https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=Stefan_et_al_2018aStefan et al 2018a - Revision history2026-04-30T19:59:54ZRevision history for this page on the wikiMediaWiki 1.27.0-wmf.10https://www.scipedia.com/wd/index.php?title=Stefan_et_al_2018a&diff=199797&oldid=prevScipediacontent: Scipediacontent moved page Draft Content 333439170 to Stefan et al 2018a2021-02-02T00:21:13Z<p>Scipediacontent moved page <a href="/public/Draft_Content_333439170" class="mw-redirect" title="Draft Content 333439170">Draft Content 333439170</a> to <a href="/public/Stefan_et_al_2018a" title="Stefan et al 2018a">Stefan et al 2018a</a></p>
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</td></tr></table>Scipediacontenthttps://www.scipedia.com/wd/index.php?title=Stefan_et_al_2018a&diff=199796&oldid=prevScipediacontent: Created page with " == Abstract == Pedestrians are among the most vulnerable victims of road traffic accidents. Establishing an unsignalized<br> pedestrian crossing at intersections occasionall..."2021-02-02T00:21:06Z<p>Created page with " == Abstract == Pedestrians are among the most vulnerable victims of road traffic accidents. Establishing an unsignalized<br> pedestrian crossing at intersections occasionall..."</p>
<p><b>New page</b></p><div><br />
== Abstract ==<br />
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Pedestrians are among the most vulnerable victims of road traffic accidents. Establishing an unsignalized<br> pedestrian crossing at intersections occasionally results in a high crash risk due to the fact that many vehicle<br> drivers do not heed the legitimate right of way of pedestrians, either deliberately or because of some kind of<br> distraction, speeding or deficiencies in the traffic environment. The primary objective of the OBSERVE project<br> was to develop a novel approach for evaluating crosswalks based on data from observed pedestrian-vehicle<br> driver interactions and local site conditions. Within the project, 85 unsignalized pedestrian crossings in the cities<br> of Graz and Vienna were investigated by means of video observation. The trajectories of different road user<br> categories were analysed to obtain information on driving and walking speeds, traffic behaviour, time gaps etc.<br> That information was subsequently used to model driving behaviour. For the modelling process, data from 54<br> zebra crossings were used. A beta-regression model identified the parameters ‘pedestrian crossing type’ and<br> ‘pedestrian crossing width’ having the highest influence on the stopping probability.<br />
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== Original document ==<br />
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The different versions of the original document can be found in:<br />
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* [https://zenodo.org/record/1487527 https://zenodo.org/record/1487527] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode<br />
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* [https://zenodo.org/record/1487527 https://zenodo.org/record/1487527],<br />
: [http://dx.doi.org/10.5281/zenodo.1487526 http://dx.doi.org/10.5281/zenodo.1487526] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode<br />
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* [https://zenodo.org/record/1487527 https://zenodo.org/record/1487527],<br />
: [http://dx.doi.org/10.5281/zenodo.1487527 http://dx.doi.org/10.5281/zenodo.1487527] under the license http://creativecommons.org/licenses/by-nc-nd/4.0/legalcode<br />
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DOIS: 10.5281/zenodo.1487526 10.5281/zenodo.1487527</div>Scipediacontent