Abstract
Traffic loading is the primary factor considered when designing a pavement. Accurate estimation of traffic load plays a crucial role in the economical design of pavements. The cross-sectional distribution of the vehicle positions means that the traffic load is spread across the surface of the pavement. It is suggested in some design guides that the spread of the traffic load across the pavement surface should be considered alongside the standard axle loading the pavement will need to carry over its lifespan. Several factors influence the distribution of vehicle positions and hence load. However, there is little guidance on how to predict the spread of traffic loads when designing a new pavement, and empirical studies supporting any such guidance is also limited. When wheel paths are perfectly aligned with each other, this is termed channelised traffic (or channelisation). The first part of this research addressed this gap through analyses of data collected on the vehicle positions at 100 sections of pavement in Portsmouth, United Kingdom. The analyses, found a positive linear association between the degree of lateral wander and both the lane width and road width. These results suggest that the use of a binary measure of vehicle position used in the UK design guidance may not be suitable. The results also highlight the importance of both lane and road width, contrary to the existing body of research that indicates only one or the other to be a determinant of vehicle position. The second part of this research focused on investigating the impact of channelisation on asphalt pavement rutting. Regression analysis was conducted to understand how the degree of channelisation influenced the rut depths that the traffic loading had created. The analyses revealed that the degree of channelisation of traffic has a statistically significant contribution to the progress of rutting. In this study, the difference between the maximum and minimum degrees of channelisation observed, related to a seven-fold difference in the rut depth. The last part of this research aimed to combine these findings to suggest ways of considering road geometry to produce a channelisation factor to be incorporated into the calculation of the traffic load for pavement design. This was achieved by combining the two predictive equations developed from regression analyses.These findings have practical contributions to give further guidance to pavement engineers when designing new pavements and considering the maintenance schedules for existing pavements, as it allows them to better predict the future condition and lifespan of a pavements.
| Date of Award | Apr 2020 |
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| Original language | English |
| Awarding Institution |
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| Supervisor | Nikos Nanos (Supervisor), Lee Woods (Supervisor) & Stephanie Barnett (Supervisor) |