Rigid and composite pavement index-based performance models for network pavement management system in the state of Louisiana

被引:9
|
作者
Khattak, Mohammad Jamal [1 ]
Landry, Corey [1 ]
Veazey, Jared [1 ]
Zhang, Zhongjie [2 ]
机构
[1] Univ Louisiana Lafayette, Dept Civil Engn, Lafayette, LA 70504 USA
[2] Louisiana Transportat Res Ctr, Baton Rouge, LA 70808 USA
关键词
PMS; performance models; network level; flexible pavements;
D O I
10.1080/10298436.2012.715643
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
The Louisiana Department of Transportation and Development (LADOTD) in conjunction with the Federal Highway Administration initiated a study to evaluate the existing Pavement Management System (PMS) of LADOTD. The study evaluated and updated the performance models for different pavement types and highway classifications as used by LADOTD. This paper discusses the development of index-based rigid and composite pavement models. Distress data collected over the last 10 years at 2-year intervals were sorted based on control sections, distress type, pavement type and four new LADOTD highway classifications: Interstate, National, State and Regional Highway System. The data were sorted and analysed based on the historical records of the construction/reconstruction and resurfacing year. Regression analyses were conducted and a methodology was adopted to develop generalised models, based on the fundamental concept of pavement rate of deterioration as a function of age. The newly developed models provide good prediction capabilities that will assist in assessing the deterioration of pavements. It is believed that improving the performance models will enhance the efficiency of the PMS of LADOTD.
引用
收藏
页码:612 / 628
页数:17
相关论文
共 50 条
  • [21] Developing Network Slurry Seal Performance Models Using Pavement Management Systems Data
    Cheng, DingXin
    Smith, Roger E.
    Tan, Sui G.
    Jaquiz, Mario
    Chang, Carlos M.
    TRANSPORTATION RESEARCH RECORD, 2022, 2676 (09) : 389 - 396
  • [22] APPLICATION OF AN ARTIFICIAL NEURAL NETWORK IN A PAVEMENT MANAGEMENT SYSTEM
    Dragovan, Hrvoje
    Rukavina, Tatjana
    Domitrovic, Josipa
    ROAD AND RAIL INFRASTRUCTURE III, 2014, : 211 - 217
  • [23] Developing Pavement Distress Deterioration Models for Pavement Management System Using Markovian Probabilistic Process
    Saha, Promothes
    Ksaibati, Khaled
    Atadero, Rebecca
    ADVANCES IN CIVIL ENGINEERING, 2017, 2017
  • [24] Application of an Artificial Neural Network in Pavement Management System
    Domitrovic, Josipa
    Dragovan, Hrvoje
    Rukavina, Tatjana
    Dimter, Sanja
    TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2018, 25 : 466 - 473
  • [25] A performance-based Pavement Management System for the road network of Montreal city-a conceptual framework
    Amin, Md Shohel Reza
    Amador-Jimenez, Luis E.
    ASPHALT PAVEMENTS, VOLS 1 AND 2, 2014, : 233 - 244
  • [26] Fatigue Performance of Interlaminar Anticracking Material for Rigid-Flexible Composite Pavement
    Liu, Li
    Liu, Zhaohui
    Liu, Jingyu
    Li, Sheng
    JOURNAL OF MATERIALS IN CIVIL ENGINEERING, 2016, 28 (10)
  • [27] Application of network-level pavement management system technology to a unique pavement deterioration problem
    Helali, K.
    Kazmierowski, T.J.
    Bradbury, A.
    Karan, M.A.
    Transportation Research Record, 1996, (1524): : 67 - 75
  • [28] Pavement management system based on financial consequence
    Bemanian, Sohila
    Polish, Patty
    Maurer, Gayle
    PAVEMENT MANAGEMENT; MONITORING, EVALUATION, AND DATA STORAGE; AND ACCELERATED TESTING 2005, 2005, (1940): : 32 - 37
  • [29] Road network pavement maintenance optimisation using the HDM-4 pavement performance prediction models
    Jorge, Diana
    Ferreira, Adelino
    INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING, 2012, 13 (01) : 39 - 51
  • [30] Evaluation of Pavement Performance Models Using Historical Condition Data for the US National Parks Pavement Network
    Bryce, James
    Nichols, Andrew
    Elias, Mohammed
    Maloche, Anthony
    Sivaneswaran, Nadarajah
    Canick, Thomas
    TRANSPORTATION RESEARCH RECORD, 2023, 2677 (09) : 188 - 198