A Review of Human Performance Models for Prediction of Driver Behavior and Interactions With In-Vehicle Technology
A Review of Human Performance Models for Prediction of Driver Behavior and Interactions With In-Vehicle Technology
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DOI：
10.1177/00187208221132740
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发表时间：
2022-10
期刊：
影响因子：
3.3
通讯作者：
Junho Park;Maryam Zahabi
中科院分区：
文献类型：
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作者：
Junho Park;Maryam Zahabi
目的研究人因模型（HPM）在驾驶员行为预测及与车载技术交互中的应用。背景HPM已被应用于许多人为因素领域，如地面交通，因为它可以量化和预测人的表现，但是，一直没有综合的文献综述预测驾驶员的行为和互动与车载技术方面的特点，所使用的方法和变量的探索。方法使用Compendex、Web of Science和Google Scholar进行系统的文献综述。结果，100项研究符合纳入标准，并由作者进行了审查。模型特征和变量进行了总结，以确定研究差距，并提供一个查找表，以选择适当的方法。结果研究结果提供了如何选择一个合适的HPM的基础上的自变量和因变量的组合的信息。综述了主要的HPM的特点、局限性、应用、建模工具和理论基础。结论该研究提供了一个国家的最新发展水平的使用HPM模型的驾驶员行为和使用的车载技术。我们提供了一个表格，可以帮助研究人员找到一个适当的建模方法的基础上，研究自变量和因变量。应用本研究的结果可以促进高功率微波在地面交通中的应用，并减少研究人员，特别是那些有限的建模背景的学习时间。
Objective This study investigated the use of human performance modeling (HPM) approach for prediction of driver behavior and interactions with in-vehicle technology. Background HPM has been applied in numerous human factors domains such as surface transportation as it can quantify and predict human performance; however, there has been no integrated literature review for predicting driver behavior and interactions with in-vehicle technology in terms of the characteristics of methods used and variables explored. Method A systematic literature review was conducted using Compendex, Web of Science, and Google Scholar. As a result, 100 studies met the inclusion criteria and were reviewed by the authors. Model characteristics and variables were summarized to identify the research gaps and to provide a lookup table to select an appropriate method. Results The findings provided information on how to select an appropriate HPM based on a combination of independent and dependent variables. The review also summarized the characteristics, limitations, applications, modeling tools, and theoretical bases of the major HPMs. Conclusion The study provided a summary of state-of-the-art on the use of HPM to model driver behavior and use of in-vehicle technology. We provided a table that can assist researchers to find an appropriate modeling approach based on the study independent and dependent variables. Application The findings of this study can facilitate the use of HPM in surface transportation and reduce the learning time for researchers especially those with limited modeling background.