Modeling people behavior in emergency situations

A model of human behavior in emergency situations in confined spaces with a complex structure. A distinctive feature of this model is that the information influence of the behavior of agents in the group is individual. The level of exposure to the influence of the information agent depends on the type, based on some factors, such as location relative to the group members, the physical and functional characteristics of the individual membership. By the functional affiliation is meant the role of agent upon condition the absence of some external destructive influences. The proposed model describes four possible physical states of the agent: alive and active; alive and passive, wounded; received critical damage, unable to move; dead. The developed theoretical foundations models have been implemented in a software environment simulation by the example of incident in the club “Lame Horse” located in Perm, Russia, 05.12.2009. The experiments showed results corresponds to the actual outcome of the incident model operating results with considering the probability of deviations

Flocking factors' assessment in case of destructive impact on swarm robotic systems

This paper dwells on exposures' analysis of open-environment operated swarm robotic systems. Flocking algorithms for swarm robotics, which use alignment and averaging of direction in local communication radius (after C. Reynolds' model) are considered. The problem where a small group of informed robots has to guide the swarm along a desired direction is also considered. Couzin I. D. et al. (2005) showed that even a minority of informed individuals is able to move the group toward the target Hereafter great number of swarm robotics' flocking algorithms were developed in order to increase swarm system's handiness. Several implicit leadership algorithms for distributed robotic systems were proposed. The idea of this paper is to study and simulate the operation of such kind of above mentioned algorithms in the situation when there are saboteurs which destructively impact swarm system. Specially developed by authors simulation software allows to vary the parameters of system operation, which can be rather the number of agents or their interaction features or etc. On the basis of the experimental data the authors produce the analysis of features in order to determine their relevance to the algorithm

Planning of Autonomous Multi-agent Intersection

In this paper, we propose a traffic management system with agents acting on behalf autonomous vehicle at the crossroads. Alternatively to existing solutions based on usage of semiautonomous control systems with the control unit, proposed in this paper algorithm apply the principles of decentralized multi-agent control. Agents during their collaboration generate intersection plan and determinate the optimal order of road intersection for a given criterion based on the exchange of information about them and their environment. The paper contains optimization criteria for possible routes selection and experiments that perform in order to estimate the proposed model. Experiment results show that this model can significantly reduce traffic density compared to the traditional traffic management systems. Moreover, the proposed algorithm efficiency increases with road traffic density. Furthermore, the availability of control unit in the system significantly reduces the negative impact of possible failures and hacker attacks

Planning of Autonomous Multi-agent Intersection

In this paper, we propose a traffic management system with agents acting on behalf autonomous vehicle at the crossroads. Alternatively to existing solutions based on usage of semiautonomous control systems with the control unit, proposed in this paper algorithm apply the principles of decentralized multi-agent control. Agents during their collaboration generate intersection plan and determinate the optimal order of road intersection for a given criterion based on the exchange of information about them and their environment. The paper contains optimization criteria for possible routes selection and experiments that perform in order to estimate the proposed model. Experiment results show that this model can significantly reduce traffic density compared to the traditional traffic management systems. Moreover, the proposed algorithm efficiency increases with road traffic density. Furthermore, the availability of control unit in the system significantly reduces the negative impact of possible failures and hacker attacks