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在三种能见度条件和两种速度下,使用驾驶模拟器测试跟车决策。

Car following decisions under three visibility conditions and two speeds tested with a driving simulator.

作者信息

Broughton Kathy L M, Switzer Fred, Scott Don

机构信息

Psychology Department, 410-F Brackett Hall, Clemson University, Clemson, SC 29634, USA.

出版信息

Accid Anal Prev. 2007 Jan;39(1):106-16. doi: 10.1016/j.aap.2006.06.009. Epub 2006 Sep 7.

Abstract

The National Highway Traffic Safety Administration web site reports that rear-end collisions in the United States exceed 1.5 million per year, or approximately 23% of all vehicle crashes. Car following behavior and the decision-making habits of drivers seem fundamental to understanding how to avoid these rear-end crashes. The present research aimed to reveal factors that govern car following under conditions of reduced visibility. It employed a KQ-Vection high-fidelity driving simulator to measure the behavior of automobile drivers following a lead vehicle at 13.4 m/s (30 MPH) or 22.4 m/s (50 MPH) under three visibility conditions--clear or one of two densities of simulated fog. At the higher speed, fog conditions separated participants into a group that stayed within visible range of the lead car, even though the headway time violated the NHTSA recommendations for the speed involved, and another group that lagged beyond the visible range. Data were compared to the model of Van Winsum for car following (The human element in car following models. Transportation Research Part F 2, 1999). Contrast and image size measurements allowed comparison to a standard contrast sensitivity function and allowed estimation of the JND term in the Van Winsum model.

摘要

美国国家公路交通安全管理局网站报告称,美国每年的追尾碰撞事故超过150万起,约占所有车辆碰撞事故的23%。跟车行为和驾驶员的决策习惯似乎是理解如何避免这些追尾事故的关键。本研究旨在揭示在能见度降低的情况下影响跟车行为的因素。研究使用了一台KQ-Vection高保真驾驶模拟器,在三种能见度条件下——清晰或两种密度的模拟雾中的一种——测量汽车驾驶员以13.4米/秒(30英里/小时)或22.4米/秒(50英里/小时)的速度跟在一辆前车后面时的行为。在较高速度下,雾天条件将参与者分为两组,一组即使车头时距违反了美国国家公路交通安全管理局针对该速度的建议,仍保持在前车的可视范围内,另一组则落在可视范围之外。研究将数据与范·温苏姆的跟车模型(跟车模型中的人为因素。《交通研究F辑》第2卷,1999年)进行了比较。对比度和图像尺寸测量使得研究能够与标准对比度敏感度函数进行比较,并能够估计范·温苏姆模型中的JND项。

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