A Novel Approach for Urban Road Network Maintenance Plans Using Spatial Autocorrelation Analysis and Roadside Conditions: A Case Study of Muroran City, Japan

Takumi Asada (), Tran Vinh Ha, Mikiharu Arimura and Shuichi Kameyama
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Takumi Asada: Department of Civil Engineering, Muroran Institute of Technology, Mizumoto, Muroran 050-8585, Japan
Tran Vinh Ha: Department of Civil Engineering, Muroran Institute of Technology, Mizumoto, Muroran 050-8585, Japan
Mikiharu Arimura: Department of Civil Engineering, Muroran Institute of Technology, Mizumoto, Muroran 050-8585, Japan
Shuichi Kameyama: Division of Civil and Environmental Engineering, Hokkaido University of Science, Teine, Sapporo 006-8585, Japan

Sustainability, 2022, vol. 14, issue 23, 1-17

Abstract: Urban and residential roads play an integral role in the infrastructure system of a city. Although they take up a large proportion of the national road network, maintenance plans for urban roads are beset by many problems. These include difficulty in collecting enormous volumes of data, implementing analyses, and interpreting results because of complicated frameworks. Thus, this study aims to introduce an effective and reliable method of formulating a maintenance plan using integrated criteria of spatial autocorrelation analysis and roadside conditions. The results demonstrate that defective pavements are clustered in certain areas, for example, mountainous and forested areas, which indicate environmental effects. Using a mixed index as a criterion for prioritization, approximately 55% of roadside residents (represented by the total residential housing floor area) and 90% of commercial and medical facilities surrounding critical sections gained benefit from maintenance activities in the second year. Importantly, the proposed method presents the advantages of simplifying implications and quantitative outcomes that could support local agents in not only implementing but also making decisions and interpreting such decisions for the community.

Keywords: pavement management system; PMS; urban road; network-level; spatial autocorrelation; socio-political indexes (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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