Department of Civil and Environmental Engineering, KAIST (Korea Advanced Institute of Science and Technology), 291 Daehak-ro, Yuseong-gu, Daejeon, 305-701, Republic of Korea.
Accid Anal Prev. 2013 Jan;50:713-23. doi: 10.1016/j.aap.2012.06.023. Epub 2012 Jul 12.
Freeway traffic accidents are complicated events that are influenced by multiple factors including roadway geometry, drivers' behavior, traffic conditions and environmental factors. Among the various factors, crash occurrence on freeways is supposed to be strongly influenced by the traffic states representing driving situations that are changed by road geometry and cause the change of drivers' behavior. This paper proposes a methodology to investigate the relationship between traffic states and crash involvements on the freeway. First, we defined section-based traffic states: free flow (FF), back of queue (BQ), bottleneck front (BN) and congestion (CT) according to their distinctive patterns; and traffic states of each freeway section are determined based on actual measurements of traffic data from upstream and downstream ends of the section. Next, freeway crash data are integrated with the traffic states of a freeway section using upstream and downstream traffic measurements. As an illustrative study to show the applicability, we applied the proposed method on a 32-mile section of I-880 freeway. By integrating freeway crash occurrence and traffic data over a three-year period, we obtained the crash involvement rate for each traffic state. The results show that crash involvement rate in BN, BQ, and CT states are approximately 5 times higher than the one in FF. The proposed method shows promise to be used for various safety performance measurement including hot spot identification and prediction of the number of crash involvements on freeway sections.
高速公路交通事故是复杂的事件，受到多种因素的影响，包括道路几何形状、驾驶员行为、交通状况和环境因素。在这些因素中，高速公路上的碰撞事故应该受到强烈影响，因为交通状态代表了由道路几何形状引起的驾驶情况的变化，并导致驾驶员行为的变化。本文提出了一种研究高速公路交通状态与碰撞事故之间关系的方法。首先，我们根据独特的模式定义了基于路段的交通状态：自由流（FF）、队列尾端（BQ）、瓶颈前端（BN）和拥堵（CT）；并根据路段上下游的实际交通数据来确定每个路段的交通状态。接下来，使用上下游的交通测量数据将高速公路碰撞数据与路段的交通状态进行集成。作为一个应用实例研究，我们将该方法应用于 I-880 高速公路的一个 32 英里长的路段。通过整合三年内高速公路碰撞事故和交通数据，我们得到了每种交通状态的碰撞事故发生率。结果表明，BN、BQ 和 CT 状态下的碰撞事故发生率大约是 FF 状态下的 5 倍。该方法有望用于各种安全性能测量，包括热点识别和预测高速公路路段的碰撞事故数量。
