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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <title>A new flood estimation paradigm for the design of civil infrastructure systems</title>
      <link>https://trid.trb.org/View/1655050</link>
      <description><![CDATA[Methods for quantifying flood risk of civil infrastructure systems such as road and rail networks require considerably more information compared to traditional methods that focus on flood risk at a point. These systems are characterised by multiple interconnected components, whereby a ‘failure’ of the overall system can arise because of complex combinations of failures in system subcomponents. Whereas traditional flood estimation approaches focus on estimating flood risk at a single location, this thesis proposes a new estimation paradigm that focuses on estimating system-wide risk. The approach builds on the traditional intensity-duration-frequency (IDF) methods that are commonly used in engineering practice in Australia and internationally; however, this is implemented in such a way at to provide information on the spatial dependence of design storms. A particular innovation in this thesis is to estimate spatial rainfall dependence across multiple storm durations, allowing it to be used to estimate flood risk across multiple catchments with differing times of concentration. Finally, whereas traditional IDF approaches consider conversion from point rainfall to spatial rainfall via areal reduction factors as a post-processing step, the approach proposed herein enables this conversion implicitly as part of the method. The case study examines a highway upgrade project on the east coast of Australia, containing five bridge crossings with differing contributing catchment areas, and thus differing times of concentration. The results are used to show the differences between conditional-flood and conventional-flood estimates at each bridge, and the relationship between the overall failure of a system and the failure probability of an individual bridge. This research therefore is shown to enable a different paradigm for design flood risk estimation, which focuses attention on the risk of the entire system rather than considering individual system elements in isolation.]]></description>
      <pubDate>Thu, 26 Sep 2019 12:21:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/1655050</guid>
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      <title>The crash performance of seagull intersections and intersections with left turn slip lanes</title>
      <link>https://trid.trb.org/View/1655043</link>
      <description><![CDATA[Alternative intersection layouts may reduce traffic delays and/or improve road safety. Two alternatives are reviewed in this research: ‘priority-controlled Seagull intersections’ and ‘priority-controlled intersections with a Left Turn Slip Lane’. Seagull intersections are used to reduce traffic delays. Some do experience high crash rates, however. Left Turn Slip Lanes allow turning traffic to move clear of the through traffic before decelerating, thereby reducing the risk of rear-end crashes. Although there is debate about the safety problems that occur at Seagull intersections and Left Turn Slip Lanes there has been very little research to quantify the safety impact of different layouts. In this study, crash prediction models have been developed to quantify the effect of various Seagull intersection and Left Turn Slip Lane designs on the key crash types that occur at priority intersections. The analysis showed that seagulls are not safe on 4-lane roads, that roadway features like kerb-side parking and nearby intersections can increase crash rates and that left turners in LTSLs can restrict visibility and create safety problems.]]></description>
      <pubDate>Thu, 26 Sep 2019 12:20:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/1655043</guid>
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      <title>Safety solutions on mixed use urban arterial roads</title>
      <link>https://trid.trb.org/View/1655040</link>
      <description><![CDATA[Urban arterials and intersections account for a large proportion of high severity crashes in Australia and New Zealand, particularly involving vulnerable road users. Safety gains appear to be slower in these ‘mixed use’ environments than in other areas. Austroads commissioned research to help identify solutions that might be applied on mixed use arterial roads to improve safety through the provision of Safe System infrastructure. The project involved assessment of six case studies around Australia and New Zealand. Concept designs were developed for each of the routes based on analysis of safety issues and the likely safety benefits were assessed. This paper presents information on the safety solutions identified, as well as the broader issues that need to be considered when addressing safety on mixed use urban arterial roads.]]></description>
      <pubDate>Thu, 26 Sep 2019 12:20:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/1655040</guid>
    </item>
    <item>
      <title>Exploring local government challenges in effective road safety delivery</title>
      <link>https://trid.trb.org/View/1632649</link>
      <description><![CDATA[]]></description>
      <pubDate>Tue, 25 Jun 2019 09:37:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/1632649</guid>
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    <item>
      <title>Guide to road design part 2: design considerations</title>
      <link>https://trid.trb.org/View/1607144</link>
      <description><![CDATA[Guide to Road Design Part 2 provides a detailed description of the three critical aspects of road design: the design objectives that apply to a road design project; context-sensitive design; and the factors that influence the road design, including road design in the context of the Safe System philosophy. Guidance is provided to practitioners on the range of influences, information, data, criteria and other considerations that may have to be assessed in developing a road project. The guide also describes the basis of the guidelines and the context in which they should be applied. It also provides links to other Austroads Guides and the resources that give further guidance on design inputs.]]></description>
      <pubDate>Mon, 20 May 2019 10:43:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/1607144</guid>
    </item>
    <item>
      <title>Modelling the impact of lifeline infrastructure failure during natural hazard events</title>
      <link>https://trid.trb.org/View/1607092</link>
      <description><![CDATA[This thesis utilises mathematical graph theory tools alongside natural hazard modelling to analyse and quantify the extent of lifeline disruption during natural hazard events and the flow on effects of service failure. A future eruption of Mount Fuji in Japan is used as the major case study scenario to assess the usefulness of graph theory techniques in aiding disaster mitigation, emergency response and community recovery. This scenario provided the opportunity to test graph theory techniques in natural hazard risk assessment and to demonstrate how graph theory can assist post event recovery in a real world context. Methods developed in this study can be used to further explore impacts of ash fall, or other volcanic phenomena, in other prefectures around Mount Fuji or other volcanoes throughout Japan. Moreover, these methods can be used to address the exposure and risk to lifelines from other natural hazard events or even to compare between them. The results of this thesis show that graph theory techniques, alongside Geographic Information Systems tools and hazard modelling, with an understanding of the use and vulnerability of particular lifelines, can help to envisage potential problems that could result from lifeline failure and aid in the process of recovery. Not only is it important to make lifeline infrastructure more resilient to disruption from future natural hazard shocks, there is also a need to increase resilience by preparing communities to cope with service outages. For true shared responsibility to occur, local governments and communities need to be better informed and prepared so they can cope with the absence of lifelines during a disaster. Collaboration between all stakeholders is required to bridge information gaps and to create holistic disaster scenarios in order to provide more realistic and accurate assessments of future natural hazard impacts.]]></description>
      <pubDate>Mon, 20 May 2019 10:18:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/1607092</guid>
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      <title>Fusion of heterogeneous data in non-destructive testing and structural health monitoring using Echo State Networks</title>
      <link>https://trid.trb.org/View/1602617</link>
      <description><![CDATA[Failure to monitor the condition of key infrastructure such as roads and bridges can result in costly closures, but the economic impact could be lessened by early intervention. Non-destructive testing (NDT) examines structures without causing damage, while structural health monitoring (SHM) monitors a structure throughout its life. This thesis presents a machine learning approach to fusing heterogeneous sensor modalities that can be systematically applied to improve sensor interpretation and reduce reliance on expertise. For the first time, echo state networks (ESNs) were used in two separate NDT and SHM data fusion case studies. The NDT-based study looked at detecting defects in steel reinforcement, teaching ESNs to combine magnetic flux leakage (MFL) and cover depth data in order to compensate for variation in MFL amplitude with increasing cover depth. Using seven different cover depths between 42.5 mm and 289 mm, the fusion approach offered improved performance for 42.5mm < depth < 205mm and the most consistent calculated optimal output threshold, demonstrating the ease of systematic application. In the SHM-based study, data from the National Physical Laboratory (NPL) footbridge monitoring project was processed by a suite of ESNs to detect, localise, classify and assess damage caused by deliberate interventions. A novel approach of combining physical and environmental sensors in order to model a different modality of physical sensor made it possible to use the residual to observe damage trends and locations, which also led to the isolation of a faulty strain gauge. There was additional success in distinguishing between different intervention types and producing a metric to express the damage level. Across both studies, the ESN approach to heterogeneous data fusion improved upon non-fusion-based alternatives. This suggests that future work should consider structures that are in regular use, combining further sensor modalities and the development of bespoke data fusion software.]]></description>
      <pubDate>Tue, 30 Apr 2019 09:29:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/1602617</guid>
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    <item>
      <title>Fundamental characterisation of thermal influence in hot mix asphalt repair</title>
      <link>https://trid.trb.org/View/1602614</link>
      <description><![CDATA[The study focuses on the issue of hot mix asphalt pothole repairs, the performance of which is greatly reduced by repair edge disintegration. This is caused by low interface temperatures which result in low density interfaces and poor repair bonding. The study examined heat flow in shallow and deep pothole excavations under controlled pre-heating done in heating-cooling cycles, referred as “dynamic heating”, and the effect of asphalt thermal properties on this. The study also examined heat flow in traditional non-heated shallow repairs, referred as “static repairs”, and dynamic shallow repairs and the effect of pothole pre-heating in repair adhesion. Finite Element modelling was also used to enhance understanding of heat flow in the executed repairs. Then, the bonding properties and rutting resistance of the repairs were assessed using shear bond tests (SBT’s) and wheel track tests (WTT’s) respectively. The results showed that irrespective of excavation depth, heating power and heater offset, temperature distribution in the pothole excavation and inside the slabs under dynamic heat was non-uniform. Dynamically heating pothole excavations for approximately 10 minutes yields better heat distribution than 20 minutes heating time while minimising the possibility of asphalt overheating. The temperature profile at the interface of the dynamically heated repair is improved when compared to static repair suggesting better interface adhesion. It was concluded that dynamically heating a pothole excavation increases repair interface adhesion and repair durability.]]></description>
      <pubDate>Tue, 30 Apr 2019 09:29:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/1602614</guid>
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    <item>
      <title>Re-suspension of road dust: contribution, assessment and control through dust suppressants: a review</title>
      <link>https://trid.trb.org/View/1602595</link>
      <description><![CDATA[]]></description>
      <pubDate>Tue, 30 Apr 2019 09:28:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/1602595</guid>
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    <item>
      <title>Flood immunity for a road or bridge: what benefits it can bring to road users, road authority and broad community?</title>
      <link>https://trid.trb.org/View/1589107</link>
      <description><![CDATA[Many road sections and bridges in Australia are subject to flooding. The road has to be closed in the event of flooding causing significant delays, disruptions and negative impacts to local economy and community. Typical flood immunity design is to raise a road section or a bridge to a certain height that is immune to a flood in 1 in 10, 20, 50 or 100 year flood intensity. Raising a road section in a floodplain or a bridge over a river is costly as volume of earthwork for embankment may increase exponentially and a higher bridge usually requires larger piers and stronger structure. While cost is high, the benefit is not well understood. There are a number of drawbacks in practical economic evaluations of flood immunity projects. A review of existing evaluations indicates that some evaluations had relied on over-simplified assumptions (e.g. all vehicles were delayed for 2 hours in the event of flooding). In other evaluations, driver behavioural response to a road closure (diversion, waiting or not-travelling) was not analysed. Some evaluations only included diversion costs but omitted the costs incurred by voluntarily and involuntarily trip cancellations. Furthermore, diversion routes for light and heavy vehicles were not appropriately identified for many project evaluations. The key objective of this paper is to provide a practical economic evaluation framework of flood immunity projects that fully accounts for road user costs, road agency costs and local economic impacts. A worked example is provided to demonstrate how the proposed methodology can be used in the economic evaluation of flood immunity options.]]></description>
      <pubDate>Tue, 26 Feb 2019 14:42:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/1589107</guid>
    </item>
    <item>
      <title>Development of random forests regression model to predict track degradation index: Melbourne case study</title>
      <link>https://trid.trb.org/View/1589084</link>
      <description><![CDATA[In rail infrastructure maintenance management systems, Track Degradation Index (TDI) is considered as a representative of quality of rail tracks. This index is usually developed based on the deviation rate or standard deviation of track geometry parameters. In this regard, prediction of future TDI is an important task as it can be employed to determine when and where maintenance and renewal activities must be deployed. In this study, a track geometry data set from Melbourne tram network has been used as the case study and gauge deviation parameter is selected as the main parameter to develop TDI. For prediction of the future TDI, Random Forests (RF) model as a Machine Learning (ML) model is used to predict the future TDI of the data set. Since TDI is a continuous variable, Random Forests Regression (RFR) model is applied. In this study, RF model has added two algorithms to the basic Decision Trees (DT) model including bagging and random subspace method. These algorithms can reduce the overfitting problem and over-focus on special features. Based on the results of this study, adjusted R2 value of the proposed prediction model is 0.93, which demonstrates that the model has the satisfying performance in predicting the TDI.]]></description>
      <pubDate>Tue, 26 Feb 2019 14:40:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/1589084</guid>
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    <item>
      <title>Data standard for road management and investment in Australia and New Zealand</title>
      <link>https://trid.trb.org/View/1589052</link>
      <description><![CDATA[The Data Standard for Road Management and Investment provides road agencies and their suppliers, in Australia and New Zealand, with a specification for the data that supports common operational activities. The Data Standard also provides road network funding agencies with a specification to inform structure of reports and submissions requested from road agencies, to enable more equitable evidence-based investment decision making. Specifically, the Standard establishes a common understanding of the meaning or semantics of the data, to ensure appropriate use and interpretation of the data by its stakeholders. The Standard also recognises various levels of sophistication in inventory and asset planning practice and provides relevant data item details in this regard. Accordingly, the Standard will benefit any road industry stakeholder who utilises data for road research, policy development, expenditure comparisons, funding approvals, supporting national reforms, national reporting, innovation, shared services, and inter-organisation communications.]]></description>
      <pubDate>Tue, 26 Feb 2019 14:34:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/1589052</guid>
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    <item>
      <title>Revised Priority Harmonisation Subsets (PHS) and metrics for data standard for road maintenance and investment</title>
      <link>https://trid.trb.org/View/1589047</link>
      <description><![CDATA[The Priority Harmonisation Subset (PHS) of the Data Standard was developed to promote the realisation of benefits from comparative road network performance reporting and data items considered to be a priority for effective asset and maintenance management. A range of stakeholders were engaged to review a draft version of the PHS, which was confined to roads (pavement and surfacing), structures (bridges and major culverts), and tunnels as these asset classes combined represent a significant share of the whole road network portfolio. As a result of the review, additional data items were sourced from the Data Standard for inclusion in the revised PHS as well as the identification of many new data items for inclusion in both the PHS and Data Standard. The revised PHS also includes a set of metrics for each of the PHS data items and identification of specific data items of use to stakeholders external to the road agencies.]]></description>
      <pubDate>Tue, 26 Feb 2019 14:34:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/1589047</guid>
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    <item>
      <title>Policies to extend the life of road assets</title>
      <link>https://trid.trb.org/View/1589034</link>
      <description><![CDATA[This report presents policy options for extending the life of road assets by mitigating deterioration caused by trucks. Beyond traditional engineering responses, it considers the role of trucks in road asset deterioration from a broader, demand-oriented perspective.]]></description>
      <pubDate>Tue, 26 Feb 2019 14:25:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/1589034</guid>
    </item>
    <item>
      <title>Development of steel angles as energy dissipation devices for rocking connections</title>
      <link>https://trid.trb.org/View/1589019</link>
      <description><![CDATA[]]></description>
      <pubDate>Tue, 26 Feb 2019 14:25:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/1589019</guid>
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