Assessing Critical Road Sections : A Decision Matrix Approach Considering Safety and Pavement Condition

Angelo, Asnake Adraro; Sasai, Kotaro; Kaito, Kiyoyuki

Sustainability, 2023, 15(9), 7244

アクセス数:7件（2026-02-15 23:21 集計）

固定URL: https://hdl.handle.net/11094/103654

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タイトル
Assessing Critical Road Sections : A Decision Matrix Approach Considering Safety and Pavement Condition
著者
ORCID
0000-0003-1494-4304 0000-0003-1494-4304
researchmap permalink
AsnakeAngelo AsnakeAngelo
Scopus Author ID
58249514600 58249514600
著者名
Angelo, Asnake Adraro
著者名
Sasai, Kotaro
NRID
1000030467550 1000030467550
researchmap permalink
asset-metrics asset-metrics
Scopus Author ID
7006682889 7006682889
著者名
Kaito, Kiyoyuki
キーワード等
critical road sections
decision matrix
mixed Markov hazard model
pavement deterioration
road maintenance
road safety
traffic crash
内容
Angelo A.A., Sasai K., Kaito K.. Assessing Critical Road Sections: A Decision Matrix Approach Considering Safety and Pavement Condition. Sustainability (Switzerland) 15, 7244 (2023); https://doi.org/10.3390/su15097244.
抄録
Identifying critical road sections that require prompt attention is essential for road agencies to prioritize monitoring, maintenance, and rehabilitation efforts and improve overall road conditions and safety. This study suggests a decision matrix with a hierarchical structure that factors in the pavement deterioration rate, infrastructure safety, and crash history to identify these sections. A Markov mixed hazard model was used to assess each section’s deterioration rate. The safety of the road sections was rated with the International Road Assessment Program star rating protocol considering all road users. Early detection of sections with fast deterioration and poor safety conditions allows for preventive measures to be taken and to reduce further deterioration and traffic crashes. Additionally, including crash history data in the decision matrix helps to understand the possible causes of a crash and is useful in developing safety policies. The proposed method is demonstrated using data from 4725 road sections, each 100 m, in Addis Ababa, Ethiopia. The case study results show that the proposed decision matrix can effectively identify critical road sections which need close attention and immediate action. As a result, the proposed method can assist road agencies in prioritizing inspections, maintenance, and rehabilitation decisions and effectively allocate budgets and resources.
出版者
MDPI
収録物名
Sustainability
巻(号)
15(9)
ページ
7244
刊行年月
2023-04-26
言語
英語
ハンドルURL
https://hdl.handle.net/11094/103654
eISSN
20711050
関連情報 (isIdenticalTo)
DOI (出版社版)
https://doi.org/10.3390/su15097244
アクセス権
open access
権利情報
This article is licensed under a Creative Commons Attribution 4.0 International License.
出版タイプ
Version of Record
カテゴリ
学術雑誌論文 Journal Article