Crash-Prone Section Identification for Mountainous Highways Considering Multi-Risk Factors Coupling Effect

Joint Authors

Wen, Huiying
Xue, Gang

Source

Journal of Advanced Transportation

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-12-31

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Civil Engineering

Abstract EN

In order to identify crash-prone sections of the highways in mountainous areas professionally and exclusively, the common phenomena of “sharp turns”, “continuous long downhill”, “multiple tunnels”, “dangerous roadside environment”, and complex and changeable meteorological environment, which all imply risk factors of the mountainous highways, are comprehensively considered.

Utilizing the improved classical coupling model, the coupling mechanism of the risk factors is revealed, and the coupling model of the traffic risk factors is constructed, by which the coupling degrees of multi-risk factors couplings are calculated respectively.

Based on the coupling degrees of the above factors, the concept of vehicle operation risk index (VORI) of the mountainous highway is introduced and its numerical value is quantified as the basis for identifying the crash-prone sections.

The 21 km of Songming to Huize section of the Songdai Highway in the Yunnan Province of China is selected as an example, and the good applicability of the identification model is verified.

American Psychological Association (APA)

Xue, Gang& Wen, Huiying. 2019. Crash-Prone Section Identification for Mountainous Highways Considering Multi-Risk Factors Coupling Effect. Journal of Advanced Transportation،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1170370

Modern Language Association (MLA)

Xue, Gang& Wen, Huiying. Crash-Prone Section Identification for Mountainous Highways Considering Multi-Risk Factors Coupling Effect. Journal of Advanced Transportation No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1170370

American Medical Association (AMA)

Xue, Gang& Wen, Huiying. Crash-Prone Section Identification for Mountainous Highways Considering Multi-Risk Factors Coupling Effect. Journal of Advanced Transportation. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1170370

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1170370