农村两车道不分段公路中心线隆隆带安全性评价:干预时间序列分析的应用

IF 3.2 Q3 TRANSPORTATION
Ahmed Hossain , Xiaoduan Sun , Ashifur Rahman , Sushmita Khanal
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引用次数: 2

摘要

中心线隆隆带是安装在高速公路路段中心的一种低成本、有效的对策,可以减少交通事故,特别是道路偏离事故。对于中心线爆震带的安全性评价,目前广泛采用naïve前后分析和实证贝叶斯横断面研究等方法。这些方法的实施可能会受到限制,因为缺乏相关的控制组,和/或崩溃中的其他时间变化,如季节性和序列自相关性。本研究旨在探索干预时间序列分析方法作为路易斯安那州农村双车道不分割高速公路中心线隆隆声带安全性评估的替代方法。在干预时间序列方法中探索了两种不同的方法,包括预测建模技术和自回归综合移动平均干预模型。预测模型基于指数平滑技术、状态空间框架和神经网络模型。该数据库包括在2010年至2012年期间对312条总长1274英里的高速公路路段的总碰撞和目标碰撞的月度观察,这些路段安装了中心线防撞带。2005-2012年为干预前阶段,2013-2017年为干预后阶段。分析表明,自回归综合移动平均干预模型在均方根误差、平均绝对误差和平均绝对百分比误差等误差估计方面表现较好。提出的自回归综合移动平均干预模型显示,在干预后,所选择的农村双车道未分割公路路段的总碰撞减少率为17.75%,目标碰撞减少率为40.54%。所有研究结果在95%的置信水平上具有统计学意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Safety evaluation of centerline rumble strips on rural two-lane undivided highways: Application of intervention time series analysis

Centerline rumble strips are low-cost effective countermeasures installed on the center of the highway segments to reduce crashes, especially roadway departure crashes. For safety evaluation of centerline rumble strips, methodologies such as naïve before-after analysis and cross-sectional study with Empirical Bayes have been widely utilized. The implementation of these methodologies may be limited due to the lack of relevant control groups, and/or other temporal variations in crashes such as seasonality and serial autocorrelation. This study aims to explore Intervention Time Series Analysis approach as an alternative method for the safety evaluation of centerline rumble strips on rural-two-lane undivided highways in Louisiana. Two different methodologies are explored in the intervention time series approach including the Forecast modeling technique and the Auto-regressive Integrated Moving Average intervention model. The forecast models are based on the exponential smoothing technique, state-space framework, and neural network model. The database consists of monthly observations of total and target crashes on 312 highway segments of 1274 miles in length in which centerline rumble strips were installed during the 2010–2012 period. The time frame 2005–2012 is defined as the pre-intervention period whereas the time frame 2013–2017 is defined as the post-intervention period. The analysis revealed that the Auto-regressive Integrated Moving Average intervention model performed better in terms of error estimates including root means square error, mean absolute error, and mean absolute percentage error. The proposed Auto-regressive Integrated Moving Average intervention model reveals a 17.75% total and 40.54% target crash reduction on the selected rural-two-lane undivided highway segments during the post-intervention period. All the findings are found statistically significant at a 95% confidence level.

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来源期刊
IATSS Research
IATSS Research TRANSPORTATION-
CiteScore
6.40
自引率
6.20%
发文量
44
审稿时长
42 weeks
期刊介绍: First published in 1977 as an international journal sponsored by the International Association of Traffic and Safety Sciences, IATSS Research has contributed to the dissemination of interdisciplinary wisdom on ideal mobility, particularly in Asia. IATSS Research is an international refereed journal providing a platform for the exchange of scientific findings on transportation and safety across a wide range of academic fields, with particular emphasis on the links between scientific findings and practice in society and cultural contexts. IATSS Research welcomes submission of original research articles and reviews that satisfy the following conditions: 1.Relevant to transportation and safety, and the multiple impacts of transportation systems on security, human health, and the environment. 2.Contains important policy and practical implications based on scientific evidence in the applicable academic field. In addition to welcoming general submissions, IATSS Research occasionally plans and publishes special feature sections and special issues composed of invited articles addressing specific topics.
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