The Influence of Correclation on the Extreme Traffic Loading of Bridges

Accurate traffic loading models based on measured data are essential for the accurate assessment
of existing bridges. There are well-established methods for the Monte Carlo simulation of single lanes
of traffic, and this can easily be extended to model the loading on bridges with two independent streams of
traffic in opposing directions. However, a typical highway bridge will have multiple lanes in the same direction,
and various types of correlation are evident in measured traffic. This paper analyses traffic patterns using
multi-lane WIM data collected at two European sites. It describes an approach to the Monte Carlo simulation
of this traffic which applies variable bandwidth kernel density estimators to empirical traffic patterns of vehicle
weights, gaps and speeds. This method provides a good match with measured data for multi-truck bridge
loading events, and it is shown that correlation has a small but significant effect on lifetime maximum load effects.