A multi-layer social force approach to model interactions in shared spaces using collision prediction

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Rinke, N.; Schiermeyer, C.; Pascucci, F.; Berkhahn, V.; Friedrich, B.: A multi-layer social force approach to model interactions in shared spaces using collision prediction. In: Transportation Research Procedia 25 (2017), S. 1249-1267. DOI: https://doi.org/10.1016/j.trpro.2017.05.144

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/1689

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Sum total of downloads: 356




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Abstract: 
In shared space environments the movements of road users is not regulated by traffic rules, but is the result of spontaneous interaction between traffic users, who negotiate the priority according to social rules such as eye contact or courtesy behavior. However, appropriate micro simulation tools, which can reproduce the operation of shared spaces, are currently lacking. In this paper, a multi-layer approach for representing the movement of road users and their interaction, based on the Social Force Model, is developed. In a free-flow layer a realistic path is calculated for each user towards his destination, while a conflict layer is used for detecting possible conflict situations and computing an appropriate reaction. The novelty of this work in the field of shared space modeling is in the implementation of group dynamics and a SFM based approach for cyclists. The presented approach is qualitatively tested in different traffic situations involving cyclists, pedestrians and pedestrian groups, and shows realistic behavior. © 2017 The Authors. Published by Elsevier B.V.
License of this version: CC BY-NC-ND 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2017
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

distribution of downloads over the selected time period:

downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 157 44.10%
2 image of flag of United States United States 79 22.19%
3 image of flag of China China 31 8.71%
4 image of flag of Japan Japan 18 5.06%
5 image of flag of Singapore Singapore 7 1.97%
6 image of flag of Taiwan Taiwan 6 1.69%
7 image of flag of India India 6 1.69%
8 image of flag of Hong Kong Hong Kong 6 1.69%
9 image of flag of Canada Canada 6 1.69%
10 image of flag of United Kingdom United Kingdom 5 1.40%
    other countries 35 9.83%

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