Experimental Analysis of Two-Dimensional Pedestrian Flow in front of the Bottleneck

This contribution presents experimental study of two-dimensional pedestrian flow with the aim to capture the pedestrian behaviour within the cluster formed in front of the bottleneck. Two experiments of passing through a room with one entrance and one exit were arranged according to phase transition study in Ezaki et al. (2012), the inflow rate was regulated to obtain different walking modes. By means of automatic image processing, pedestrians' paths are extracted from camera records to get actual velocity and local density. Macroscopic information is extracted by means of virtual detector and leaving times of pedestrians. The pedestrian's behaviour is evaluated by means of density and velocity. Different approaches of measurement are compared using several fundamental diagrams. Two phases of crowd behaviour have been recognized and the phase transition was described.Comment: In proceedings of Traffic and Granullar Flow 2013, Springe

Parameter estimation for macroscopic pedestrian dynamics models from microscopic data

In this paper we develop a framework for parameter estimation in macroscopic pedestrian models using individual trajectories -- microscopic data. We consider a unidirectional flow of pedestrians in a corridor and assume that the velocity decreases with the average density according to the fundamental diagram. Our model is formed from a coupling between a density dependent stochastic differential equation and a nonlinear partial differential equation for the density, and is hence of McKean--Vlasov type. We discuss identifiability of the parameters appearing in the fundamental diagram from trajectories of individuals, and we introduce optimization and Bayesian methods to perform the identification. We analyze the performance of the developed methodologies in various situations, such as for different in- and outflow conditions, for varying numbers of individual trajectories and for differing channel geometries

ProactiveCrowd: modeling proactive steering behaviours for agent-based crowd simulation

How to realistically model an agent's steering behavior is a critical issue in agent-based crowd simulation. In this work, we investigate some proactive steering strategies for agents to minimize potential collisions. To this end, a behavior-based modeling framework is first introduced to model the process of how humans select and execute a proactive steering strategies in crowded situations and execute the corresponding behavior accordingly. We then propose behavior models for two inter-related proactive steering behaviors, namely gap seeking and following. These behaviors can be frequently observed in real-life scenarios, and they can easily affect overall crowd dynamics. We validate our work by evaluating the simulation results of our model with the real-world data and comparing the performance of our model with that of another state-of-the-art crowd model. The results show that the performance of our model is better or at least comparable to the compared model in terms of the realism at both individual and crowd level

Data archive for exploring pedestrian dynamics and its application in dimensioning of facilities for multidirectional streams

In this paper an overview of an open data archive with data from experiments investigating pedestrian dynamics is presented. As an example of the use of this data the analysis of recently published data about the capacity of crossings is shown

Experimental Study on the Effect of Using Smartphones on Pedestrian Flow in Straight Corridors

With the development of science and technology, smartphones are widely used in people’s daily lives. An interesting phenomenon is that many pedestrians use smartphones while walking in the public places, which not only harm and even kill in some cases, but also affect the pedestrian traffic safety. At present, most studies focus on the pedestrians in the normal state that they don’t use phones while walking. Few research has been done on the pedestrian flow when they use phones. Therefore, the experiment that the pedestrians use phones while walking in straight corridor was conducted to study the movement characteristics and compared with the normal one. From the trajectories, the lane formation can be found in all experiments and the trajectories when they use phones are more chaotic. When pedestrians distract themselves by using phones, they walk more slowly and the flow is lower, leading to the longer egress time to pass the corridor. The distance from the boundary is defined as the shortest distance between the pedestrians and the wall. When they use phones, they try to avoid collision with the wall and walk away from the wall, so the distance is further than the normal one. The nearest pedestrian distance is defined as the nearest distance among all pedestrians. When they use phones, they distract themselves and don’t have enough time to avoid collision with others, so the nearest pedestrians distance is closer than the normal one. Our findings maybe a new insight for pedestrian flow when they distract themselves by using the phones, talking with others and thinking deeply, which can enrich empirical data and contribute to the simulation model

Analysis and Modeling of Pedestrian Walking Behaviors Involving Individuals with Disabilities

The objective of this dissertation was to study walking behaviors of pedestrian groups involving individuals with disabilities. To this end, large scale controlled walking experiments were conducted at Utah State University (USU) to examine walking behaviors in various walking facility types, such as passageway, right angle, oblique angle, queuing area, bottleneck, and stairs. Walking experiments were conducted over four days involving participants with and without disabilities. Automated video identification and semi-structured questionnaires were used to collect revealed and stated walking data. This study provided statistical analysis and models to study three different aspects of operational walking behaviors. Firstly, walking speed was examined as one of the most important behavioral variables. The differences in crowd walking speeds were carefully noted in analyzing the effects of adding individuals with disabilities and the impacts of different indoor walking facilities. Results showed that the presence of individuals with disabilities in a crowd significantly reduces the overall crowd speed. Statistical analysis also provided to compare walking speeds of pedestrian groups involving individuals with disabilities in different walking environments. Secondly, the dissertation proposed a framework to study the interactions of different pedestrian groups. Specifically, a mixed time headway distribution model was used to examine the time headway between followers and different leader types. In addition, the implications of interaction behaviors were studied based on the capacity of the queuing area behind the doorway. Results revealed that: (1) individuals with disabilities had significant effects on capacity reduction; (2) individuals with visual impairments and non-motorized ambulatory devices had the minimum capacity reduction effects in queuing area; and (2) individuals with motorized wheelchairs and individuals with mobility canes had the maximum capacity reduction effects in queuing area. Lastly, this study explored how a heterogeneous mix of pedestrians (including individuals with disabilities) perceive and evaluate operational performance of walking facilities. Both trajectory and survey data sources were used, and an ordered statistical approach was applied to analyze pedestrian perceptions. Results indicated that individuals with disabilities were less tolerant of extreme congested environments. Furthermore, analysis showed that the Level of Service (LOS) criteria provided in HCM does not follow the actual perceptions

Pedestrian flow characteristics through different angled bends: Exploring the spatial variation of velocity

Common geometrical layouts could potentially be bottlenecks, particularly during emergency and high density situations. When pedestrians are interacting with such complex geometrical settings, the congestion effect might not be uniform over the bottleneck area. This study uses the trajectory data collected through a controlled laboratory experiment to explore the spatial variation of speeds when a group of people navigates through bends. Four turning angles, i.e., 45°, 90°, 135° and 180°, with a straight corridor and two speed levels, i.e., normal speed walking and slow running (jogging), were considered in these experiments. Results explained that the speeds are significantly different over the space within the bend for all angles (except 0°) under both speed levels. In particular, average walking speeds are significantly lower near the inner corner of the bend as compared to the outer corner. Further, such speed variations are magnified when the angle of the bend and desired speed increase. These outcomes indicate that even smaller turning angles, e.g., 45° could create bottlenecks near the inner corner of the bend, particularly when the walking speeds are high. The findings of this study could be useful in understanding the congestion and bottleneck effects associated with complex geometrical settings, and calibrating microscopic simulation tools to accurately reproduce such effects.Open access funding was provided by the Qatar National Library