Pedestrian Simulation Research Articles

Game theory model of exit selection in pedestrian evacuation considering visual range and choice firmness**Project supported by the National Natural Science Foundation of China (Grant No. 71904116) and the Fund from the Shanghai Municipal Commission of Science and Technology, China (Grant Nos. 19DZ1209600 and 18DZ1201500).

Exit choice is one of the most important pedestrian behaviors during evacuation. Distance to the exit is a generally recognized factor influencing expected moving time to the exit. Visual range determines how much information a pedestrian can perceive, thus the number of pedestrians within the visual field can be used to estimate waiting time at the exit. Besides, the choice firmness that reflects the degree to which a pedestrian would persist in his/her previous choice of exit is proposed. By integrating game theory into a cellular automata simulation framework, the pedestrian exit choice mechanism is investigated and explicitly modeled in this paper. A systematic analysis of the key factors influencing pedestrian evacuation is conducted, including visual radius and choice firmness of a pedestrian, initial crowd distribution of the room, exit layout as well as exit width. It is found that low choice firmness level can lead to unnatural pedestrian behavior such as wandering, which is adverse to evacuation. The longer the pedestrian’s visual radius, the earlier the pedestrian can determine his/her final selection of the exit. Compared with the scenario where the pedestrians are randomly distributed, pedestrians clustered together in a corner of the room lead to high crowd density and imbalanced use of exits. Furthermore, the exit layout and exit width also have a certain influence on pedestrian evacuation process. The results of this paper may be of benefit to the formulation of behavioral rules in other pedestrian simulation models.

Experimental study on individual risk in crowds based on exerted force and human perceptions

Frequent and intense interactions between individuals inevitably occur in crowd disasters. Previous studies indicate that the primary risk evaluation parameters for individuals in crowds during these interactions are exerted force and its duration. In this study, a series of controlled laboratory experiments simulating static and fluctuant loads were conducted to obtain real-time exerted force data and the associated individual subjective feelings. An individual risk evaluation method is then established to assign a specific individual risk value to each data set of exerted force and its duration according to the individuals’ feelings. This method divides the range of risk value into three zones: comfortable zone, uncomfortable zone and crisis zone. The transition from an uncomfortable zone to crisis zone is not a single numerical value but a range that considers individual differences. The method presented in this paper can assist in developing pedestrian simulation models as well as managing crowd events. Practitioner summary: Accident surveys indicate that casualties and injuries usually occur under a long-term static load or heavy dynamic load. We tested human body extrusion experiments in four conditions, measured the real-time load intensity and duration of the individual’s action on the thoracic cavity during the mutual extrusion process, and an individual risk evaluation method has been established based on the force exerted on the body and its duration to prevent crowd disasters. Abbreviations: NIST: National Institute of Standards and Technology; IREM: individual risk evaluation method; CPR: cardiopulmonary resuscitation

Spatio-Semantic Road Space Modeling for Vehicle–Pedestrian Simulation to Test Automated Driving Systems

Automated driving technologies offer the opportunity to substantially reduce the number of road accidents and fatalities. This requires the development of systems that can handle traffic scenarios more reliable than the human driver. The extreme number of traffic scenarios, though, causes enormous challenges in testing and proving the correct system functioning. Due to its efficiency and reproducibility, the test procedure will involve environment simulations to which the system under test is exposed. A combination of traffic, driving and Vulnerable Road User (VRU) simulation is therefore required for a holistic environment simulation. Since these simulators have different requirements and support various formats, a concept for integrated spatio-semantic road space modeling is proposed in this paper. For this purpose, the established standard OpenDRIVE, which describes road networks with their topology for submicroscopic driving simulation and HD maps, is combined with the internationally used semantic 3D city model standard CityGML. Both standards complement each other, and their combination opens the potentials of both application domains—automotive and 3D GIS. As a result, existing HD maps can now be used by model processing tools, enabling their transformation to the target formats of the respective simulators. Based on this, we demonstrate a distributed environment simulation with the submicroscopic driving simulator Virtual Test Drive and the pedestrian simulator MomenTUM at a sensitive crossing in the city of Ingolstadt. Both simulators are coupled at runtime and the architecture supports the integration of automated driving functions.

Risks to pedestrians in traffic systems with unfamiliar driving rules: a virtual reality approach

In this study, a virtual-reality (VR) pedestrian simulation method was used to evaluate the risks to pedestrians crossing streets in a traffic system with driving rules that were unfamiliar to them. Pedestrians from mainland China (which has a right-side driving (RD) system) and Hong Kong (which has a left-side driving (LD) system) were studied. Significant differences were observed between pedestrians from the different locations in terms of the direction in which the pedestrians habitually first looked before crossing. When exposed to an unfamiliar driving rule (i.e., traffic coming from an inconsistent direction in terms of participants’ habitual driving system), the odds of participants from mainland China making an error in their looking behavior were 2.93 times those when exposed to a familiar driving rule. Road markings and traffic sound did not improve these participants’ looking behavior. The results also show a negative correlation between inattentive looking behavior and time to collision (significant at the 1% level), as these errors lead to a shorter time to collision and increased the risk to pedestrians. The results of this study confirmed the risks for pedestrians traveling to places with unfamiliar driving rules and confirmed the existence of habitual looking behavior, and therefore provide evidence of the need for future studies to improve this problem. These may help decision makers take the risks of pedestrians from different driving rules into consideration in future traffic policymaking or traffic-facility improvements. The use of a VR simulation-based approach in this study provided a safe and controllable way to trial interventions and potential improvements without risking injury to participants, and thus may also be used for similar future studies.

Modeling pedestrian evacuation for near-field tsunamis fusing ALCD and agent-based approaches: A case study of Rincón, PR

Phenomena like tsunamis cannot be predicted, and simulation models are continuously being used in an attempt to understand how individuals will react in an emergency evacuation event. More specifically, pedestrian evacuation simulation can be used to better understand how pedestrians will escape an at-risk area. This work presents a pedestrian evacuation model (PEM) for the municipality of Rincón, Puerto Rico. This PEM provides insight on the vulnerability of Rincón to tsunamis using an iterative, optimization-based algorithm that fuses anisotropic least cost distance (ALCD) and agent-based (AB) approaches. This work advances the ALCD literature by providing a computationally-feasible PEM implementation capable of: (1) strategically initializing the location of pedestrians based on infrastructure and land use considerations, (2) managing individual as well as group-based evacuation, (3) assigning evacuation speeds and responses using probability and machine learning approaches, and (4) penalizing evacuation times using fatigue and reaction delays. The results of this PEM will provide emergency managers with a more realistic depiction of the time to reach safety using a systematic framework. Results, based on the worst-case scenario, indicate that 32.44% of the population in the tsunami evacuation zone (TEZ) would reach safety under 5 min, 41.96% between 5 and 15 min, and 25.60% would require more than 15 min. Unless effective public policy and mitigation strategies take place, the aftermath of a tsunami that inundates the Rincón coastline in less than 5 min could amount to up to 3312 casualties or 68% of the population in the TEZ.

EVALUATING PASSENGER EVACUATION STRATEGIES IN A MASS RAPID TRANSIT STATION IN THAILAND

Rail transit plays a significant role to serve major commuters in many large and congested cities. In Bangkok metropolitan region in Thailand, several mass rapid transit (MRT) lines and stations are currently being constructed and operated. To perform efficient safety and operational performances, the analysis of pedestrian traffic flow within transit stations under normal and emergency circumstances is a crucial step for planning, design, and operations of station facilities. This study focuses on applying the pedestrian traffic simulation to model the characteristics of passengers and then evaluate passenger evacuation strategies in mass rapid transit stations. The pedestrian’s walking behavior and characteristics were observed. Three evacuation strategies were examined including (a) Evacuation to Ground Level; (b) Evacuation to Train; and (c) Evacuation to Track Level. The evacuation times under a given number of evacuate occupants were evaluated, and the bottleneck of evacuation strategies was identified. A case study of Tao Poon mass rapid transit station was carried out. The results showed that the pedestrian traffic simulation technique provides great flexibility in modeling different scenarios in emergency situations and evaluating the dynamic nature of pedestrian flow characteristics. It is also useful to planners, designers, and operators of rail transit systems in practice.

Comparison and Selection of Reconstruction Schemes for Transfer Channels of Zhichun Road Station in Beijing Subway Based on Pedestrian Simulation

As the most critical facility of the rail transit station, the transfer channel’s capacity and efficiency greatly affect the operational efficiency and safety of the transfer station. Due to the uncoordinated network planning and the inaccurate prediction of passenger flow, the current capacity of the transfer station at the peak of the transfer station is seriously insufficient. It is necessary to redesign and rebuild the transfer channel to meet the needs of passengers in the peak period. Taking the Zhichun Road Station of Beijing Subway as an example, this paper uses the Vissim pedestrian simulation software to establish different transfer channel reconstruction schemes due to the problems caused by insufficient capacity of the transfer channel. Based on the actual transfer and facility capabilities, comprehensive considerations are made from the transfer time, transfer distance and reconstruction costs to arrive at the best retrofit solution.CLC number: U291.69

An Artificial Neural Network Framework for Pedestrian Walking Behavior Modeling and Simulation

Movement behavior models of pedestrian agents form the basis of computational crowd simulations. In contemporary research, a large number of models exist. However, there is still no walking behavior model that can address the various influence factors of movement behavior holistically. Thus, we endorse the use of artificial neural networks to develop walking behavior models because machine learning methods can integrate behavioral factors efficiently, automatically, and data-driven. In this paper, we support this approach by providing a framework that describes how to include artificial neural networks into a pedestrian research context. The framework comprises 5 phases: data, replay, training, simulation, and validation. Furthermore, we describe and discuss a prototype of the framework.

A Method for Joint Estimation of Homogeneous Model Parameters and Heterogeneous Desired Speeds

One of the main strengths of microscopic pedestrian simulation models is the ability to explicitly represent the heterogeneity of the pedestrian population. Most pedestrian populations are heterogeneous with respect to the desired speed, and the outputs of microscopic models are naturally sensitive to the desired speed; it has a direct effect on the flow and travel time, thus strongly affecting results that are of interest when applying pedestrian simulation models in practice. An inaccurate desired speed distribution will in most cases lead to inaccurate simulation results. In this paper we propose a method to estimate the desired speed distribution by treating the desired speeds as model parameters to be adjusted in the calibration together with other model parameters. This leads to an optimization problem that is computationally costly to solve for large data sets. We propose a heuristic method to solve this optimization problem by decomposing the original problem in simpler parts that are solved separately. We demonstrate the method on trajectory data from Stockholm central station and analyze the results to conclude that the method is able to produce a plausible desired speed distribution under slightly congested conditions.

Compression of Pedestrian Crowd in Corner Turning Subject experiment-based analysis of walking trajectories

In this study, pedestrian crowd dynamics at corner turns were investigated by analyzing pedestrian trajectories in a subject experiment for building more reliable, general-purpose, pedestrian simulation models. An experiment under laboratory conditions was conducted wherein a pedestrian crowd walked straight for a short distance before turning into a right-angled corner built with partition walls; the opposite sides were unwalled. Trials were performed with different widths and densities of initial participant positions. Finally, the trajectories of the pedestrians were extracted from a video through computer image analysis. The results demonstrated that pedestrian behavior at corner turns depends on lane position, lane distance (from the wall), and crowd density.

Investigating pedestrians’ obstacle avoidance behaviour

Modelling and simulating pedestrian motions are standard ways to investigate crowd dynamics aimed to enhance pedestrians’ safety. Movement of people is affected by interactions with one another and with the physical environment that it may be a worthy line of research. This paper studies the impact of speed on how pedestrians respond to the obstacles (i.e. Obstacles avoidance behaviour). A field experiment was performed in which a group of people were instructed to perform some obstacles avoidance tasks at two levels of normal and high speeds. Trajectories of the participants are extracted from the video recordings for the subsequent intentions:(i) to seek out the impact of total speed, x and yaxis (ii) to observe the impact of the speed on the movement direction, x-axis, (iii) to find out the impact of speed on the lateral direction, y-axis. The results of the experiments could be used to enhance the current pedestrian simulation models.

Pedestrian collision avoidance with a local dynamic goal

We present here a general formalism for equipping simulated pedestrians with an avoidance mechanism. The central idea is to use a short-range target which is adjusted dynamically depending on the environment and thus modulating the desired velocity of the agent. This formulation can be implemented over any type of existing pedestrian model, being force-based or rule-based. As an example, we implement a simple instance of the formulation which is adjusted to reproduce previous reported and available experimental data of collision avoidance in scenarios of low density. The proposed minimal model shows good agreement with the real trajectories and other macroscopic observables.

Historic Neighborhood Design Based on Facility Heatmap and Pedestrian Simulation: Case Study in China

Abstract With the rapid growth of tourism in China, the spatial conflict between tourists and the host community has become a major issue in historic neighborhood design. This study employed big da...

Effect of group behavior on pedestrian choice for vertical walking facilities

Analyzing the characteristics of group behavior, leader-follower model which adopts dynamic group floor field to represent the attraction in a group is used to model pedestrian group behavior. Pedestrian choice model of vertical walking facilities based on support vector machine (SVM) with the effect of group behavior is established. Fusing pedestrian choice model of vertical walking facilities and leader-follower model into a cellular automata (CA)-based pedestrian simulation model, we simulate the pedestrian choice process for vertical walking facilities with the effect of group behavior. The simulation results indicate that with the effect of group behavior, the choice results of some pedestrians are changed, and the efficiency of pedestrians passing is reduced. To some extent, the efficiency of pedestrians passing is improved with the mean distribution of luggage in each group.

Simulation and analysis of pedestrians in the station of urban rail transit

The hall of Wuhan Dazhi road station of urban rail transit is modelled by Anylogic. Based on the data surveyed in the morning peak period of some workday, walking paths of pedestrians are simulated and utilization of equipments is analyzed. To reduce pedestrian waiting time, security checkpoints are added. Then the average passage time going through the station hall is reduced.

PEDESTRIAN SIMULATION OF METRO RAIL TRANSIT (MRT) LINE 7 STATION 1-NORTH AVENUE STATION, QUEZON CITY, PHILIPPINES

Simulation of pedestrian flow represents an advanced approach in modeling and evaluating train stations. In this study, pedestrian simulation was done using the simulation software Simio to assess the passenger capacity of MRT 7 Station 1-North Avenue Station through level of service (LOS), queuing system, and train facility utilization. This paper presents the actual situation inside the train station while predicting the behavior of queuing pedestrians and provides an accurate estimate of the volume-to-capacity ratio of passengersentering the station. The study’s approach debugged the conventional assignments of pedestrians currently used in the field. The constructed three-dimensional building of the North Avenue Station served as framework for the simulation. Sources, sinks, servers, and paths of the software were the main elements of the simulation. Each library was defined by their time usage based on data gathered. Time usages of 1.21 sec. and 240 sec. for sources and sinks, respectively, were used in the simulation. Servers were defined by the train facilities utilizedin the simulation, namely, automatic ticketing machines (TVM) with time usage of 43 seconds, ticketing toll gates with 1.4 seconds, and manual ticketing windows (BOM) with 20 seconds. In addition to the libraries,pathsthat provided the flow, direction, and distribution of pedestrians were calibrated using 10% for TVM users, 35% for BOM users, and 55% for others (regular tickets, beep cards, promo trips) based on data obtained. Simulation results showed that the new proposed plan has a higher passenger capacity than the original plan.

A Framework for Integrating Human Factors in the Early Stages of Ship Design: Application to the Mess Halls of a Surface Combatant

The new F-110 frigates project is currently in the conceptual design and definition phase. General arrangement has to be defined; there are many demands and proposals of changes. One of them is the design of the most crowded areas, the mess halls. The aim of this article is to provide the Spanish Navy Staff with a decision tool that helps in determining the optimal distribution of the future F-110 mess halls. For this purpose, a new "analytical decision maker" model was designed providing advanced statistical methods and computer pedestrian simulations within multicriteria decision-making framework that allows optimizing conceptual designs. To reduce subjectivity, crew movement simulations and statistical methods were added to the multicriteria decision model, thus creating a less-subjective decision tool. A sensitivity analysis was conducted to check the robustness of results. An integrative decision and design approach are necessary for broad acceptance of human factors adoption within naval architecture design. 1. Introduction 1.1. Ship design and human factors Ship design is a complex challenging process that requires the successful coordination of many different disciplines and that necessarily involves trade-offs between competing interests to achieve a balanced result. Hence, ship designers need to understand the complex interaction between different design drivers and their influence on the final solution, always being aware that the cost of rework may become drastically high if errors are found in the later stages of the design.

Pedestrians’ road crossing behaviour in front of automated vehicles: Results from a pedestrian simulation experiment using agent-based modelling

The objective of this research is to explore the relation between personal characteristics of pedestrians and their crossing behaviour in front of an automated vehicle (AV). For this purpose, a simulation experiment was developed using Agent-Based Modelling (ABM) techniques. Sixty participants were asked to cross the road in a virtual environment displayed on a computer screen, allowing to record their crossing behaviour when in the presence of AVs and conventional vehicles (CVs). In some experimental configurations, the AVs communicated their intention to continue or not to continue their trajectories through the use of lights. The ABM allowed controlling the behaviour of the vehicles when interacting with the simulated avatar of the respondents. The subjects of the experiment were also asked to fill in a questionnaire about usual behaviour in traffic, as well as attitudes and risk perceptions toward crossing roads. The questionnaire data were used to estimate individual specific behavioural latent variables by means of principal component analysis which resulted in three main factors named: violations, lapses, and trust in AVs. The results of generalized linear mixed models applied to the data showed that besides the distance from the approaching vehicle and existence of a zebra crossing, pedestrians’ crossing decisions are significantly affected by the participants’ age, familiarity with AVs, the communication between the AV and the pedestrian, and whether the approaching vehicle is an AV. Moreover, the introduction of the latent factors as explanatory variables into the regression models indicated that individual specific characteristics like willingness to take risks and violate traffic rules, and trust in AVs can have additional explanatory power in the crossing decisions.

A study on passengers’ alighting and boarding process at metro platform by computer simulation

Abstract Passengers’ alighting and boarding process in metro stations has attracted increasing research attention since it has significant influence on the platform passenger distribution as well as the train dwell time. In this study, a field survey was firstly performed in a densely populated metro station at downtown area in Hong Kong to observe passengers’ alighting and boarding characteristics and collect sample data. One commonly existing phenomenon is found that boarding passengers start to get aboard even when there are alighting passengers still inside the metro carriage. This is defined as passengers’ non-compliance behaviors in this paper. In addition, time indicators are defined to measure the alighting and boarding efficiency. Then a microscopic pedestrian simulation model based on the Social Force Model is proposed to simulate the passengers’ alighting and boarding patterns at metro platform. The verification result shows the good applicability of the proposed model to simulate the actual situation. Finally, several simulation tests are conducted to explore the impacts that passengers’ non-compliance behaviors have on the alighting and boarding efficiency in different passenger volume conditions. The simulation result shows that higher level of passengers’ non-compliance behaviors leads to longer passenger’s alighting duration and boarding duration, but the influence on the overall transaction time is related to different passenger volume conditions. Thus, metro station facility could apply different alighting and boarding rules in different passenger volume conditions to increase alighting and boarding efficiency.

An HMD-based pedestrian simulator for training and measuring individuals perceptual-motor behaviour in road crossing

Pedestrian simulators are used to evaluate human perception and behaviour in road-crossing. It is, however, needful to ensure that whether the virtual environment used in those systems is in accord...