Analysis of left-turn crash using Poisson Regression model at unsignalized intersections

DOI

10.2991/iceesd-18.2018.94How to use a DOI?

Keywords

unsignalized intersection; left-turn crash; Possion regression model; short left lane

Abstract

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.

Copyright

© 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/).

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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  -