RT info:eu-repo/semantics/article
T1 Transition probability matrices for pavement deterioration modelling with variable duty cycle times
A1 Alonso-Solorzano, Ángela
A1 Pérez Acebo, Heriberto
A1 Findley, Daniel J.
A1 Gonzalo Orden, Hernán
K1 Pavement performance model
K1 Probabilistic model
K1 Homogeneous Markov chain
K1 International Roughness Index
K1 Pavement management system
K1 Pavimentos
K1 Pavements
K1 Carreteras
K1 Roads
AB Probabilistic pavement models, with Markov chains as the most widely used type, are considered to capture an accurate representation of the in situ pavement performance. Homogeneous Markov chain models present the same transition probability matrix (TPM) for all the transitions of the period and require data from multiple duty cycles of one or two years. The aim of this paper is to explore the feasibility of developing homogeneous Markov chain models with variations of the duty cycle (in increments of either one or two years). Without considering maintenance and rehabilitation works, this research found that TPMs for a one-year duty cycle can be calculated from the two-year duty cycle, without a noticeable effect on accuracy using International Roughness Index (IRI) values from the Spanish State Road Network. However, for developing coherent TPMs, two primary assumptions were made: (1) heavy vehicle traffic volumes determine the traffic category (TC), and (2) only roads from the same climatic region were modelled. The satisfactory results verified the validity of the methodology and overcame the disadvantages of homogeneous Markov models. Furthermore, the results suggest that pavement sections are adequately designed in Spain for each TC because of the similar deterioration patterns.
PB Taylor and Francis
SN 1029-8436
YR 2023
FD 2023-11
LK http://hdl.handle.net/10259/9860
UL http://hdl.handle.net/10259/9860
LA eng
DS Repositorio Institucional de la Universidad de Burgos
RD 21-ene-2025