Identification of Statistical Model of
Vehicular Live Load in Long Span Bridges
using WIM data
Chong Hyun Kim
In this paper the statistical model of the vehicular live load on long span bridges reflecting Korean traffic pattern was identified. Traffic jams, which are assumed for live load model on long span bridges, do not always occur in reality. The assumption may lead to excessive conservatism. To reflect actual trafiic patterns, driving situations other than traffic jams were investigated using recently measured traffic data from six different sites in Korea. An extrapolation method using Cramer's asymptotic solution was proposed to estimate maximum load distribution. A method developing multiple presence factors appropriate for long span bridges was discussed. The statistical characteristics of live the load model (Hwang, 2012) was estimated. Bias factor was not uniform according to influence length due to different decreasing rate of load. Site-to-site variability also needed to be considered. A new live load model for long span bridges incorporating the decreasing rates and site-to-site variability was proposed. The lane load was classified into two groups: normal and heavy traffic sites. Load models for influence line length and span length were proposed respectively. The statistical characteristics of the proposed load model and load effects were identified.
Vehicular live load model on long span bridge, Statistical model, Cramer's asymptotic solution, WIM data, Multiple presence factor