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R L Lytton

Bio: R L Lytton is an academic researcher. The author has contributed to research in topics: Pavement management & Ranking (information retrieval). The author has an hindex of 2, co-authored 3 publications receiving 77 citations.

Papers
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01 Jan 1987
TL;DR: In this paper, Latton et al. presented concepts of pavement performance prediction and modeling, and proposed development of pavement prediction models from shrp/ltpp data (rauhut,jb and gendell,ds); predictive pavement condition program in the Washington state pavement management system (jackson,nc, kay,rk and peters,aj); a rating system for unsurfaced roads to be used in maintenance management (eaton,ra, gerard,s and dattilo,rs); pavement prediction and risk modelling in rehabilitation budget planning in rehabilitation
Abstract: Papers presented at this session include: concepts of pavement performance prediction and modeling (lytton,rl); proposed development of pavement performance prediction models from shrp/ltpp data (rauhut,jb and gendell,ds); predictive pavement condition program in the Washington state pavement management system (jackson,nc, kay,rk and peters,aj); a rating system for unsurfaced roads to be used in maintenance management (eaton,ra, gerard,s and dattilo,rs); pavement performance prediction and risk modelling in rehabilitation budget planning : a markovian approach (cook,wd and kazakov,a); development of pavement performance curves for the Iowa Department of Transportation (cable,jk and suh,yc); a Norwegian model for prediction of pavement deterioration (bertelsen,d); pavement performance prediction model (gschwendt,i, poliacek,i and lehovec,f); mn/dot's implementation of a pavement life prediction model (hill,ld); impacts of studded tyres and their role in pavement management (isotalo,j). For the covering abstract of the conference see IRRD 807044.

58 citations

01 Jan 1987
TL;DR: Papers presented at this session include a micro-computer Markov dynamic programming system for pavement management in Finland and a computationally efficient system for infrastructure management with application to pavement management.
Abstract: Papers presented at this session include: recent developments and potential future directions in ranking and optimization procedures for pavement management (cook,wd and lytton,rl); sample size selection (scullion,t, lytton,rl and templeton,cj); the economic optimization of pavement maintenance and rehabilitation policy (markow,mj, brademeyer,bd and sherwood,j); achieving efficiency in planning and programming through network-level policy optimization and pavement management (paterson,wdo and fossberg,pe); a dynamic programming approach to optimization for pavement management systems (feighan,kj, shahin,my and sinha,kc); a decomposition approach for rehabilitation and maintenance programming (gendreau,m); a computationally efficient system for infrastructure management with application to pavement management (nesbitt,dm and sparks,ga); a micro-computer Markov dynamic programming system for pavement management in Finland (thompson,pd, neumann,la and miettinen,m). For the covering abstract of the conference see IRRD 807044.

1 citations


Cited by
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Journal ArticleDOI
TL;DR: In this paper, a nonhomogeneous Markov Probabilistic model is developed to determine pavement deterioration rates in different stages, where the transition probability matrices (TPMs) are considered as a time-related transition process and each element of the TPM is determined on the basis of a reliability analysis and a Monte Carlo simulation technique.
Abstract: Accurate prediction of pavement deterioration is the most important factor in the determination of pavement repair years and optimization programming of highway network maintenance. The Nonhomogeneous Markov Probabilistic Modeling Program, developed to determine pavement deterioration rates in different stages, is described. In this program the transition probability matrices (TPMs) are considered as a time-related transition process. Each element of the TPMs is determined on the basis of a reliability analysis and a Monte Carlo simulation technique. This avoids the use of the existing conventional methods, which involve taking an average subjective opinion of pavement engineers or observing a large number of multiyear pavement performance data and conducting a number of statistical calculations. As a result a series of TPMs for an individual pavement section for different stages can be determined by running the program. Furthermore, the pavement condition state in terms of a probability vector at each stage (year) is calculated. In applying the models both the predicted actual traffic (in terms of equivalent single axle loads) at each stage and the maximum traffic that the pavement can withstand at each defined pavement condition state interval are considered to be random variables. In addition, the sensitivities of pavement deterioration rates to pavement design parameters, such as traffic growth rate, subgrade strength, and material properties, are studied. Finally, an example of calculating the TPMs for a pavement section located in southeastern Ontario, Canada, is demonstrated. It shows that the sensitivities of the TPMs to traffic growth rate, subgrade deflection, and pavement thickness are significant.

125 citations

Journal ArticleDOI
TL;DR: A novel prediction model for RSL of road pavement using support vector regression (SVR) optimized by particle filter to overcome the challenges is presented and the results show the superiority of the proposed model with a correlation coefficient index equal to 95%.
Abstract: Accurate prediction of the remaining service life (RSL) of pavement is essential for the design and construction of roads, mobility planning, transportation modeling as well as road management syst...

92 citations

Journal ArticleDOI
TL;DR: In this paper, artificial neural networks (ANN) is used in modeling the present serviceability index of the flexible pavements, which can be easily and realistically performed to solve the problems which do not have a formulation or function about the solution.

86 citations

Journal ArticleDOI
TL;DR: Airport pavement management systems (APMS) as mentioned in this paper are computer-based decision support systems that can be used by the agencies running airports to determine cost-effective maintenance and rehabilitation strategies to preserve the various pavement structures (runways, taxiways, etc).
Abstract: Airport pavement management systems (APMS) are computer-based decision support systems that can be used by the agencies running airports to determine cost-effective maintenance and rehabilitation strategies to preserve the various pavement structures (runways, taxiways, etc) which are a critical component of these facilities In this paper, we describe the main elements of APMS and review existing systems

72 citations

Journal ArticleDOI
Abstract: Pavement performance deterioration cannot be predicted precisely because traffic and environmental actions as well as the material properties and geometric variables of pavement systems are uncertain. Therefore, the prediction of the pavement performance should be carried out based on a probabilistic framework. A simple probabilistic approach is developed in this study for predicting pavement performance. The approach is based on a nonhomogenous continuous Markov chain. Its use in conjunction with the flexible pavement deterioration models in the Ontario Pavement Analysis of Cost (OPAC) and in the AASHTO guide is explored. The proposed approach is more efficient than the ones found in the literature since the probability transition matrix in this study depends only on two model parameters, one controlling the intensity of transition and the other controlling the time transformation. The proposed approach seems able to mimic well the pavement degradation process predicted by the OPAC and AASHTO models.

68 citations