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001024563 1001_ $$0P:(DE-Juel1)185055$$aFeldmann, Sina$$b0
001024563 1112_ $$aPedestrian and Evacuation Dynamics 2023$$cEindhoven$$d2023-06-28 - 2023-06-30$$gPED2023
001024563 245__ $$aTemporal segmentation of motion propagation in response to an external impulse
001024563 260__ $$aAmsterdam [u.a.]$$bElsevier Science$$c2024
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001024563 520__ $$aIn high-density crowds, local motion can propagate, amplify, and lead to macroscopic phenomena, including"density waves". These density waves only occur when individuals interact, and impulses are transferred toneighbours. How this impulse is passed on by the human body and which effects this has on individuals isstill not fully understood. To further investigate this, experiments focusing on the propagation of a push wereconducted within the EU-funded project CrowdDNA. In the experiments the crowd is greatly simplified byfive people lining up in a row. The rearmost person in the row was pushed forward in a controlled mannerwith a punching bag. The intensity of the push, the initial distance between participants and the initial armposture were varied. Collected data included side view and top view video recordings, head trajectories, 3Dmotion using motion capturing (MoCap) suits as well as pressure measured at the punching bag. With a hybridtracking algorithm, the MoCap data are combined with the head trajectories to allow an analysis of the motionof each limb in relation to other persons.The observed motion of the body in response to the push can be divided into three phases. These are (i)receiving an impulse, (ii) receiving and passing on an impulse, and (iii) passing on an impulse. Using the 3DMoCap data, we can identify the start and end times of each phase. To determine when a push is passed on,the forward motion of the person in front has to be considered. The projection of the center of mass relativeto the initial position of the feet is a measure of the extent to which a person is displaced from the restposition. Specifying the timing of these phases is particularly important to distinguish between different typesof physical interactions. Our results contribute to the development and validation of a pedestrian model foridentifying risks due to motion propagation in dense crowds.
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001024563 536__ $$0G:(EU-Grant)899739$$aCrowdDNA - TECHNOLOGIES FOR COMPUTER-ASSISTED CROWD MANAGEMENT (899739)$$c899739$$fH2020-FETOPEN-2018-2019-2020-01$$x1
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001024563 7001_ $$0P:(DE-Juel1)203585$$aChatagnon, Thomas$$b1$$ufzj
001024563 7001_ $$0P:(DE-Juel1)173971$$aAdrian, Juliane$$b2$$eCorresponding author
001024563 7001_ $$0P:(DE-HGF)0$$aPettré, Julien$$b3
001024563 7001_ $$0P:(DE-Juel1)132266$$aSeyfried, Armin$$b4
001024563 773__ $$0PERI:(DE-600)2021100-4$$a10.1016/j.ssci.2024.106512$$gVol. 175, p. 106512 -$$p106512$$tSafety Science$$v175$$x0925-7535$$y2024
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