Road departments in developing areas are responsible for the maintenance of extensive rural road networks, consisting largely of unpaved roads in poor condition. The increase in traffic and the limited funds available have contributed to a need to formalize the identification and prioritization of regravelling and betterment projects of the lower category roads in particular. A method based on the visual evaluation of relevant aspects of unpaved roads is presented. This visual assessment method is incorporated into an algorithm to produce regravelling and betterment maintenance indices. Consistency of results was verified in a validation of the methodology by a panel of engineers and senior personnel involved with road maintenance. Finally, to generalize the algorithm, tranic volumes are taken into account in calculating the priority indices. Guidance is given for the general implementation of this method and algorithm.
This paper detailed an investigation in which archival data for some selected Natal soils were used to evaluate the existing mathematical and graphical prediction models for the California bearing ratio (CBR). It descriptionbed how the relationships between CBR and various classification parameters (in both simple and multivariate forms) were further examined when these existing models were found to be generally unsatisfactory, and then discussed the lack of any suitable correlations in the data capable of providing a universally applicable prediction model. The good relationship between CBR and maximum swell was examined, further research into the influence of the clay fraction on CBR prediction was reported and the interim use of the shrinkage and grading moduli to obtain minimum CBR values for shrinking and non-shrinking soils respectively was proposed.