文章基本信息

标题：Human Multi-Robot Communication for Roadway Safety Notification
本地全文：下载
作者：Jessica Manning ; Yue Wang ; John Wagner 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2021
卷号：54
期号：20
页码：783-788
DOI：10.1016/j.ifacol.2021.11.267
语种：English
出版社：Elsevier
摘要：AbstractMulti-robot systems (MRS) involve multiple individual robots working together towards a common goal. Human multi-robot interaction research has focused on either using a visual interface for humans or having the human use speech or gestures to interact with multiple agents. Some difficulties lie with the humans’ ability to collect information from multiple robots. This paper investigates the use of MRS to visually communicate with vehicle drivers for roadway safety information by depicting various shapes and symbols. The robots will move to visually display an internationally recognizable shape or alphanumeric message for the human to interpret. These messages could be quickly deployed along the roadway to inform operators of drastic changes in the road conditions such as crashes, environmental hazards, or construction zones. The quick deployment offers a suitable addition to fixed roadway signs which are unable to rapidly adapt to changing conditions. A computer-generated display conveys these symbols to human test subjects using multiple agents. The chosen statistical analyses performed include Analysis of Variance (ANOVA) with additional Tukey’s Honestly Significant Difference (HSD) and Chi-square tests. Researchers used 25 participants in the tests conducted through Zoom where 62% of responses correctly identified the shapes with an average time of 10.84 seconds. The tests demonstrated a statistically significant average estimation time difference among the various shapes, and that the participants can accurately identify each shape. There was also an association between accuracy of prediction and number of robots used in the trials.
关键词：KeywordsHuman-MachineHuman-Robot SystemsRoboticsTransportation Systems