Safety Effects of Installing Left-Turn Lanes at Signalized Approaches: Traffic Engineering-Based Analysis

Abstract Instead of standard left-turn pockets, compromised configurations such as shared left-turn and through lane or left-turn lane traps catering to urban planners’ planted median design may lead to unsafety. These nonstandard configurations induce unnecessary mandatory or discretionary lane changes that give rise to rear-end and sideswipe risks. This study aims to quantify the safety effects of left-turn lane installation by incorporating traffic engineering elements into the regression formulae. Some challenges are handled: (1) analyzing treatment effects with limited samples; (2) without a safety performance function, applying the proposed “bias-immune window” to account for regression-to-the-mean; and (3) enhancing the quality of estimation, including capturing time trend effects. Apart from difference-in-difference (DD), this study has analyzed the effects of fundamental traffic engineering elements, including continuity of mainstream traffic and mainstream smoothness. Conventional DD yields a crash modification factor (CMF) of installing the left bay on sideswipe collisions with a value of 0.33. Likewise, the proposed method suggests CMF of mainstream continuity from desirable lane configuration on sideswipe with a value of 0.422. On the other hand, although conventional DD failed to determine the treatment effect on rear-end collisions, the proposed engineering-based analysis can identify mainstream smoothness offered by the left-turn bay with a CMF of 0.279. With the quantitative results, traffic engineers have a solid basis for prioritizing left-turn lane installation.

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Publication Details

Journal
Journal of Transportation Engineering Part A Systems
Published
2026-10-15
DOI
https://doi.org/10.1061/jtepbs.teeng-9668
Primary Topic
Traffic and Road Safety
Type
article
Field-Weighted Citation Impact
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article

Safety Effects of Installing Left-Turn Lanes at Signalized Approaches: Traffic Engineering-Based Analysis

Wei San-ya, Yen-Hsiang Chen, Tien‐Pen Hsu, Hsin-Yun Tsai
Journal of Transportation Engineering Part A Systems
Traffic and Road Safety
article

Safety Effects of Installing Left-Turn Lanes at Signalized Approaches: Traffic Engineering-Based Analysis

Wei San-ya, Yen-Hsiang Chen, Tien‐Pen Hsu, Hsin-Yun Tsai
article en

Abstract

Abstract Instead of standard left-turn pockets, compromised configurations such as shared left-turn and through lane or left-turn lane traps catering to urban planners’ planted median design may lead to unsafety. These nonstandard configurations induce unnecessary mandatory or discretionary lane changes that give rise to rear-end and sideswipe risks. This study aims to quantify the safety effects of left-turn lane installation by incorporating traffic engineering elements into the regression formulae. Some challenges are handled: (1) analyzing treatment effects with limited samples; (2) without a safety performance function, applying the proposed “bias-immune window” to account for regression-to-the-mean; and (3) enhancing the quality of estimation, including capturing time trend effects. Apart from difference-in-difference (DD), this study has analyzed the effects of fundamental traffic engineering elements, including continuity of mainstream traffic and mainstream smoothness. Conventional DD yields a crash modification factor (CMF) of installing the left bay on sideswipe collisions with a value of 0.33. Likewise, the proposed method suggests CMF of mainstream continuity from desirable lane configuration on sideswipe with a value of 0.422. On the other hand, although conventional DD failed to determine the treatment effect on rear-end collisions, the proposed engineering-based analysis can identify mainstream smoothness offered by the left-turn bay with a CMF of 0.279. With the quantitative results, traffic engineers have a solid basis for prioritizing left-turn lane installation.

Journal of Transportation Engineering Part A SystemsVol. 152(12)
British Airways (United Kingdom) (GB), National Taiwan University (TW)
Sustainable cities and communities, Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Traffic and Road Safety
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