自然驾驶研究的描述性和概念性结构:计算文献综述

Fletcher J. Howell, Sjaan Koppel, David B. Logan
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引用次数: 0

摘要

自然驾驶研究(NDS)是一种新兴的方法,用于在没有实验控制的情况下从驾驶仪表车辆进行日常驾驶的驾驶员处收集驾驶数据。为评估 NDS 研究领域,我们进行了一次计算文献综述,旨在定量描述 NDS 数据现有应用的范围和结构。我们使用科学计量学和文本挖掘方法对 1120 篇文献进行了分析,以确定主要贡献者和主题。NDS 研究在美国和中国尤为突出,但与其他学科相比,国际合作有限。文件和词语的网络映射显示,NDS 研究的数据来源、类型和分析方法高度重叠。在道路安全的安全系统方法中,以驾驶员为中心的行为和特征,如分心、风险和年龄偏大,在数量和发生率方面最为相关,相比之下,道路基础设施和车辆方面的研究相对较少。
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Descriptive and conceptual structure of naturalistic driving study research: A computational literature review

Naturalistic driving studies (NDS) are an emerging method of collecting driving data from drivers in instrumented vehicles undertaking everyday trips without experimental control. A computational literature review was performed to assess the NDS research domain that aimed to quantitatively describe the extent and structure of existing applications of NDS data. A corpus of 1120 documents was analysed using the methods of scientometrics and text mining to identify prominent contributors and topics. NDS research saw particular prominence in the US and China, however, international collaboration was limited compared to other disciplines. Network mapping of documents and words showed a high degree of overlap in the data sources, types, and analysis methodologies across NDS research. In the context of a safe system approach to road safety, driver-centred behaviours and characteristics such as distraction, risk, and older age were most relevant in terms of number and occurrence, in contrast to relatively underrepresented aspects of road infrastructure and vehicles.

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来源期刊
Transportation Research Interdisciplinary Perspectives
Transportation Research Interdisciplinary Perspectives Engineering-Automotive Engineering
CiteScore
12.90
自引率
0.00%
发文量
185
审稿时长
22 weeks
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