@article{ref1,
title="Macro-level literature analysis on pedestrian safety: bibliometric overview, conceptual frames, and trends",
journal="Accident analysis and prevention",
year="2022",
author="Mirhashemi, Ali and Amirifar, Saeideh and Tavakoli Kashani, Ali and Zou, Xin",
volume="174",
number="",
pages="e106720-e106720",
abstract="Due to the high volume of documents in the pedestrian safety field, the current study conducts a systematic bibliometric analysis on the researches published before October 3, 2021, based on the science-mapping approach. Science mapping enables us to present a broad picture and comprehensive review of a significant number of documents using co-citation, bibliographic coupling, collaboration, and co-word analysis. To this end, a dataset of 6311 pedestrian safety papers was collected from the Web of Science Core Collection database. First, a descriptive analysis was carried out, covering whole yearly publications, most-cited papers, and most-productive authors, as well as sources, affiliations, and countries. In the next steps, science mapping was implemented to clarify the social, intellectual, and conceptual structures of pedestrian-safety research using the VOSviewer and Bibliometrix R-package tools. Remarkably, based on intellectual structure, pedestrian safety demonstrated an association with seven research areas: &quot;Pedestrian crash frequency models&quot;, &quot;Pedestrian injury severity crash models&quot;, &quot;Traffic engineering measures in pedestrians' safety&quot;, &quot;Global reports around pedestrian accident epidemiology&quot;, &quot;Effect of age and gender on pedestrians' behavior&quot;, &quot;Distraction of pedestrians&quot;, and &quot;Pedestrian crowd dynamics and evacuation&quot;. Moreover, according to conceptual structure, five major research fronts were found to be relevant, namely &quot;Collision avoidance and intelligent transportation systems (ITS)&quot;, &quot;Epidemiological studies of pedestrian injury and prevention&quot;, &quot;Pedestrian road crossing and behavioral factors&quot;, &quot;Pedestrian flow simulation&quot;, and &quot;Walkable environment and pedestrian safety&quot;. Finally, &quot;autonomous vehicle&quot;, &quot;pedestrian detection&quot;, and &quot;collision avoidance&quot; themes were identified as having the greatest centrality and development degrees in recent years.<p /> <p>Language: en</p>",
language="en",
issn="0001-4575",
doi="10.1016/j.aap.2022.106720",
url="http://dx.doi.org/10.1016/j.aap.2022.106720"
}