Abstract
This paper examines the nature of traffic loading in recurrent congested traffic conditions on a long-span suspension bridge. Traffic flow and percentage of trucks are extracted from image data and a cluster analysis performed to classify the data into four clusters. One cluster (MTHF, medium truck percentage and high flow) is identified that incorporates almost 50% of the hours of traffic data scattered throughout the day. Site-specific load assessment confirms that this MTHF cluster is the most critical for the bridge considered, the Forth Road Bridge in Scotland. For non-recurrent congestion, another cluster (HTLF, high percentage of trucks and low flow) is shown to govern but this finding is highly site-specific, depending on the relative frequency of the different types of congestion. A comparison of the maximum hourly/daily MTHF load effect of the cable force for five notional bridges shows that a 100% increase in the bridge span generates an increase of about 65% in the characteristic load effect.
Highlights
Traffic loading represents a key component in the safety assessment of an existing bridge [1,2].For short- and medium-span bridges, free-flowing traffic with an allowance for dynamic interaction, is the critical loading condition
OBrien et al [9] simulate congestion on a single lane long-span bridge using in-house microsimulation software. They conclude that different forms of congestion for traffic with different percentages of trucks can lead to the bridge being critically loaded, but there is no dominant one
Due to the low % trucks, neither the low trucks/medium flowlow (LTMF) nor the low trucks/high flow (LTHF) clusters are critical for bridge traffic loading
Summary
Traffic loading represents a key component in the safety assessment of an existing bridge [1,2]. From a long-span bridge loading perspective, the car/truck mix and inter-vehicle gaps are key properties of congested traffic. Many researchers create congestion by ‘collapsing’ free-flowing traffic, i.e., by reducing the recorded inter-vehicle gaps (axle-to-axle or bumper-to-bumper) to minimum values [5,15,16,17,18,19,20] This is inappropriate for multi-lane traffic as it changes the relative positions of vehicles in adjacent lanes. OBrien et al [9] simulate congestion on a single lane long-span bridge using in-house microsimulation software They conclude that different forms of congestion for traffic with different percentages of trucks can lead to the bridge being critically loaded, but there is no dominant one. The feasibility is established of extracting valuable information from images such as traffic composition, vehicle lengths and bridge load effects
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