A Markov deterioration model for predicting recurrent maintenance of a network of roads: a case study of Niger state, Nigeria.

  • YA Jimoh
  • AY Adama
Keywords: large· and complex system, · condition deterioration, Markov. chain, transition probability matrix.


The parameters of the Markov chain model for predicting the condition of the road at a design · period for· the flexible pavement failures of wheel track rutting, cracks and pot holes were developed for the Niger State· road network . in Nigeria. Twelve sampled candidate roads were each subjected to standard inventory, traffic count and pavement condition study, whose outcome together with the temperature and rainfall characteristics. were used to generate a computerized data base. A Markov transition probabilistic model · (TPM) was subsequently developed. The prevailing condition of each of the three selected parameters were set out in five severity bands and established intervention levels in respect of proportional distribution of the failures across the three geo . political maintenance zones of the network. The TPM was developed by adopting Costello (2005) respective criteria for Mediterranean and cold region climate and weather. The relevance of the outcome for stochastic analysis and design of budget for recurrent maintenance of a road network was highlighted in the paper.

KeYWords: large· and complex system,· condition deterioration, Markov. chain, transition probability matrix.


Journal Identifiers

eISSN: 2437-2110
print ISSN: 0189-9546