Safety Evaluation of the Combined Effect of Offset Left-Turn Lanes and Flashing-Yellow-Arrow Signals at Signalized Intersections on Multilane Divided Highways in Alabama Using the Empirical Bayes Method

Author:

Biswas Pranesh1ORCID,Kang Min-Wook2ORCID,Rahman Moynur3ORCID

Affiliation:

1. Alabama Department of Transportation, Mobile, AL

2. Department of Civil, Coastal, & Environmental Engineering, University of South Alabama, Mobile, AL

3. Traffic Engineering Department, City of Mobile, Mobile, AL

Abstract

The present study conducted an empirical Bayes (EB) before–after analysis to investigate the combined effects of the offset left-turn lanes and flashing-yellow-arrow (FYA) signals implemented at signalized intersections on multilane, divided highways in Alabama. A total of 35 signalized intersections were selected for the EB safety analysis. Among them, 30 intersections were classified as a reference group and five were classified as a treatment group. The reference group includes intersections which have not undergone any left-turn treatments from the period of 2010 to 2020, while the treatment group includes those improved with offset left-turn lanes and FYA signal implementation concurrently during years in that period. Safety performance functions were developed with data collected at reference-group intersections to predict crashes at such intersections under a no-treatment scenario. A study focus was then given to understanding the change in crash frequency before and after the combined treatments for the treatment-group intersections, using the EB method. Results show that the combined left-turn treatments (i.e., implementing offset left-turn lanes coupled with FYA signals) could reduce different types of crashes effectively. There was a substantial reduction of 27% in total crashes (crash modification factor [CMF] = 0.73), a 43% decrease in left-turn crashes (CMF = 0.57), and a 36% reduction in total injury crashes (CMF = 0.64) after the treatments. These findings were supported by their respective standard errors, which are 0.060, 0.101, and 0.106 for total, left-turn, and total injury crashes, respectively, and all the CMFs are statistically significant at 95% confidence intervals.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3