Department of Transportation Planning and Engineering, National Technical University of Athens, 5 Heroon Polytechniou Str., Athens GR-15773, Greece.
OSeven Telematics Limited, 27B Chaimanta Str., Athens GR-15234, Greece.
J Safety Res. 2020 Feb;72:203-212. doi: 10.1016/j.jsr.2019.12.021. Epub 2020 Jan 13.
Technological advancements during recent decades have led to the development of a wide array of tools and methods in order to record driving behavior and measure various aspects of driving performance. The aim of the present study is to present and comparatively assess the various driver recording tools that researchers have at their disposal.
In order to achieve this aim, a multitude of published studies from the international literature have been examined based on the driver recording methodologies that have been implemented. An examination of more traditional survey methods (questionnaires, police reports, and direct observer methods) is initially conducted, followed by investigating issues pertinent to the use of driving simulators. Afterwards, an extensive section is provided for naturalistic driving data tools, including the utilization of on-board diagnostics (OBD) and in-vehicle data recorders (IVDRs). Lastly, in-depth incident analysis and the exploitation of smartphone data are discussed.
A critical synthesis of the results is conducted, providing the advantages and disadvantages of utilizing each tool and including additional knowledge regarding ease of experimental implementation, data handling issues, impacts on subsequent analyses, as well as the respective cost parameters.
New technologies provide undeniably powerful tools that allow for seamless data handling, storage, and analysis, such as smartphones and in-vehicle data recorders. However, this sometimes comes at considerable costs (which may or may not pay off at a later stage), while legacy driver recording methods still have their own niches to fill in research. Practical Applications: The present research supports researchers when designing driver behavior monitoring studies. The present work enables better scheduling and pacing of research activities, but can also provide insights for the distribution of research funds.
近几十年来，技术的进步使得能够开发出各种工具和方法，以便记录驾驶行为并测量驾驶性能的各个方面。本研究的目的是介绍和比较研究人员可使用的各种驾驶员记录工具。
为了实现这一目标，根据所实施的驾驶员记录方法，对来自国际文献的大量已发表研究进行了检查。首先对更传统的调查方法（问卷、警察报告和直接观察者方法）进行了检查，然后研究了与驾驶模拟器使用相关的问题。接下来，提供了一个广泛的自然驾驶数据工具部分，包括使用车载诊断（OBD）和车内数据记录器（IVDR）。最后，深入讨论了事故分析和智能手机数据的利用。
对结果进行了批判性综合，介绍了每种工具的优缺点，并提供了有关实验实施的便利性、数据处理问题、对后续分析的影响以及各自成本参数的额外知识。
新技术提供了强大的工具，可实现无缝的数据处理、存储和分析，例如智能手机和车内数据记录器。然而，这有时需要付出相当大的代价（可能在以后的阶段得到回报，也可能得不到回报），而传统的驾驶员记录方法在研究中仍然有其自身的优势。
本研究为设计驾驶员行为监测研究的研究人员提供支持。本工作可以更好地安排和规划研究活动，但也可以为研究资金的分配提供见解。
