Analysis of left-turn crash using Poisson Regression model at unsignalized intersections
- 10.2991/iceesd-18.2018.94How to use a DOI?
- unsignalized intersection; left-turn crash; Possion regression model; short left lane
The purpose of this study is to explore the safety performance of short left-turn lanes at unsignalized intersections, where it is often impractical to provide the standard lengths either when the available length between two adjacent opening is inadequate or when heavy left-turn volumes leads to demanding lane length. Left-turn crash data of six years from Houston, Texas of the years 2006-2011 were collected. There were thirty-nine lanes shorter than the standard requirements and thirteen lanes meeting the requirements. A Poisson Regression model was developed to relate traffic and geometric attributes to the total count of rear-end, sideswipe, and object-motor vehicle accidents at a left-turn lane. Furthermore, Crash Modification Factors (CMFs) were calculated for future applications in projecting the crash frequency given a specific change of the lane length. The results shows that short left-turn lanes have negative safety impacts. The study finally puts forward the opinion to improve the present conditions at the left-turn unsignalized intersection.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Liyan Qin AU - Yan Lu AU - Shuai Zhang PY - 2018/05 DA - 2018/05 TI - Analysis of left-turn crash using Poisson Regression model at unsignalized intersections BT - Proceedings of the 2018 7th International Conference on Energy, Environment and Sustainable Development (ICEESD 2018) PB - Atlantis Press SP - 520 EP - 526 SN - 2352-5401 UR - https://doi.org/10.2991/iceesd-18.2018.94 DO - 10.2991/iceesd-18.2018.94 ID - Qin2018/05 ER -