Highway Capacity Manual改訂の動向--テイラ-教授の講演より

With the increasing size and frequency of mass events, the study of crowd disasters and the simulation of pedestrian flows have become important research areas. However, even successful modeling approaches such as those inspired by Newtonian force models are still not fully consistent with empirical observations and are sometimes hard to calibrate. Here, a cognitive science approach is proposed, which is based on behavioral heuristics. We suggest that, guided by visual information, namely the distance of obstructions in candidate lines of sight, pedestrians apply two simple cognitive procedures to adapt their walking speeds and directions. Although simpler than previous approaches, this model predicts individual trajectories and collective patterns of motion in good quantitative agreement with a large variety of empirical and experimental data. This model predicts the emergence of self-organization phenomena, such as the spontaneous formation of unidirectional lanes or stop-and-go waves. Moreover, the combination of pedestrian heuristics with body collisions generates crowd turbulence at extreme densities—a phenomenon that has been observed during recent crowd disasters. By proposing an integrated treatment of simultaneous interactions between multiple individuals, our approach overcomes limitations of current physics-inspired pair interaction models. Understanding crowd dynamics through cognitive heuristics is therefore not only crucial for a better preparation of safe mass events. It also clears the way for a more realistic modeling of collective social behaviors, in particular of human crowds and biological swarms. Furthermore, our behavioral heuristics may serve to improve the navigation of autonomous robots.

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How simple rules determine pedestrian behavior and crowd disasters

We present a real-time crowd model based on continuum dynamics. In our model, a dynamic potential field simultaneously integrates global navigation with moving obstacles such as other people, efficiently solving for the motion of large crowds without the need for explicit collision avoidance. Simulations created with our system run at interactive rates, demonstrate smooth flow under a variety of conditions, and naturally exhibit emergent phenomena that have been observed in real crowds.

Continuum crowds

Human mobility: Models and applications

Every organisation from the scale of whole countries down to small companies has a list of system developments which have ended in various forms of disaster. The nature of the failures varies but typical examples are: cost overruns; timescale overruns and sometimes, loss of life. The post-mortems to these systems reveal a wide range of reasons all the way from hardware failures, through software errors right to major system level mistakes. More importantly a large number of these systems share one attribute: complexity. This paper presents a fresh look at the nature of complexity in the building of computer based systems.

http://ieeexplore.ieee.org/iel3/4458/12639/00581896.pdf

Complex systems

We present simulations of evacuation processes using a recently introduced cellular automaton model for pedestrian dynamics. This model applies a bionics approach to describe the interaction between the pedestrians using ideas from chemotaxis. Here we study a rather simple situation, namely the evacuation from a large room with one or two doors. It is shown that the variation of the model parameters allows to describe different types of behaviour, from regular to panic. We find a non-monotonic dependence of the evacuation times on the coupling constants. These times depend on the strength of the herding behaviour, with minimal evacuation times for some intermediate values of the couplings, i.e., a proper combination of herding and use of knowledge about the shortest way to the exit.

/pdf/simulation-of-evacuation-processes-using-a-bionics-inspired-3b8s1kn0gb.pdf

Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics

We investigate the role of conflicts in pedestrian traffic, i.e., situations where two or more people try to enter the same space. Therefore a recently introduced cellular automaton model for pedestrian dynamics is extended by a friction parameter mu. This parameter controls the probability that the movement of all particles involved in a conflict is denied at one time step. It is shown that these conflicts are not an undesirable artifact of the parallel update scheme, but are important for a correct description of the dynamics. The friction parameter mu can be interpreted as a kind of an internal local pressure between the pedestrians which becomes important in regions of high density, occurring, e.g., in panic situations. We present simulations of the evacuation of a large room with one door. It is found that friction has not only quantitative effects, but can also lead to qualitative changes, e.g., of the dependence of the evacuation time on the system parameters. We also observe similarities to the flow of granular materials, e.g., arching effects.

Friction effects and clogging in a cellular automaton model for pedestrian dynamics.

The floor field model, which is a cellular automaton model for studying evacuation dynamics, is investigated and extended. A method for calculating the static floor field, which describes the shortest distance to an exit door, in an arbitrary geometry of rooms is presented. The wall potential and contraction effect at a wide exit are also proposed in order to obtain realistic behavior near corners and bottlenecks. These extensions are important for evacuation simulations, especially in the case of panics.

Extended floor field CA model for evacuation dynamics

We report new results obtained using cellular automata for pedestrian dynamics with friction. Monte-Carlo simulations of evacuation processes are compared with experimental results on competitive behavior in emergency egress from an aircraft. In the model, the recently introduced

/pdf/simulation-of-competitive-egress-behavior-comparison-with-3e75ca4ynj.pdf

Simulation of competitive egress behavior: comparison with aircraft evacuation data

We study discretization effects in cellular automata models for pedestrian dynamics by reducing the cell size. Then a particle occupies more than one cell which leads to subtle effects in the dynamics, e.g. non-local conflict situations. Results from computer simulations of the floor field model are compared with empirical findings. Furthermore, the influence of increasing the maximal walking speed vmax is investigated by increasing the interaction range beyond nearest neighbour interactions. The extension of the model to vmax>1 turns out to be a severe challenge which can be solved in different ways. Four major variants are discussed that take into account different dynamical aspects. The variation of vmax has a strong influence on the shape of the flow–density relation. We show that walking speeds vmax>1 lead to results which are in very good agreement with empirical data.

/pdf/discretization-effects-and-the-influence-of-walking-speed-in-2e070g69ov.pdf

Ansgar Kirchner

Papers

Simulation of evacuation processes using a bionics-inspired cellular automaton model for pedestrian dynamics

Friction effects and clogging in a cellular automaton model for pedestrian dynamics.

Extended floor field CA model for evacuation dynamics

Simulation of competitive egress behavior: comparison with aircraft evacuation data

Discretization effects and the influence of walking speed in cellular automata models for pedestrian dynamics