Beijing Engineering Research Center of Urban Transport Operation Guarantee, College of Metropolitan Transportation, Beijing University of Technology, Beijing, 100124, PR China.
Traffic Operations & Safety Laboratory, University of Wisconsin-Madison, 1415 Engineering Drive, Madison, WI 53706, USA.
Accid Anal Prev. 2019 Jul;128:197-205. doi: 10.1016/j.aap.2019.04.019. Epub 2019 May 1.
This paper studies the effectiveness of fog warning systems on driving performance and traffic safety in heavy fog condition. A comparison study was conducted for four scenarios in heavy fog condition. First, a series of indexes corresponding to driving speed adjustments and surrogate measures of safety was obtained to explore the impacts that fog warning systems have on driving behavior and traffic safety when approaching a fog area. This study divided the analyzed road into three different zones (clear zone, transition zone, and fog zone) according to visibility levels. Then, multivariate analysis of variance (MANOVA) was conducted, and the effects of drivers' individual characteristics on driving behavior were also investigated. Moreover, the linear mixed model with random effects was estimated to consider the contributing factors of the drivers' speed adjustment behaviors. In addition, the standard deviation of speed, TET (time exposed time-to-collision), and TIT (time integrated time-to-collision) were selected to evaluate the longitudinal safety. To obtain the driving data, an empirical driving simulator platform was established based on a real-world road in Beijing. Thirty-five drivers were recruited to participate in the driving experiment. The results showed that the cooperative vehicle-infrastructure warning systems could be beneficial to better driving behavior and safer traffic operations. The results revealed that the warning systems could be beneficial to speed reduction before entering a fog area. In addition, the On-Board Unit (OBU) had a significant impact on individual speed adjustment. Moreover, the results showed that scenarios with fog warning systems improve safety significantly over the no warning system scenario. The study results could also facilitate the selection of a proper information release format in the context of connected vehicles.
本文研究了雾天预警系统对驾驶性能和交通安全的影响。在雾天条件下，对四个场景进行了对比研究。首先，获得了一系列与驾驶速度调整相对应的指标和安全替代指标，以探索雾天预警系统在接近雾区时对驾驶行为和交通安全的影响。本研究根据能见度水平将分析道路分为三个不同区域（清晰区、过渡区和雾区）。然后，进行了多元方差分析（MANOVA），并研究了驾驶员个体特征对驾驶行为的影响。此外，还使用具有随机效应的线性混合模型来考虑驾驶员速度调整行为的影响因素。此外，选择速度标准差、TET（碰撞时间暴露时间）和 TIT（碰撞时间综合时间）来评估纵向安全性。为了获得驾驶数据，基于北京的真实道路，建立了一个经验驾驶模拟器平台。共招募了 35 名驾驶员参与驾驶实验。结果表明，协同车路预警系统有利于改善驾驶行为和提高交通运行安全。结果表明，预警系统有利于在进入雾区前减速。此外，OBU（车载单元）对个体速度调整有显著影响。此外，结果表明，有雾天预警系统的场景比没有预警系统的场景显著提高了安全性。研究结果还可以为在车联网环境下选择适当的信息发布格式提供参考。
