Montella Alfonso, Mauriello Filomena, Pernetti Mariano, Rella Riccardi Maria
University of Naples Federico II, Department of Civil, Architectural and Environmental Engineering, Via Claudio 21, 80125, Naples, Italy.
University of Campania Luigi Vanvitelli, Department of Engineering, Via Roma 29, 81031, Aversa, CE, Italy.
Accid Anal Prev. 2021 Jun;155:106119. doi: 10.1016/j.aap.2021.106119. Epub 2021 Apr 10.
The main objective of this paper was to analyse the roadway, environmental, and driver-related factors associated with an overrepresentation of frequency and severity of run-off-the-road (ROR) crashes. The data used in this study refer to the 6167 crashes occurred in the section Naples-Candela of A16 motorway, Italy in the period from 2001 to 2011. The analysis was carried out using the rule discovery technique due to its ability of extracting knowledge from large amounts of data previously unknown and indistinguishable by investigating patterns that occur together in a given event. The rules were filtered by support, confidence, lift, and validated by the lift increase criterion. A two-step analysis was carried out. In the first step, rules discovering factors contributing to ROR crashes were identified. In the second step, studying only ROR crashes, rules discovering factors contributing to severe and fatal injury (KSI) crashes were identified. As a result, 94 significant rules for ROR crashes and 129 significant rules for KSI crashes were identified. These rules represent several combinations of geometric design, roadside, barrier performance, crash dynamic, vehicle, environmental and drivers' characteristics associated with an overrepresentation of frequency and severity of ROR crashes. From the methodological point of view, study results show that the a priori algorithm was effective in providing new information which was previously hidden in the data. Finally, several countermeasures to solve or mitigate the safety issues identified in this study were discussed. It is worthwhile to observe that the study showed a combination of factors contributing to the overrepresentation of frequency and severity of ROR crashes. Consequently, the implementation of a combination of countermeasures is recommended.
本文的主要目的是分析与冲出道路（ROR）碰撞事故的频率和严重程度过高相关的道路、环境和驾驶员相关因素。本研究使用的数据涉及2001年至2011年期间在意大利A16高速公路那不勒斯-坎德拉路段发生的6167起碰撞事故。由于规则发现技术能够通过调查给定事件中共同出现的模式，从大量以前未知且无法区分的数据中提取知识，因此使用该技术进行了分析。通过支持度、置信度、提升度对规则进行筛选，并通过提升度增加标准进行验证。进行了两步分析。第一步，确定导致ROR碰撞事故的因素的规则。第二步，仅研究ROR碰撞事故，确定导致严重和致命伤害（KSI）碰撞事故的因素的规则。结果，确定了94条关于ROR碰撞事故的重要规则和129条关于KSI碰撞事故的重要规则。这些规则代表了与ROR碰撞事故的频率和严重程度过高相关的几何设计、路边、护栏性能、碰撞动力学、车辆、环境和驾驶员特征的几种组合。从方法论的角度来看，研究结果表明先验算法有效地提供了以前隐藏在数据中的新信息。最后，讨论了几种解决或减轻本研究中确定的安全问题的对策。值得注意的是，该研究表明了导致ROR碰撞事故的频率和严重程度过高的多种因素的组合。因此，建议实施多种对策的组合。
