Cost-Effectiveness Analyses of Maintenance Treatments for Low- and Moderate-Traffic Asphalt Pavements in Tennessee-Reference-Cited by-同舟云学术

Cost-Effectiveness Analyses of Maintenance Treatments for Low- and Moderate-Traffic Asphalt Pavements in Tennessee

Published:2013-08 Issue:8 Volume:139 Page:797-803
ISSN:0733-947X
Container-title:Journal of Transportation Engineering
language:en
Short-container-title:J. Transp. Eng.

Author:

Dong Qiao¹,Huang Baoshan²,Richards Stephen H.³,Yan Xuedong⁴

Affiliation:

1. Postdoctoral Research Associate, Dept. of Civil and Environmental Engineering, Univ. of Tennessee, Knoxville, TN 37996.

2. Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Tennessee, Knoxville, TN 37996 (corresponding author).

3. Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of Tennessee, Knoxville, TN 37996.

4. Professor, School of Traffic and Transportation, Beijing Jiaotong Univ., Bejing, China, 100044.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Transportation,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29TE.1943-5436.0000556

Reference21 articles.

1. Butt A. A. Feighan K. J. Shahin M. Y. and Carpenter S. (1987). “Pavement performance prediction using Markov process.” Transportation Research Record 1123 Transportation Research Board Washington DC 12–19.

2. Darter M. I. Smith R. E. and Shahin M. Y. (1985). “Use of life cycle cost analysis as the basis for determining the cost effectiveness of maintenance and rehabilitation treatments for developing a network level assignment procedure.” Proc. North American Pavement Management Conference Vol. 2 Ontario Ministry of Transportation and Communications Toronto Ontario 7.5–7.18.

3. Evaluation of Effectiveness and Cost-Effectiveness of Asphalt Pavement Rehabilitations Utilizing LTPP Data

4. Elton D. J. and Jung C. H. (1988). “Asphalt pavement evaluation using fuzzy sets.” Transportation Research Record 1196 Transportation Research Board Washington DC 1–6.

5. Priority Rating of Highway Maintenance Needs by Neural Networks

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