedestrian dynamics, such as fundamental diagram and movement time. In addition, social groups adjust their relative positions and distance to alleviate the influence of high density.

A Robust Visual-Aided Inertial Navigation Algorithm for Pedestrians

Real-time and robust state estimation for pedestrians is a challenging problem under the satellite denial environment. The zero-velocity-aided foot-mounted inertial navigation system, with the shortcomings of unobservable heading, error accumulation, and poorly adaptable parameters, is a conventional method to estimate the pose relative to a known origin. Visual and inertial fusion is a popular technology for state estimation over the past decades, but it cannot make full use of the movement characteristics of pedestrians. In this paper, we propose a novel visual-aided inertial navigation algorithm for pedestrians, which improves the robustness in the dynamic environment and for multi-motion pedestrians. The algorithm proposed combines the zero-velocity-aided INS with visual odometry to obtain more accurate pose estimation in various environments. And then, the parameters of INS have adjusted adaptively via taking errors between fusion estimation and INS outputs as observers in the factor graphs. We evaluate the performance of our system with real-world experiments. Results are compared with other algorithms to show that the absolute trajectory accuracy in the algorithm proposed has been greatly improved, especially in the dynamic scene and multi-motions trials.

Crowd infection and its prevention strategy in a subway station based on social force model

With the development of society, crowds in public buildings are dense, and the subsequent spread of diseases in places with high population density has attracted widespread attention. In the real situation, the spread of the disease has its complexity, such as the influence of factors such as the movement of people and the intervention of external measures, so it is necessary to further refine the description of the process of infection transmission. Based on the social force model, this article focuses on the impact of microscopic crowd movement in public places on the dynamics of infection. Taking a typical pedestrian exit process in a subway station as an example, we numerically simulated the infection problem among small-scale people in public places, observed the impact of pedestrian movement characteristics on infection transmission, put forward corresponding prevention and control measures, and verified the effectiveness of the measures.

Trajectory distributions: A new description of movement for trajectory prediction

Trajectory prediction is a fundamental and challenging task for numerous applications, such as autonomous driving and intelligent robots. Current works typically treat pedestrian trajectories as a series of 2D point coordinates. However, in real scenarios, the trajectory often exhibits randomness, and has its own probability distribution. Inspired by this observation and other movement characteristics of pedestrians, we propose a simple and intuitive movement description called a trajectory distribution, which maps the coordinates of the pedestrian trajectory to a 2D Gaussian distribution in space. Based on this novel description, we develop a new trajectory prediction method, which we call the social probability method. The method combines trajectory distributions and powerful convolutional recurrent neural networks. Both the input and output of our method are trajectory distributions, which provide the recurrent neural network with sufficient spatial and random information about moving pedestrians. Furthermore, the social probability method extracts spatio-temporal features directly from the new movement description to generate robust and accurate predictions. Experiments on public benchmark datasets show the effectiveness of the proposed method.

Study on the law of vertical evacuation behavior during earthquakes considering social relationship

With the increasing density of people in buildings and complexity of building structures, pedestrians will inevitably be affected by social relationships during vertical evacuation when an earthquake occurs. However, empirical data on the evacuation of pedestrians on stairs in small groups are lacking in the current research. This study aims to analyze and discuss the impact of social relations between pedestrians on the evacuation efficiency and individual behavior after an earthquake. Field experiments were conducted in a university campus with 84 volunteers, and the variables considered were social relationships, speed, and obstacles. After tracking the pedestrian trajectory using the PeTrack software, the interpersonal angle and distance, average speed, time–space relationship, step frequency, offset angle, and pedestrian lateral oscillation were calculated and analyzed. The results show that pedestrian groups with close social relationships have smaller interpersonal angles and distances, and their speed of evacuation is faster than that of pedestrian groups with unfamiliar social relationships. A subjective increase in pedestrian speed increases the evacuation speed and step frequency, whereas road obstacles produce the opposite results. The findings of this study can provide basic data for modeling the vertical evacuation of pedestrian groups as well as a reference for studying the complex characteristics of pedestrian movement during earthquakes.

Dynamic analysis of single-file pedestrian movement with maintaining social distancing in times of pandemic

In order to uncover the characteristics of pedestrian movement under different social distancing measures, we performed a series of single-file experiments considering two types of social distancing measures, namely 1 m and 2 m, and compared them with normal experiments conducted before Covid-19. Firstly, the findings indicate that social distancing measures do make pedestrians keep a greater distance, but there are social distance violations. When the density is greater than 0.23 m−1, pedestrians have more violations under the measure of 2 m than that of 1 m at the same density. Although the typical stop-and-go wave is still observed in social distancing experiments, the increase in social distancing causes pedestrian stopping behavior to occur at lower density, and shortens the density range of the transition from free flow to jammed flow. Moreover, the headway-speed relation under social distancing measures is not a simple horizontal displacement of that under normal conditions. Although their free speeds are similar, the increase in social distancing makes pedestrians need longer adaption time and more space to transform the motion state. Finally, fundamental diagrams are obtained, and the maximum specific flows for social distancing of 1 m and 2 m is 0.62 s−1 and 0.53 s−1, respectively. Apart from the comparison with normal conditions, the comparison with the two-dimensional social distancing experiments shows that pedestrians are more able to comply with the prescribed social distance and stop less in single-file movement. These enrichments offer empirical data of pedestrian movement under different social distancing measures and benefit pedestrian modeling during pandemics.