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利用实时交通数据评估匝道控制对高速公路安全的影响。

Evaluating the effect of ramp metering on freeway safety using real-time traffic data.

机构信息

Department of Civil & Environmental Engineering, Florida International University, 10555 West Flagler Street, Miami, FL, 33174, USA.

School of Engineering, University of North Florida, 1 UNF Drive, Jacksonville, FL, 32224, USA.

出版信息

Accid Anal Prev. 2021 Jul;157:106181. doi: 10.1016/j.aap.2021.106181. Epub 2021 May 18.

Abstract

Ramp metering relieves traffic congestion, reduces delay, and maintains the capacity flow on freeways. Due to its operational mechanism, ramp metering can also improve freeway safety. While the operational benefits of ramp metering have extensively been quantified, research on its safety effects is sparse. This study focused on evaluating the effects of ramp metering on the safety performance of the freeway mainline. It developed a crash risk prediction model for segments downstream of the entrance ramps when ramp metering is activated. The study was based on a corridor with system-wide ramp metering along I-95 in Miami, Florida. Real-time traffic, crash, and ramp metering operations data collected from 2016 to 2018 were used in the analysis. The study adopted a matched crash and non-crash case approach to evaluate the crash risk when ramp meters were activated and deactivated. A penalized logistic regression model was developed using a bootstrap resampling technique to estimate the effects of ramp metering activation and select important variables that could predict crash risk when ramp meters were activated. Results indicated that ramp metering improves safety along the freeway corridor by reducing the crash risk downstream of the entrance ramps. During ramp metering activation, the crash risk on segments downstream of the entrance ramps 5 min later can be predicted using the difference in the average lane speeds between upstream and downstream detectors, the average traffic volume in the lanes at the downstream and upstream detectors, and the coefficient of variation of speed between lanes in the upstream detectors. Also, the coefficient of variation of occupancy downstream could predict the crash risk 15 min later. The study results could be used by transportation agencies when evaluating the deployment of ramp meters. Moreover, the developed crash risk prediction model could be used in real-time to help agencies identify the increased crash risk and provide appropriate warning information to the upstream traffic.

摘要

匝道控制可缓解交通拥堵、减少延误并维持高速公路的容量流。由于其运行机制,匝道控制还可以提高高速公路的安全性。尽管匝道控制的运行效益已经得到了广泛的量化,但对其安全效果的研究却很少。本研究重点评估了匝道控制对高速公路主线安全性能的影响。它开发了一个在入口匝道处匝道控制激活时下游路段的碰撞风险预测模型。该研究基于佛罗里达州迈阿密的 I-95 全线匝道控制系统的走廊。从 2016 年到 2018 年,收集了实时交通、碰撞和匝道控制操作数据,并用于分析。该研究采用了匹配的碰撞和非碰撞案例方法来评估在匝道控制激活和停用时的碰撞风险。采用bootstrap 重采样技术开发了一个惩罚逻辑回归模型,以估计匝道控制激活的效果并选择在匝道控制激活时可以预测碰撞风险的重要变量。结果表明,匝道控制通过降低入口匝道下游的碰撞风险来提高高速公路走廊的安全性。在匝道控制激活期间,可以使用上游和下游检测器之间的平均车道速度差、下游和上游检测器处车道的平均交通量以及上游检测器中车道之间速度变化系数来预测 5 分钟后入口匝道下游路段的碰撞风险。此外,下游占有率的变化系数可以预测 15 分钟后的碰撞风险。这些研究结果可用于运输机构在评估匝道控制的部署时参考。此外,开发的碰撞风险预测模型可以实时使用,以帮助机构识别增加的碰撞风险并为上游交通提供适当的警告信息。

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