Naturalistic driving study data applied to road infrastructure: A systematic review

IF 3.9 2区 工程技术 Q1 ERGONOMICS
Fletcher J. Howell, Azhaginiyal Arularasu, David B. Logan, Sjaan Koppel
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引用次数: 0

Abstract

Introduction:

Naturalistic driving studies (NDS) have great potential to characterize the road infrastructure factors influencing everyday driving. A systematic review was undertaken to evaluate the objectives, data processing, and analyses in best-practice applications of NDS data to road infrastructure. Method: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, a systematic search of seven databases was conducted on 27 June 2023 (PROSPERO CRD42023434948). Fifty-three English-language, peer-reviewed studies were analyzed on the basis of the primary infrastructure category reflected in the research aims. Results: Studies described curves (14), turns at intersections (8), intersections (6), multi-modal treatments (6), ramps (4), work zones (4), charging (2), and other factors (9). Each study was assessed for the risk of methodological bias using amended National Heart, Lung, and Blood Institute templates for Quality Assurance. 74% of studies were assessed to be of ’Good’ quality, 13% of ‘Fair’ quality, and 13% of ‘Poor’ quality. Road infrastructure was characterized by external video (38%) complemented by non-NDS sources including satellite imagery (21%) and government data (19%). Data preparation was required in 91% of studies to extract meaningful variables (e.g. manual video coding) and/or link multiple datasets. Analysis predominantly determined correlations between aspects of driver behavior (speed, trajectory, etc.) and infrastructure factors (geometry, lane configuration, etc.). Conclusions: The methods employed were broadly applicable, but required considerable subject-specific adaptation for non-NDS datasets and/or time-consuming video coding. The incorporation of road infrastructure factors in NDS research can continue to be improved by reducing the computational cost of sample processing.Practical Applications: Encouraged by the adaptability of the identified methods, NDS research has the potential to benefit from the consideration of road infrastructure factors in a Safe System context. The analytical requirements for all components of the Safe System should be considered when planning future NDS data collections and/or analysis.
自然驾驶研究(NDS)在描述影响日常驾驶的道路基础设施因素方面具有很大的潜力。我们进行了一项系统审查,以评估NDS数据在道路基础设施中的最佳应用目标、数据处理和分析。方法:根据系统评价和荟萃分析首选报告项目(PRISMA)指南,于2023年6月27日对7个数据库进行系统检索(PROSPERO CRD42023434948)。根据研究目标中反映的主要基础设施类别,分析了53份同行评议的英语研究。结果:研究描述了曲线(14)、十字路口转弯(8)、十字路口(6)、多模式治疗(6)、坡道(4)、工作区(4)、收费(2)和其他因素(9)。使用修订后的国家心脏、肺和血液研究所质量保证模板评估了每项研究方法偏差的风险。74%的研究被评估为“好”质量,13%为“一般”质量,13%为“差”质量。道路基础设施的特点是外部视频(38%),辅以非nds来源,包括卫星图像(21%)和政府数据(19%)。91%的研究需要进行数据准备,以提取有意义的变量(如手动视频编码)和/或链接多个数据集。分析主要确定了驾驶员行为(速度、轨迹等)和基础设施因素(几何形状、车道配置等)之间的相关性。结论:采用的方法广泛适用,但需要针对非nds数据集和/或耗时的视频编码进行大量的主题调整。通过降低样本处理的计算成本,可以继续改进NDS研究中道路基础设施因素的纳入。实际应用:由于所确定方法的适应性,NDS研究有可能从考虑安全系统背景下的道路基础设施因素中受益。在规划未来的NDS数据收集和/或分析时,应考虑安全系统所有组成部分的分析要求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.40
自引率
4.90%
发文量
174
审稿时长
61 days
期刊介绍: Journal of Safety Research is an interdisciplinary publication that provides for the exchange of ideas and scientific evidence capturing studies through research in all areas of safety and health, including traffic, workplace, home, and community. This forum invites research using rigorous methodologies, encourages translational research, and engages the global scientific community through various partnerships (e.g., this outreach includes highlighting some of the latest findings from the U.S. Centers for Disease Control and Prevention).
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