Long-span bridge traffic loading based on multi-lane traffic micro-simulation. (15th May 2016)

• Record Type: Journal Article
• Authors: Caprani, Colin C.; OBrien, Eugene J.; Lipari, Alessandro
• Is Part Of: Engineering structures. Volume 115(2016:May 15)
• Page Start: 207
• Page End: 219
• Publication Date: 2016-05-15
• Subjects: Long-span bridges -- Traffic loading -- Micro-simulation -- Lane-changing -- Congestion -- Probabilistic modelling; Structural engineering -- Periodicals; Structural analysis (Engineering) -- Periodicals; Construction, Technique de la -- Périodiques; Génie parasismique -- Périodiques; Pression du vent -- Périodiques; Earthquake engineering; Structural engineering; Wind-pressure; Periodicals; 624.105
• DOI: 10.1016/j.engstruct.2016.01.045
• Languages: English
• ISSNs: 0141-0296

Abstract

Highlights: Multi-lane traffic micro-simulation is used to find the total load on two long-span bridges. Different types of congestion patterns and traffic compositions are considered. Lane change activity and subsequent formation of truck platoons are analysed. In some cases slow-moving traffic may result in greater loading than full-stop conditions. Critical bridge loading events may happen also at low inflows. Abstract: Long-span bridge traffic loading is governed by congestion. Although congestion can take various forms, most previous studies consider only a queue of vehicles. In this paper, traffic micro-simulation is used to generate several congested traffic scenarios on a two-lane same-direction roadway passing over two long-span bridges. To this end, an acknowledged car-following model is coupled with a lane-changing model. Different traffic compositions and several congestion patterns are analysed in relation to their traffic features and influence on bridge loading. It is found that: (a) slow-moving traffic may be as critical as the full-stop condition, depending on the span length; (b) critical long in-lane truck platoons form mainly at moderate inflows, typically occurring outside of rush hours; (c) the truck distribution between lanes has a limited effect on the total loading; (d) the presence of cars has a strong indirect influence on loading through their interaction with trucks. The methodology and the findings have relevance for computing a more accurate traffic loading for long-span bridges.