Pedestrian Simulation Research Articles

Static floor field construction and fine discrete cellular automaton model: Algorithms, simulations and insights

While cellular automaton (CA) models have a broad range of applications in the field of pedestrian dynamics, there are still three significant issues (the efficient and accurate construction of the static floor field (SFF), the insufficient simulation accuracy, and the discretization effect) that have not been resolved or fully clarified yet. This work aims to tackle these challenges. First, a novel approximate algorithm that resolves the dilemma between accuracy and efficiency is proposed to construct the SFF, based on which the static navigation field is created by the proposed method. Then, a novel fine discrete CA model based on the desired direction is developed to capture the locomotion movement behaviour. The novel SFF construction algorithm and locomotion movement model are (theoretically and/or numerically) validated and compared to the state-of-the-art approaches in manifold scenarios. Later on, systematic simulation analyses are conducted to investigate the discretization effect at the micro and macro levels. The assessment metrics show that the performance of the proposed algorithm and model is superior over that of the state-of-the-art approaches. The proposed model can resolve the well-known diagonal movement artefact in the existing CA models and reproduce crowd movement and self-organized lane formation observed empirically. It is found that the non-isotropic SFF results in significantly biased and unrealistic evacuation movement. Moreover, the discretization degree is found to significantly affect the individual and crowd movement simulation outcomes, and the magnitude and direction of its effect depend on the used model and the setup of the scenarios. The proposed algorithm and model are promising tools in pedestrian modelling and simulation. The findings provide fresh insights into the development and application of CA models.

Research on Pedestrian Deceleration Behavior Based on Buffer Space

Understanding the specific mechanism of pedestrian deceleration behavior can better provide data support and parameter calibration for pedestrian flow simulation. In this paper, by introducing a buffer space, designed the pedestrians walking single file experiment and field observation, has obtained the pedestrian buffer space data under different speed, speed - buffer space mathematical model is established, the results show that the pedestrian expected speed and size of the buffer space were positively correlated, pedestrian movement normally, their relation can be used on the two lower limit function, said In the running state, it can be represented by a linear function.

Research on Features of Pedestrians Using Smartphones at Transit Stations Based on Social Force Model

The smartphone has become nearly indispensable in people’s daily lives. Prevalent smartphone usage can be observed on various occasions, even during walking. However, pedestrians’ perception of their surroundings may decline because they are absorbed by using the smartphone. The behavior of pedestrians using smartphones while walking at transit stations can be viewed as disturbance to pedestrian flows, thereby reducing the efficiency of station operation or even creating safety problems. This study seeks to describe such behavioral features mathematically and provide relevant implications for transit station design. Based on the social force model, the parameters reflecting the effect of smartphone usage on the perceived driving and repulsive forces are added and calibrated. By extracting trajectory data from the videos filmed in the field, the genetic algorithm is employed for the calibration process to minimize the gaps between the actual and projected trajectories. Two sets of parameter settings, for pedestrians with and without using smartphones, are determined and further applied to microscopic pedestrian simulation for a transfer station of the metro system in Taipei, Taiwan. The results indicate that pedestrians using smartphones are more prone to being affected by other pedestrians, revealing that their velocities are relatively unstable, while they need longer relaxation time to attain their desired walking statuses. The simulation results also visualize the potential bottlenecks in the station, where smartphone users may become obstacles to other pedestrians and increase the congestion level, highlighting the importance of incorporating the behavior modeling of pedestrians using smartphones into transit station design.

Influence of rotation on pedestrian flow considering bipedal features: Modeling using a fine discrete floor field cellular automaton

Previous studies assume pedestrians rotate with a single axis (often the geometric center of agents in simulation) for simple implementation, which ignores the asymmetry and bipedal features of pedestrian behavior. Therefore, for a higher level of simulation realism, we propose a floor field cellular automaton simulating the rotation with a dual-axis considering bipedal features. Validated by the experimental results, the simulation of pedestrians with the dual-axis rotation fits well with the empirical data, much better than the center-axis rotation. Then, we investigated the influence of rotation on the pedestrian flow in three typical scenarios where one could frequently observe the rotation behavior. The findings reveal that the rotation behaviors significantly influence the crowd phenomena of pedestrians, including the travel and flow efficiency, the shape of arching and trajectories of the crowd, and the lane formation. The pedestrians with the dual-axis rotation flow fluently and efficiently when passing through a bottleneck or a crowd: (1) in the case of single-exit room evacuation, the dual-axis rotation improves the efficiency by 5%–150%; (2) in the case of unidirectional flow in the L-shaped passage, the improved efficiency by the dual-axis rotation is about 30%; (3) in the counter flow, the dual-axis rotation greatly relieves the unrealistic congestion.

Evaluation of Metro Station Design in Terms of Normal Operation and Emergency Evacuation Scenarios with 3D Simulation Software

Yaya simülasyonu teknolojilerinin mimarlık ve şehir planlama disiplinlerinde kullanımı yeni bir kavram olmamakla birlikte; makine öğrenmesi tabanlı, insan davranışlarına benzer sonuçlar veren, ajan bazlı, gerçekçiliği ve geçerliliği bilimsel olarak ispatlanmış üç boyutlu simülasyon yazılımları son yıllarda ortaya çıkmışlardır. Bu yazılımlar, özellikle kalabalık ve karmaşık mekanlarda ortaya çıkabilecek sirkülasyon ve acil durum tahliye problemlerinin henüz tasarım aşamasındayken görülmesine olanak sağlamakta; bu sayede yapı inşa edilmeden önce projede gerekli revizyonların gerçekleştirilmesine imkan vermektedir. Ulusal ve uluslararası standartlar doğrultusunda gerçekleştirilen bu çalışmanın amacı, güncel simülasyon teknolojilerinin yapılara ilişkin normal işletme ve acil durum tahliye senaryolarının değerlendirilmesinde kullanımını örnek olarak seçilen gerçek bir metro istasyonu projesi üzerinden incelemektir. Seçilen raylı sistem hattındaki istasyona özgü yolcu yüklerinin bulunması amacıyla klasik elle hesaplama yöntemleri kullanılmış, ortaya çıkan değerler Massmotion yazılımına aktarılarak mekânsal kapasite analizleri gerçekleştirilmiş ve istasyonun tüm katlarına ilişkin hizmet seviyeleri bulunmuştur. Sonuç olarak metro istasyonunun normal işletme ve acil durum tahliye senaryolarının gereksinimlerini karşılayıp karşılamayacağı test edilmiş, ortaya çıkan sonuçlar çalışma kapsamında verilmiştir.

An experimental study on evacuation dynamics including individuals with simulated disabilities

This paper aims to measure the effect of individuals with simulated disabilities on evacuation processes in a room with an exit through a controlled experiment. A total of 60 individuals participated in the experiment. There are three mixed ratios (i.e., 0%, 5% and 10%) of users of two mobility aids (i.e., wheelchair users and pedestrians on crutches simulated by non-disabled pedestrians using auxiliaries). Video recordings and the Mean-shift algorithm are employed to extract and track pedestrians’ trajectories. Evacuation time, speed, evacuation sequence and specific flow are analyzed according to the trajectories. It is discovered that compared with tests without individuals with simulated disabilities, evacuation time in tests with simulated wheelchair users and pedestrians on crutches increases, while the average instantaneous speed and specific flow decrease. The spatial distribution obtained by the Nearest-neighbor analysis suggests that congestion near the exit formed slower in tests with individuals with simulated disabilities. It is found that compared with tests without individuals with simulated disabilities, crowd danger is higher in the tests involving individuals with simulated disabilities, especially with simulated wheelchair users. It is hoped that this study will be helpful in crowd management involving individuals with disabilities.

Data assimilation and agent-based modelling: towards the incorporation of categorical agent parameters.

This paper explores the use of a particle filter-a data assimilation method-to incorporate real-time data into an agent-based model. We apply the method to a simulation of real pedestrians moving through the concourse of Grand Central Terminal in New York City (USA). The results show that the particle filter does not perform well due to (i) the unpredictable behaviour of some pedestrians and (ii) because the filter does not optimise the categorical agent parameters that are characteristic of this type of model. This problem only arises because the experiments use real-world pedestrian movement data, rather than simulated, hypothetical data, as is more common. We point to a potential solution that involves resampling some of the variables in a particle, such as the locations of the agents in space, but keeps other variables such as the agents' choice of destination. This research illustrates the importance of including real-world data and provides a proof of concept for the application of an improved particle filter to an agent-based model. The obstacles and solutions discussed have important implications for future work that is focused on building large-scale real-time agent-based models.

Development of a Method for Evaluating Social Distancing Situations on Urban Streets during a Pandemic

In the New Normal era of “Living with COVID-19”, we need a measure of the safety of street spaces. Social distancing during a pandemic is considered an effective safety measure, but the current binary threshold approach to social distancing is clearly inadequate for evaluating and monitoring the risk of infection on urban streets. This study is to propose a social distancing indicator that can quantitatively evaluate the level of exposure to viral infection for pedestrians using urban streets during a pandemic, and to develop a statistical model to estimate the proposed indicator from simulations of pedestrian activity on urban streets. We assumed that the risk of infection on urban streets has a direct relationship with distance between pedestrians. The social distancing indicator was based largely on the findings of past studies. We developed a statistical model to relate the proposed indicator to three other explanatory variables: pedestrian density, clumpiness, and directional heterogeneity. We used pedestrian simulation to generate the raw data for these explanatory variables. The social distancing indicator demonstrated a statistically significant relationship with input variables and can be used to evaluate pedestrians’ social distancing on urban streets. We measured the relationship between different levels of pedestrian density, clumpiness, and directional heterogeneity and related the results to the potential level of exposure to viral infection. Health agencies can use the findings to develop appropriate policies for monitoring and improving the social distance between pedestrians on urban streets during a pandemic.

Are socially-aware trajectory prediction models really socially-aware?

Our transportation field has recently witnessed an arms race of neural network-based trajectory predictors. While these predictors are at the core of many applications such as autonomous navigation or pedestrian flow simulations, their adversarial robustness has not been carefully studied. In this paper, we introduce a socially-attended attack to assess the social understanding of prediction models in terms of collision avoidance. An attack is a small yet carefully-crafted perturbations to fail predictors. Technically, we define collision as a failure mode of the output, and propose hard- and soft-attention mechanisms to guide our attack. Thanks to our attack, we shed light on the limitations of the current models in terms of their social understanding. We demonstrate the strengths of our method on the recent trajectory prediction models. Finally, we show that our attack can be employed to increase the social understanding of state-of-the-art models. The code is available at https://s-attack.github.io/.

A Framework of Community Pedestrian Network Design Based on Urban Network Analysis

Community is the foundation of modern cities, where urban residents spend most of their lifetime. Effective and healthy community design plays a vital role in improving residents’ living quality. Pedestrian network is an indispensable element in the community. Successful pedestrian network design can help the residents be healthy both physically and mentally, build the awareness of “Go Green” for the society, and finally contribute to low-carbon and green cities. This paper proposes a community pedestrian network design method based on Urban Network Analysis with the help of the Rhino software. A case study of a typical community in Guangzhou, China was implemented, specifying the steps of the proposed method. The findings presented include the features of the citizens and the accessibilities of the neighbors that are obtained from the community pedestrian network simulation. The limitation and scalability of this method was discussed. The proposed method can be essential to designing healthy and sustainable communities.

Macro-level literature analysis on pedestrian safety: Bibliometric overview, conceptual frames, and trends

Due to the high volume of documents in the pedestrian safety field, the current study conducts a systematic bibliometric analysis on the researches published before October 3, 2021, based on the science-mapping approach. Science mapping enables us to present a broad picture and comprehensive review of a significant number of documents using co-citation, bibliographic coupling, collaboration, and co-word analysis. To this end, a dataset of 6311 pedestrian safety papers was collected from the Web of Science Core Collection database. First, a descriptive analysis was carried out, covering whole yearly publications, most-cited papers, and most-productive authors, as well as sources, affiliations, and countries. In the next steps, science mapping was implemented to clarify the social, intellectual, and conceptual structures of pedestrian-safety research using the VOSviewer and Bibliometrix R-package tools. Remarkably, based on intellectual structure, pedestrian safety demonstrated an association with seven research areas: “Pedestrian crash frequency models”, “Pedestrian injury severity crash models”, “Traffic engineering measures in pedestrians’ safety”, “Global reports around pedestrian accident epidemiology”, “Effect of age and gender on pedestrians’ behavior”, “Distraction of pedestrians”, and “Pedestrian crowd dynamics and evacuation”. Moreover, according to conceptual structure, five major research fronts were found to be relevant, namely “Collision avoidance and intelligent transportation systems (ITS)”, “Epidemiological studies of pedestrian injury and prevention”, “Pedestrian road crossing and behavioral factors”, “Pedestrian flow simulation”, and “Walkable environment and pedestrian safety”. Finally, “autonomous vehicle”, “pedestrian detection”, and “collision avoidance” themes were identified as having the greatest centrality and development degrees in recent years.

Simulation of adult-child matching behavior: A case study of primary school in Linyi city, China

Pedestrian evacuation at the gate of primary school after school is always a tricky question bothering us. In order to improve the safety and efficiency of pedestrian evacuation at the gate of primary school, adult–child matching behavior after school is analyzed. We propose four adult–child matching strategies considering order or random of adults and children in the matching process. Fusing the matching strategy into a cellular automata (CA)-based pedestrian simulation model and taking the Linyi No. 40 middle school, China as the case study, the adult–child matching behavior is simulated on the platform of MATLAB software. The simulation results indicate that evacuation efficiency of the strategy (adults are orderly distributed in the first waiting area and children are orderly queuing up) reaches the maximum value among the four strategies. Effective matching strategies could reduce pedestrian conflicts. The randomly children and randomly adults are all the negative impacts for evacuation. Orderly evacuation process could reduce pedestrian conflicts. Compared with the randomly children, the effect on evacuation efficiency of the randomly adults is larger. A reasonable number of evacuated pedestrians at a time could improve the whole evacuation efficiency, and we advise the Linyi No. 40 middle school to evacuate three classes at a time.

Pedestrian dynamics in single-file merging flows

Single-file experiments are widely used to investigate pedestrian movement properties. However, most single-file experiments were conducted in a circular channel rather than complex structures. In this paper, we designed single-file merging experiments with different merging angles θ and inflow rates at the entrances of the branch and upstream. We found fundamental diagrams were not affected by the merging angle, but the fundamental diagram after merging (downstream) was different from that before merging (upstream and the branch) at large densities. The flow before merging had a peak value 1.2 ped/s at the density of 0.9 ped/m and the flow after merging increased with the density up to 1.6 ped/m. The function proposed by Weidmann was extended to describe the density–velocity​ relation before merging. Moreover, we found when the branch and upstream inflows at the entrances were large enough, the branch and upstream flows in the corridors would reach a balanced state and were almost equal, and putting a proper frequency of metronome program to control the inflow rate at the entrances can increase the efficiency of the merging flow. The flow in scenario with θ=120° was most efficient considering both Shannon entropy and average time headway. The results can be used to calibrate pedestrian simulation models.

How COVID-19 is Affecting Pedestrian Modeling and Simulation: The Case of Venice

The use of computer-based pedestrian crowd simulations has become crucial in transport planning considering the unprecedented effects of the COVID-19 pandemic on urban mobility. However, there is still a lack of knowledge in relation to the impact of social distancing on crowding, queuing, route choice, and other pedestrian crowd phenomena. In this context, the aim of the current study was to apply the Social Force Model of the pedestrian simulation platform PTV Viswalk to investigate the effects of disruption of social distancing on pedestrian dynamics. First, a descriptive set of metrics and parameters was applied for calibrating the dynamic regulation of interpersonal distances among pedestrians. The plausibility of the proposed social distancing model was then evaluated against the so-called fundamental diagram to calibrate pedestrian volume-delay functions. Finally, the proposed model was integrated into the PTV Visum simulation platform to evaluate the effects of social distancing on large-scale pedestrian route choice. To do so, a macroscopic static model of the city of Venice was developed to test the effectiveness of alternative crowd management strategies related to pedestrian dynamics in a predictive scheme.

Empirical characterisation of agents’ spatial behaviour in pedestrian movement simulation

Route choice behaviour is a key factor in determining pedestrian movement flows throughout the urban space. Agent-based modelling, a simulation paradigm that allows modelling individual behaviour mechanisms to observe the emergence of macro-level patterns, has not employed empirical data regarding route choice behaviour in cities or accommodated heterogeneity. The aim of this paper is to present an empirically based Agent-Based Model (ABM) that accounts for behavioural heterogeneity in pedestrian route choice strategies, to simulate the movement of pedestrians in cities. We designed a questionnaire to observe to what degree people employ salient urban elements (local and global landmarks, regions, and barriers) and road costs (road distance, cumulative angular change) and to empirically characterise the agent behaviour in our ABM. We hypothesised that a heterogeneous ABM configuration based on the construction of agent typologies from empirical data would portray a more plausible picture of pedestrian movement flows than a homogeneous configuration, based on the same data, or a random configuration. The city of Münster (DE) was used as a case study. From a sample of 301 subjects, we obtained six clusters that differed in relation to the role of global elements (distant landmarks, barriers, and regions) and meaningful local elements along the route. The random configuration directed the agents towards natural elements and the streets of the historical centre. The empirically based configurations resulted in lower pedestrian volumes along roads designed for cars (25% decrease) but higher concentrations along the city Promenade and the lake (40% increase); based on our knowledge, we deem these results more plausible. Minor differences were identified between the heterogeneous and homogeneous configurations. These findings indicate that the inclusion of heterogeneity does not make a difference in terms of global patterns. Yet, we demonstrated that simulation models of pedestrian movement in cities should be at least based on empirical data at the average sample-level to inform urban planners about areas prone to high volumes of pedestrians.

A modified heuristics-based model for simulating realistic pedestrian movement behavior

Pedestrian movement simulation models are used in various areas, such as building evacuation, transportation engineering, and safety management of large events. It also provides effective means to uncover underlying mechanisms of collective behaviors. In this work, a modified heuristics-based model is presented. In this model, the potential collisions in the moving process are explicitly considered. Meanwhile, a series of simulations is conducted in two typical scenarios to demonstrate the influence of critical parameters on model performance. It is found that when facing a wide obstacle in a corridor, the larger the visual radius, the earlier the pedestrian starts to make a detour. In addition, when a pedestrian observes a large crowd walking toward him, he chooses to make a detour and moves in the flow in a uniform direction. Furthermore, the model can reproduce the lane formation pedestrian flow phenomena in relatively high-density situations. With the increase of pedestrian visual radius and the weight of potential collision resistance, more stable pedestrian lanes and fewer moving-through-the-counterflow pedestrians can be observed. In terms of model validation, the density-speed relationship of simulation results accords well with that of the published empirical data. Our results demonstrate that the modified heuristics-based model can overcome the deficiency of the original model, and reproduce more realistic pedestrian movement behavior.

Analysis of Toilet Scale of Freeway Service Areas Based on Crowd Gatherings

On fully enclosed freeways, the service area is the only key node for certain crowd activities such as resting, toileting, and dining. In these activities, using the toilet is the most important purpose for people to enter the service area. A reasonable toilet location and size in the service area is the basis for its efficient operation. This study conducts field surveys on several service areas, including Meicun, Tai’an, and Qianxian, through video recording and crowd tracking questionnaires. We summarize and analyze the characteristics of population flow in Chinese freeway service areas. The key data obtained through field surveys are reported, such as the priority and length of stay of customers in the facilities during peak hours at weekends, to analyze the characteristics of pedestrian traffic in the service areas. Finally, based on a large number of pedestrian simulation methods used in studies on the layout of subways and airport facilities, the AnyLogic simulation software is applied to establish a crowd movement model for these areas. The study not only obtained the pedestrian characteristics of the service area but also showed that only changing the location of toilets has no effect on the efficiency of toilet use without changing the level of service, whereas changing the number of toilets has a significant impact on the efficiency. Most importantly, this paper establishes a relationship model between the toilet size of the service area and the service area pedestrians flow; when the toilet seats 266/158/148 people, the maximum flow of people in the service area is about 3,115/2200/2000 p/h, which can provide help for the scale design of the service area.

Collaborating with the crowd

Microscopic agent-based simulations promise the meaningful inclusion of crowd dynamics in planning processes. However, such complex urban issues depend on a multiplicity of criteria. Thus, an isolated model cannot represent the walk of pedestrians meaningfully in planning contexts. This paper reframes crowd simulation as collaborative experimentation and embeds it directly in the design process. Beyond the simulation algorithm, this perspective draws attention to user interactions, interfaces, and visualizations as crucial simulation elements. Through a prototype, we combine an agent-based pedestrian simulation with a hybrid physical–digital interface. Based on this configuration, we explore requirements of the early design stages and accordingly discuss concepts for interaction, simulation, and visualization. The prototype blends user inputs with intuitive design interactions, adapts the simulation process to qualitative and dynamic negotiations, and presents results immediately in the discussed context. Thus, it aligns crowd simulation with contingent collaborations and reveals its potential in the early design stages.

Effect of a Moving Obstacle on Pedestrian Flow Through an Exit

Current studies about moving obstacles mainly focus on uncommon evacuation scenarios, while there lacks researches on common egress scenarios, such as evacuation from an exit. This study aims to prove that pedestrian flow through exit can be improved by the presence of a moving obstacle and investigate the effect of a moving obstacle on regulating pedestrian flow. Unidirectional pedestrian flow simulations based on social force model are conducted to study the influence of a moving obstacle, that is a mobile robot, on the pedestrian flow through an exit. The robot reciprocates parallel to the wall of the exit with a constant speed 0.5m/s, and the gap between the robot and the exit is set to 1.0m. The pedestrians need to obey the rule of avoiding collision with the robot. By comparing the distributions of individual evacuation time with and without a moving obstacle, it is proven that that the average evacuation time can be reduced by a moving obstacle obviously. The moving obstacle can lead to the inhomogeneous distribution of the crowd near the exit by observing the density profiles. Furthermore, the crowd near the exit is classified into four groups according to movement direction (left or right) and position (the left or right part relative to the center of the exit) of the robot. It reveals that the moving obstacle impedes the evacuation of small proportion pedestrians, but promotes the evacuation of the large proportion pedestrians by the analysis on the fundamental diagrams of the four groups.

Physical distance characterization using pedestrian dynamics simulation

In the present work we study how the number of simulated customers (occupancy) affects social distance in an ideal supermarket, considering realistic typical dimensions and processing times (product selection and checkout). From the simulated trajectories we measure social distance events of less than 2 m, and their duration. Among other observables, we define a physical distance coefficient that informs how many events (of a given duration) each agent experiences.