自然驾驶数据的应用:系统性审查和文献识别分析
Md Rakibul Alam1, Debapreet Batabyal1, Kui Yang1
1Chair of Transportation Systems Engineering, Technical University of Munich, Munich, Germany.
Accident; analysis and prevention
|June 28, 2023
概括
自然驾驶数据 (NDD) 分析揭示了驾驶员安全研究的关键趋势. 本系统性审查对智能运输系统 (ITS) 中的NDD应用进行了映射,突出了共同的主题和进化细微差别.
科学领域:
- 智能运输系统 (ITS) 研究研究
- 驾驶员行为和安全分析分析.
- 数据驱动的运输研究
背景情况:
- 自然驾驶数据 (NDD) 提供了对驾驶员行为和安全的洞察.
- 现有的审查缺乏在ITS中的NDD应用程序的全面聚合.
- 了解NDD应用的演变对于未来的研究至关重要.
研究的目的:
- 系统地审查和绘制NDD在智能运输系统 (ITS) 研究中的应用.
- 确定NDD利用的进化趋势和主题集群.
- 提供NDD应用的多方面的聚合,解决当前的研究差距.
主要方法:
- 使用关键词"自然主义驾驶数据"和"自然主义驾驶研究数据"进行系统的文献审查.
- 采用了研究绩效分析和科学绘图技术.
- 2002年1月至2022年3月期间发表的393篇论文的专题聚类.
主要成果:
- 确定了NDD的共同应用领域,建模目标和分析技术.
- 突出了主要ITS研究领域与NDD整合之间的关系.
- 揭示了NDD应用程序在二十年中的进化轨迹.
结论:
- 在ITS中,NDD是推动驾驶员安全和行为评估的重要资源.
- 本综述提供了NDD应用程序的结构化概述,帮助研究人员在现场导航.
- 未来的研究可以利用这些发现来探索新兴趋势和完善分析技术.
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