2020
DOI: 10.1016/j.aap.2020.105669
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Modeling crash risk of horizontal curves using large-scale auto-extracted roadway geometry data

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Cited by 21 publications
(9 citation statements)
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“…Therefore, they allow vehicles to adjust their direction of travel gradually. However, changes in the geometry of highway sections with an H curve often pose safety concerns (Sil, Nama,, Maji, & Maurya, 2020); (Ma, Yang, Wang, Xie, & Yang, 2020). Sharp turns have been known to cause driver instability (positioning themselves on a passing line), leading to a collision.…”
Section: Horizontal Archmentioning
confidence: 99%
“…Therefore, they allow vehicles to adjust their direction of travel gradually. However, changes in the geometry of highway sections with an H curve often pose safety concerns (Sil, Nama,, Maji, & Maurya, 2020); (Ma, Yang, Wang, Xie, & Yang, 2020). Sharp turns have been known to cause driver instability (positioning themselves on a passing line), leading to a collision.…”
Section: Horizontal Archmentioning
confidence: 99%
“…Zhang et al [35] highlighted the effectiveness of in-vehicle data, such as lateral and longitudinal stability indicators, in assessing the road crash risk. Ma et al [13] demonstrated the significance of including elevation features to address the confounding impact of vertical curves along H-curves. Finally, Ding et al [46] stressed the importance of incorporating visual perception, including speed risk perception and distance risk perception, and suggested the potential application of line markings.…”
Section: Research Outcomesmentioning
confidence: 99%
“…Put simply, some researchers concentrate on enhancing the overall safety of an entire traffic network or a specific region [8,9], such as downtown New York City. Others address crash-related issues occurring on highway segments [10], on ramp/off ramp sections [11], weaving areas [12], and curved segments [13]. Additionally, efforts have been made to improve safety at intersections [14].…”
Section: Introductionmentioning
confidence: 99%
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“…To evaluate the effectiveness of friction treatments in improving traffic safety on curves, researchers have developed safety prediction models to quantify the relationship between curve crash frequency and curve geometry, pavement skid resistance, pavement characteristics, wet-weather conditions, and so forth ( 8 10 ). However, because of the scarcity of curve-related crash data, coupled with the large number of variables involved and the highly varied operating conditions under which crashes occur, statistical empirical equations have not been found satisfactory in establishing the safety effectiveness of different friction improvement treatments ( 11 , 12 ).…”
mentioning
confidence: 99%