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000852633 020__ $$a978-3-319-98653-1 (print)
000852633 020__ $$a978-3-319-98654-8 (electronic)
000852633 0247_ $$2doi$$a10.1007/978-3-319-99813-8_17
000852633 0247_ $$2ISSN$$a0302-9743
000852633 0247_ $$2ISSN$$a1611-3349
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000852633 037__ $$aFZJ-2018-05530
000852633 041__ $$aEnglish
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000852633 1001_ $$0P:(DE-Juel1)132077$$aChraibi, Mohcine$$b0$$eCorresponding author$$ufzj
000852633 1112_ $$aInternational conference on cellular automata for research and industry$$cComo$$d2018-09-17 - 2018-09-21$$gACRI 2018$$wItaly
000852633 245__ $$aThe automatic generation of an efficient floor field for CA simulations
000852633 260__ $$aCham$$bSpringer International Publishing$$c2018
000852633 29510 $$aCellular Automata
000852633 300__ $$a185 - 195
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000852633 4900_ $$aLecture Notes in Computer Science$$v11088
000852633 520__ $$aThe Hermes project [1] demonstrated the usefulness of on site predictive simulations of probable evacuation scenarios for security personnel. However, the hardware needed was prohibitively expensive [2]. For use in crowd management, the software has to run on available computers. The CA methods, which are fast enough, have well known problems with treating corners and turns. The present paper shows how a standard CA method can be modified to produce a realistic movement of people around bends and obstacles by changing the standard floor field. This can be done adaptively allowing for the momentary situation using simple predictions for the immediate future. The approach has one or two tuning parameter that have an obvious meaning and can therefore be set correctly by people not familiar with the inner process of a CA simulation. With this, a high end laptop can simulate more than 100 000 persons faster than real time, which should be enough for most occasions. It is intended to integrate the method into the tool JuPedSim [23].
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000852633 7001_ $$0P:(DE-Juel1)132269$$aSteffen, Bernhard$$b1$$ufzj
000852633 773__ $$a10.1007/978-3-319-99813-8_17
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