We conducted a computer-based experiment with over 450 human participants and used a Bayesian model selection approach to explore dynamic exit route choice mechanisms of individuals in simulated crowd evacuations. In contrast to previous work, we explicitly explore the use of time-dependent and time-independent information in decision-making. Our findings suggest that participants tended to base their exit choices on time-dependent information, such as differences in queue lengths and queue speeds at exits rather than on time-independent information, such as differences in exit widths or exit route length. We found weak support for similar decision-making mechanisms under a stress-inducing experimental treatment. However, under this treatment participants were less able or willing to adjust their original exit choice in the course of the evacuation. Our experiment is not a direct test of behaviour in real evacuations, but it does highlight the role different types of information and stress play in real human decision-making in a virtual environment. Our findings may be useful in identifying topics for future study on real human crowd movements or for developing more realistic agent-based simulations.
The evacuation of crowds from buildings or vehicles is one example that highlights the importance of understanding how individual-level interactions and decision-making combine and lead to the overall behaviour of crowds. In particular, to make evacuations safer, we need to understand how individuals make movement decisions in crowds. Here, we present an evacuation experiment with over 500 participants testing individual behaviour in an interactive virtual environment. Participants had to choose between different exit routes under the influence of three different types of directional information: static information (signs), dynamic information (movement of simulated crowd) and memorized information, as well as the combined effect of these different sources of directional information. In contrast to signs, crowd movement and memorized information did not have a significant effect on human exit route choice in isolation. However, when we combined the latter two treatments with additional directly conflicting sources of directional information, for example signs, they showed a clear effect by reducing the number of participants that followed the opposing directional information. This suggests that the signals participants observe more closely in isolation do not simply overrule alternative sources of directional information. Age and gender did not consistently explain differences in behaviour in our experiments.
In this paper we propose an event-driven way finding algorithm for pedestrians in a graph-based structure. The motivation of each pedestrian is to leave the facility. The events used to redirect pedestrians include the identification of a jam situation and/or identification of a better route than the present. The modeled strategies are the shortest path (local and global); they are combined with a quickest path approach, which is based on an observation principle, i.e. pedestrians take their decisions based on the observed environment and are routed dynamically in the network using an appropriate cost benefit analysis function. The influences of the different strategies on the evacuation time, the individual times spent in jam, the jam size evolution, and the overall jam size itself are investigated. The response of the system to broken escape routes is also analyzed. A good and plausible dynamic response in the route choice behavior of the pedestrians is achieved.
In moving pedestrian crowds, the distribution of individuals over different available routes emerges from the decisions of individuals that may be influenced by the actions of others. Understanding this phenomenon not only is important for research into collective behaviour, but also has practical applications for building safety and event management. Here, we study the mechanisms underlying pedestrian route choice, focusing on how time-independent information, such as path lengths, and time-dependent information, such as queue lengths, affect both initial decisions and subsequent changes in route choices. We address these questions using experiments with nearly 140 volunteers and an individual-based model for route choice. Crucially, we consider a wide range of route choice scenarios. We find that initial route choices of pedestrians achieve a balanced usage of available routes. Our model suggests that pedestrians performing trade-offs between exit widths and predicted exit crowdedness can explain this emergent distribution in many contexts. Few pedestrians adjust their route choice in our experiments. Simulations suggest that these decisions could be explained by pedestrians comparing estimates of the time it would take them to reach their target using different routes. Route choice is complex, but our findings suggest that conceptually simple behaviours may explain many movement decisions.
The choice of the exit to egress from a facility plays a fundamental role in pedestrian modelling and simulation. Yet, empirical evidence for backing up simulation is scarce. In this contribution, we present three new groups of experiments that we conducted in different geometries. We varied parameters such as the width of the doors, the initial location and number of pedestrians which in turn affected their perception of the environment. We extracted and analysed relevant indicators such as distance to the exits and density levels. The results put in evidence the fact that pedestrians use time-dependent information to optimize their exit choice, and that, in congested states, a load balancing over the exits occurs. We propose a minimal modelling approach that covers those situations, especially the cases where the geometry does not show a symmetrical configuration. Most of the models try to achieve the load balancing by simulating the system and solving optimization problems. We show statistically and by simulation that a linear model based on the distance to the exits and the density levels around the exit can be an efficient dynamical alternative.
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