Examining the impacts of road pavement roughness and rutting on traffic safety: A macrolevel analysis.

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Tác giả: Chris De Gruyter, Viet N Huynh, Long T Truong

Ngôn ngữ: eng

Ký hiệu phân loại: 627.12 Rivers and streams

Thông tin xuất bản: England : Traffic injury prevention , 2025

Mô tả vật lý:

Bộ sưu tập: NCBI

ID: 186918

OBJECTIVES: Many studies have examined the safety effects of pavement conditions at microscopic and mesoscopic levels, focusing on road segments, intersections, horizontal curves, and tunnels. These studies have often reported mixed safety effects. However, a macrolevel analysis would provide a more comprehensive understanding by considering the safety effects across the entire road network. Despite its potential advantages, there has been limited macrolevel research to examine the effects of pavement conditions on traffic safety. This research explores the impacts of pavement roughness and rutting on traffic safety, using traffic analysis zones (TAZs) and statistical area level 2 (SA2) as spatial units. METHODS: Random parameter negative binomial regression models are estimated using several data sets encompassing traffic crashes, census, traffic, and pavement conditions in Victoria, Australia. RESULTS: Though the effects vary across zones, those with a greater share of arterials and freeways with very poor rutting or roughness generally tend to have more traffic crashes. Additionally, evidence at the SA2 level suggests that a greater share of arterials and freeways with very poor roughness is generally associated with more fatal crashes. CONCLUSIONS: Overall, the findings suggest that improving road conditions by reducing pavement roughness and rutting could enhance safety, from a network perspective. Road authorities should prioritize maintenance and rehabilitation efforts in areas where roughness and rutting are most severe to maximize safety outcomes. In addition, integrating macrolevel models to predict the safety effects of pavement conditions in strategic planning can enable road agencies to plan infrastructure investments more effectively and proactively.
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