Now showing 1 - 10 of 24
  • Publication
    Micro-simulation modelling of congestion due to lane closures
    (Irish Transport Research Network, 2012-08-30) ; ;
    Incident clearance and road work often require the closure of one or more of the available lanes on a highway. A lane-closure causes a significant capacity reduction, which often leads to heavy congestion. Simulation of congestion events due to lane - closures is relevant both for traffic and infrastructure management. This is especially valid when trucks are involved and they concentrate on bridges or in tunnels, thus generating critical situation s for loading and safety. A better understanding of the effects of lane closures requires a realistic simulation of the merging manoeuvre of vehicles occurring in the proximity of the lane closure. Micro-simulation allows for the motion of individual vehic les and it is therefore a suitable tool for studying traffic merging. In this paper, a micro-simulation tool made up of a car-following model and a lane-changing model is used for simulating a lane closure on a two-lane one direction stretch of road. The effects on traffic are studied, in terms of average speed, lane change rates, and truck distribution. It is found that the lane-changing model requires an appropriate parameter calibration when applied to lane-closures. These parameters are quite different from the ones reported in literature. An alternative means of causing congestion is also tested and it is found that it can replicate the overall congestion features upstream the closure. However, there are some differences about details of the traffic features
  • Publication
    Recent Advances in the Governing Form of Traffic for Bridge Loading
    The assessment of site-specific bridge traffic loading using WIM data is a critical feature of minimizing the cost of rehabilitation and replacement for bridge stock. For short- to medium-span bridges, it is often assumed that free-flowing traffic, including the dynamic interaction between the vehicles and bridge, governs the extreme load effect. In this paper, some recent advances in statistical techniques applied to bridge load effect extrapolation are presented. A critical review of these new approaches is made and it is shown that extrapolation results are now considerably more reliable and repeatable. It is also shown that there is doubt over the governing form of traffic. Therefore, the authors present some initial results of congested-traffic models in comparison to a free-flowing model. For a range of bridge lengths and load effects, the authors determine the dynamic ratio that would be required for free-flowing traffic to govern. The implications of these recent advances and various findings are discussed with reference to the future direction of research into bridge traffic loading
  • Publication
    Headway modelling for traffic load assessment of short to medium span bridges
    (Institution of Structural Engineers, 2005-08-16) ;
    Site-specific assessment of the loading to which existing bridges are subject has considerable potential for saving on rehabilitation and replacement costs of the bridge stock. Monte Carlo simulations, with traffic measurements from site, are used to estimate the characteristic values for load effects. In this paper, it is shown that the critical loading events from which the characteristic effects are derived, are strongly dependent on the assumptions used for the headways of successive trucks. A new approach which uses measured headway statistical distributions is developed and is shown to be a reasonable balance between conservative assumptions and less realistic scenarios. The sensitivity of characteristic load effects to conventional headway assumptions is shown to be significant.
  • Publication
    The effect of controlling heavy vehicle gaps on long-span bridge loading
    (Transportation Research Board, 2013-01) ; ;
    Long-span road bridges are governed by congested traffic rather than free-flowing conditions. During congestions, heavy vehicles can get quite close to each other, thus giving potential critical loading events for the bridge. In this paper, the effects of a system capable of warning truck drivers when the gap falls below a certain threshold are investigated. The effects are studied both in terms of increase in traffic disruption and reduction in loading. The minimum distance between trucks should be ideally adjusted in relation to the site-specific traffic features and to the load the bridge is able to carry in safety. Doing so, it is possible to allow for future increase in truck weight regulations and/or heavy traffic volumes, by adjusting the control gap value. Importantly, the system does not presume any restriction to the truck weight. By contrast, the system is meant to be an alternative way of limiting the load on long-span bridges by keeping the trucks apart, rather than by limiting the truck weight. The introduction of such a gap control system is studied by means of micro-simulation. The car-following model used here has been shown able to replicate many observed congestion patterns. Results show that the introduction of the gap control system does not significantly disrupt the traffic further. On the other hand, having only 10% of equipped trucks beneficially reduces the total traffic loading by about 10%. When most trucks are equipped, nearly 50% reduction in the total load can be attained.
  • Publication
    Probabilistic study of lifetime load effect distribution of bridges
    Assessment of highway bridge safety requires a prediction of the probability of occurrence of extreme load effects during the remaining life of the structure. While the assessment of the strength of an existing bridge is relatively well understood, the traffic loading it is subject to, has received less attention in the literature. The recorded traffic data are often limited to a number of days or weeks due to the cost of data collection. Studies in the literature have used many different methods to predict the lifetime maximum bridge load effect using a small amount of data, including fitting block maximum results to a Weibull distribution and raising maximum daily or maximum weekly distributions to an appropriate power. Two examples are used in this study to show the importance of the quantity of data in predicting the lifetime maximum distribution. In the first, a simple example is used for which the exact theoretical probabilities are available. Hence, the errors in estimations can be assessed directly. In the second, ‘long-run’ simulations are used to generate a very large database of load effects from which very accurate estimates can be deduced of lifetime maximum effects. Results are presented for bidirectional traffic, with one lane in each direction, based on Weigh-in-Motion data from the Netherlands.
  • Publication
    The Effect of Lane Changing on Long-Span Highway Bridge Traffic Loading
    Maximum loading on long-span bridges typically occurs in congested traffic conditions. As traffic becomes congested car drivers may change lane, increasing the tendency for trucks to travel in platoons. For long-span bridges this phenomenon may increase the regularity and severity of bridge repair programs, with potential significant associated costs. This research investigates the effect of lane changing by car drivers on bridge loading. A Monte Carlo simulation model in which individual car drivers probabilistically decide, based on a lane-changing bias probability, whether or not to change lane has been developed. The sensitivity of bridge loading to this factor is investigated for different bridge lengths and traffic compositions. This research concludes that the lane-changing behavior of car drivers has an effect on bridge loading for long-span bridges, and the magnitude of this effect is quite sensitive to the percentage of trucks in the traffic.
  • Publication
    Finding the Distribution of Bridge Lifetime Load Effect by Predictive Likelihood
    (ASRANet Ltd, 2006-07) ;
    To assess the safety of an existing bridge, the loads to which it may be subject in its lifetime are required. Statistical analysis is used to extrapolate a sample of load effect values from the simulation period to the required design period. Complex statistical methods are often used and the end result is usually a single value of characteristic load effect. Such a deterministic result is at odds with the underlying stochastic nature of the problem. In this paper, predictive likelihood is shown to be a method by which the distribution of the lifetime extreme load effect may be determined. A basic application to the prediction of lifetime Gross vehicle Weight (GVW) is given. Results are also presented for some cases of bridge loading, compared to a return period approach and important differences are identified. The implications for the assessment of existing bridges are discussed.
  • Publication
    The structural reliability of bridges subject to time-dependent deterioration
    The reliability of the structural performance of any given structure is affected by both in-service loading and material deterioration due to environmental attack. They must be evaluated at any given time in order to compute lifetime probability of failure. This paper presents an innovative methodology to derive the structure lifetime load effect due to existing traffic using a statistical tool known as Predictive Likelihood. Loss of resistance due to corrosion originated by chloride ingression is also taken into account. Finally the lifetime probability of failure is evaluated via the application of a time-discretization strategy
  • Publication
    Load effect of multi-lane traffic simulations on long-span bridges
    The traffic loading of long-span bridges is governed by congestion. Real-world observations show that congestion can take up different forms. Nevertheless, most previous studies on bridge traffic loading considered only a queue of standstill vehicles. In this paper, a micro-simulation tool is used for generating congested traffic on a two-lane same-way roadway. The total load is computed for a sample long-span bridge. Different congestion patterns are found and they are studied in relation to their effect on loading. It is found that very slow-moving traffic returns the highest loading events, rather than full stop conditions. The topic is especially relevant to existing bridges, where small differences in the loading may play an important role in the safety assessment and subsequent maintenance plans.
  • Publication
    Modelling of Highway Bridge Traffic Loading: Some Recent Advances
    The accurate estimation of site-specific lifetime extreme traffic load effects is an important element in the cost-effective assessment of bridges. In recent years, the improved quality and increasing use of weigh-in-motion technology has resulted in better quality and larger databases of vehicle weights. This has enabled measurements of the regular occurrence of extremely heavy vehicles, with weights in excess of 100 t. The collected measurements have been used as the basis for building and calibrating a Monte Carlo simulation model for bridge loading. The computer programs written to implement this model generate simulated traffic in two lanes – for both the same direction and the bidirectional cases – and calculate load effects for bridges of various spans. The research focuses on free-flowing traffic on short to medium-span bridges. This paper summarizes recent advances and their contribution to the highway bridge traffic loading problem.