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The interrelationships between speed limits, geometry, and driver behavior: a proof-of-concept study utilizing naturalistic driving data

机译:速度限制,几何形状和驾驶员行为之间的相互关系:利用自然驾驶数据的概念验证研究

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摘要

Speed management has been an extensive focus of traffic safety research dating back to the 1960\u27s. Research has generally shown crash risk to increase as the average speed of traffic increases and as the standard deviation of travel speeds increases within a traffic stream. However, research as to the effects of speed limits has been somewhat inconclusive.This study investigates how speed limits affect driver speed selection, as well as the resultant crash risk, while controlling for various confounding factors such as traffic volumes and roadway geometry. Data are obtained at very high resolution from a Naturalistic Driving Study (NDS) conducted as a part of the second Strategic Highway Research Program (SHRP 2). These data are integrated with a Roadway Information Database (RID), which provides extensive details as to roadway characteristics in the six-state study area (Florida, Indiana, New York, North Carolina, Pennsylvania, and Washington.) These sources are used to examine how driver speed selection varies among freeways with different posted speed limits, and how the likelihood of crash/near-crash events change with respect to various speed metrics.Regression models are estimated to assess three measures of interest: the average speed of vehicles during the time preceding crash, near-crash, and baseline (i.e., normal) driving events; the variation in travel speeds leading up to each event as quantified by the standard deviation in speeds over this period (i.e. the average acceleration/deceleration rate); and the probability of a specific event resulting in a crash or near-crash based on speed selection and other salient factors.Significant correlation was observed with respect to speed selection behavior among the same individuals and particularly within a single driving event. Mean speeds are shown to increase with speed limits. However, these increases are less pronounced at higher speed limits. Drivers tend to reduce their travel speeds along horizontal or vertical curves, under adverse weather conditions, and particularly under heavy congestion. Increases in average travel speed and the variability in travel speeds are both found to increase crash risk. Crash risk also increases on vertical curves and ramp junctions, as well as among the youngest and oldest age groups of drivers.Ultimately, this research provides an important demonstration of how naturalistic driving data may be leveraged to examine driver behavior and research questions of interest that are difficult or impractical through other empirical settings. The results also provide important insights that provide greater understanding of how drivers adapt their speed selection behavior in response to posted speed limits and other roadway characteristics.
机译:自1960年代以来,速度管理一直是交通安全研究的重点。研究通常显示出崩溃风险随着交通平均速度的增加以及交通流中行驶速度的标准偏差的增加而增加。然而,关于速度限制的影响的研究尚无定论。这项研究调查了速度限制如何影响驾驶员的速度选择以及由此产生的撞车风险,同时控制了各种混杂因素,例如交通量和道路几何形状。作为第二个战略公路研究计划(SHRP 2)的一部分,从自然驾驶研究(NDS)以高分辨率获得了数据。这些数据与道路信息数据库(RID)集成在一起,该信息数据库提供了有关六州研究区域(佛罗里达州,印第安纳州,纽约州,北卡罗来纳州,宾夕法尼亚州和华盛顿州)道路特征的广泛详细信息。检查驾驶员的速度选择在具有不同公布速度限制的高速公路之间如何变化,以及撞车/近撞事件的可能性相对于各种速度指标如何变化。估计回归模型以评估三个令人关注的指标:车辆在行驶期间的平均速度撞车,接近撞车和基线(即正常)驾驶事件之前的时间;通过此期间速度的标准偏差(即平均加速/减速率)来量化导致每个事件的行进速度变化;以及基于速度选择和其他显着因素的特定事件导致撞车或接近撞车的可能性。在同一个人之间,特别是在单个驾驶事件中,观察到与速度选择行为显着相关。显示平均速度随速度限制而增加。但是,这些增加在较高的速度限制下不太明显。在不利的天气条件下,尤其是在严重拥堵的情况下,驾驶员倾向于降低沿水平或垂直曲线的行驶速度。平均行驶速度的增加和行驶速度的变化都增加了撞车的风险。垂直曲线和坡道交界处以及最年轻和最年长的驾驶员群体中的碰撞风险也增加了。本研究最终证明了如何利用自然驾驶数据来检查驾驶员行为并研究感兴趣的问题通过其他经验设置很难或不切实际。结果还提供了重要的见解,可以使驾驶员更好地理解驾驶员如何根据公布的速度限制和其他道路特征来调整速度选择行为。

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    Hamzeie, Raha;

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  • 年度 2016
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