Modeling same-direction two-lane traffic for bridge loading

Many highway bridges carry traffic in two same-direction lanes, and modeling the traffic loading on such bridges has been the subject of numerous studies. Different assumptions have been used to model multiple-presence loading events, particularly those featuring one truck in each lane. Using a database of weigh-in-motion measurements collected at two European sites for over 1 million trucks, this paper examines the relationships between adjacent vehicles in both lanes in terms of vehicle weights, speeds and inter-vehicle gaps. It is shown that there are various patterns of correlation, some of which are significant for bridge loading. A novel approach to the Monte Carlo simulation of such traffic is presented which is relatively simple to apply. This is a form of smoothed bootstrap in which kernel functions are used to add randomness to measured traffic scenarios. It is shown that it gives a better fit to the measured data than models which assume no correlation. Results are presented from long-run simulations of traffic using the different models and these show that correlation may account for an increase of up to 8% in lifetime maximum loading.

► Models bridge loading from traffic in two same-direction lanes.
► Identifies significant patterns of correlation in weigh-in-motion data.
► Uses kernel density estimators to add randomness to measured traffic scenarios.
► Results from Monte Carlo simulation show good fit to measured data.
► Correlation between vehicles may increase lifetime maximum loading by up to 8%.