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Title:

Piecewise Multiple Linear Models for Pavement Marking Retroreflectivity Prediction Under Effect of Winter Weather Events

Accession Number:

01595000

Record Type:

Component

Availability:

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Order URL: http://worldcat.org/isbn/9780309441230

Abstract:

Most existing models for prediction of pavement marking retroreflectivity have been developed from data collected in locations with similar weather conditions; therefore, the effect of different weather conditions, such as winter weather events, has not been extensively studied. This study develops degradation models that can predict retroreflectivity of durable pavement marking materials under various winter weather conditions. Piecewise multiple linear models are proposed to explicitly account for the effect of winter weather events in this study. In comparisons of the proposed models with conventional multiple linear models (MLMs) developed from the same set of data, the proposed models outperformed the MLMs, and the overall root-mean-square error improved from 204.6 mcd/m2/lux for MLMs to 106.5 mcd/m2/lux for piecewise MLMs. The proposed models also show robust and consistent results in predicting retroreflectivity of different materials in different states. The results indicate that the proposed method can be adopted by various states and regions for comprehensive retroreflectivity prediction under various weather conditions.

Monograph Accession #:

01594661

Report/Paper Numbers:

16-2425

Language:

English

Authors:

Wang, Chieh
Wang, Zhaohua
Tsai, Yi-Chang

Pagination:

pp 52–61

Publication Date:

2016

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 2551
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

9780309441230

Media Type:

Print

Features:

Figures (3) ; References (26) ; Tables (5)

Subject Areas:

Highways; Maintenance and Preservation; Pavements

Files:

PRP, TRIS, TRB, ATRI

Created Date:

Jan 12 2016 5:04PM

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