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Micro-simulation modelling of traffic loading on long-span bridges
Author(s)
Date Issued
2013
Date Available
2018-08-17T08:43:03Z
Abstract
Traffic loading on long-span bridges is governed by congestion. An accurate modelling of the traffic loading to which a bridge is actually exposed allows to plan maintenance operations more effectively. However, most previous research uses simplified traffic models, typically consisting of a queue of vehicles at minimum bumper-to-bumper distances, in fact neglecting lighter and more frequently observed forms of congestion. Moreover, the available load models assume conservative frequencies of occurrence of congestion. In this research, micro-simulation is used to reproduce several observed congestion patterns. Different combinations of traffic streams and congestion strengths are simulated, thus allowing the analysis of several traffic features and their effects on long-span bridge loading. It is found that the queue of vehicles at a standstill, widely used in previous research, is not always the most critical congested state for long-span bridge loading. In fact, also slow-moving traffic can be critical. It is also found that the load does not significantly depend on the inflow, as long as congestion is triggered, implying that critical loading events may also happen out of rush hours. A new methodology is proposed to compute the characteristic load based on site-specific traffic data, such as incident patterns and hourly flow distributions. This methodology is applied to traffic data available from the literature. It is found that flows with high truck percentage, typically occurring at night-time in combination with low traffic volumes, largely contribute to the characteristic load, even though congestion in such conditions is quite rare. Finally, some issues related to traffic data collection for bridge loading are dealt with and a promising application for bridge loading control is proposed.
Type of Material
Doctoral Thesis
Qualification Name
Ph.D.
Copyright (Published Version)
2013 the Author
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
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