The significance of endogeneity problems in crash models: an examination of left-turn lanes in intersection crash models

Kim, Do-Gyeong and Washington, Simon (2006) The significance of endogeneity problems in crash models: an examination of left-turn lanes in intersection crash models. Accident Analysis and Prevention, 38 6: 1094-1100. doi:10.1016/j.aap.2006.04.017


Author Kim, Do-Gyeong
Washington, Simon
Title The significance of endogeneity problems in crash models: an examination of left-turn lanes in intersection crash models
Journal name Accident Analysis and Prevention   Check publisher's open access policy
ISSN 0001-4575
1879-2057
Publication date 2006-11-01
Sub-type Article (original research)
DOI 10.1016/j.aap.2006.04.017
Open Access Status Not yet assessed
Volume 38
Issue 6
Start page 1094
End page 1100
Total pages 7
Place of publication Langford Lane, Oxford, United Kingdom
Publisher Elsevier
Language eng
Abstract Crash prediction models are used for a variety of purposes including forecasting the expected future performance of various transportation system segments with similar traits. The influence of intersection features on safety have been examined extensively because intersections experience a relatively large proportion of motor vehicle conflicts and crashes compared to other segments in the transportation system. The effects of left-turn lanes at intersections in particular have seen mixed results in the literature. Some researchers have found that left-turn lanes are beneficial to safety while others have reported detrimental effects on safety. This inconsistency is not surprising given that the installation of left-turn lanes is often endogenous, that is, influenced by crash counts and/or traffic volumes. Endogeneity creates problems in econometric and statistical models and is likely to account for the inconsistencies reported in the literature. This paper reports on a limited-information maximum likelihood (LIML) estimation approach to compensate for endogeneity between left-turn lane presence and angle crashes. The effects of endogeneity are mitigated using the approach, revealing the unbiased effect of left-turn lanes on crash frequency for a dataset of Georgia intersections. The research shows that without accounting for endogeneity, left-turn lanes 'appear' to contribute to crashes; however, when endogeneity is accounted for in the model, left-turn lanes reduce angle crash frequencies as expected by engineering judgment. Other endogenous variables may lurk in crash models as well, suggesting that the method may be used to correct simultaneity problems with other variables and in other transportation modeling contexts.
Keyword Angle crashes
Endogeneity
Left-turn lane indicator
Limited-information maximum likelihood estimation
Q-Index Code C1
Q-Index Status Provisional Code
Institutional Status Non-UQ

Document type: Journal Article
Sub-type: Article (original research)
Collection: School of Civil Engineering Publications
 
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