基于驾驶模拟器的大雾驾驶预警系统评价

Xiaohua Zhao;Xuewei Li;Yufei Chen;Haijian Li;Yang Ding
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引用次数: 8

摘要

目的-大雾会导致能见度低,从而增加交通事故的概率和严重程度,而大雾预警系统通过向驾驶员传达警告信息,有助于减少事故。本文旨在探讨大雾预警系统动态信息标志(DMS)对驾驶员性能的影响。设计/方法/方法-首先,建立了一个基于驾驶模拟器的测试平台,并收集了DMS下的驾驶员表现数据。实验路线由三个不同的区域(即警戒区、过渡区和大雾区)组成,选择了整个区域的平均速度、平均加速度、平均急动度、警戒区和过渡区的终止速度、过渡区与大雾区的最大减速率和平均减速比。接下来,应用单向方差分析来测试指标之间的显著差异。此外,还考虑了驾驶员的主观感受。调查结果-结果表明,DMS有利于在驾驶员进入大雾区之前降低速度。此外,当驾驶员进入大雾区时,DMS可以减轻驾驶员的紧张情绪,使驾驶员操作更加平稳。独创性/价值-本文基于驾驶模拟测试平台,提供了一种评估预警系统在不利条件下有效性的综合方法。该方法可以扩展到其他特殊场景下的车辆到基础设施技术评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of fog warning system on driving under heavy fog condition based on driving simulator
Purpose - Heavy fog results in low visibility, which increases the probability and severity of traffic crashes, and fog warning system is conducive to the reduction of crashes by conveying warning messages to drivers. This paper aims at exploring the effects of dynamic message sign (DMS) of fog warning system on driver performance. Design/methodology/approach - First, a testing platform was established based on driving simulator and driver performance data under DMS were collected. The experiment route was consisted of three different zones (i.e. warning zone, transition zone and heavy fog zone), and mean speed, mean acceleration, mean jerk in the whole zone, ending speed in the warning zone and transition zone, maximum deceleration rate and mean speed reduction proportion in the transition zone and heavy fog zone were selected. Next, the one-way analysis of variance was applied to test the significant difference between the metrics. Besides, drivers' subjective perception was also considered. Findings - The results indicated that DMS is beneficial to reduce speed before drivers enter the heavy fog zone. Besides, when drivers enter a heavy fog zone, DMS can reduce the tension of drivers and make drivers operate more smoothly. Originality/value - This paper provides a comprehensive approach for evaluating the effectiveness of the warning system in adverse conditions based on the driving simulation test platform. The method can be extended to the evaluation of vehicle-to-infrastructure technology in other special scenarios.
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