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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>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <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>The Node-Place model, accessibility, and station level transit ridership</title>
      <link>https://trid.trb.org/View/2367965</link>
      <description><![CDATA[This paper uses Sydney rail data to examine the relationship between station level ridership and local and regional accessibility. We use net transit accessibility, which is the additional number of opportunities reachable by transit over walking to represent the regional connectivity value provided by transit. We map accessibility at transit stations, and use the number of opportunities within walking distance as an indicator of local access. We find elements of place (or local) access, including access to jobs and to residents within walking distance (local access), and nodal (or regional) access, including transit access to distant jobs and residential locations are both significant indicators of station level ridership. In particular, the number of jobs within walking distance of a transit station is the best single predictor of transit ridership. This paper highlights the importance of high density around station areas for transit ridership.]]></description>
      <pubDate>Mon, 15 Apr 2024 16:44:27 GMT</pubDate>
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    <item>
      <title>Petrol prices in Australia</title>
      <link>https://trid.trb.org/View/2367074</link>
      <description><![CDATA[Australian petrol prices are determined by movements in the world oil price, the Australian exchange rate, and numerous other components of the price chain. This paper models these factors, examines a short-term scenario for the world oil price and shows how it would translate into movements in Australian retail petrol prices. Detailing the chain allows an understanding of what is going on during periods of rapid changes, such as during the COVID pandemic, as well as what is behind the long-term trends and thus what might be expected in the foreseeable future. The transport of goods and people in Australia is affected by many trends. One of the most important of these trends, given the dependence of mobility in Australia on liquid fuels, is that of the price of fuel (petrol, diesel, LPG, aviation turbine fuel and avgas). Using the retail petrol price as an example, the following analysis shows how these trends can be conceptualised and simulated. The conceptual framework developed allows for an understanding of the forces involved in generating trends in Australian petrol prices.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367074</guid>
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      <title>Uncovering the determinants of shippers' willingness to shift from road to rail freight transport</title>
      <link>https://trid.trb.org/View/2367073</link>
      <description><![CDATA[Traditionally, agri-food shippers have preferred road transport to move their commodities from the point of production to the point of consumption. However, road transport's environmental and economic impact have become increasingly apparent, especially following the just-ended COVID pandemic. As such, a growing interest in inducing a modal shift in the freight movement from road to rail freight has increased exponentially. This shift can potentially influence the existing modal split, as rail transport offers lower carbon emissions, reduced road congestion, and lower transportation costs. Various factors influence the mode choice decisions of freight shippers, and modellers consider these factors within the perceived utility these shippers are assumed to maximise. However, this perceived utility varies for different shippers, even for the same commodity type, resulting in shippers choosing different modes for different freight trips. In this study, we look at revealed modal shift choice behaviours by estimating a discrete choice model to understand the key factors that induce modal choice. The estimated mode choice model applies a revealed preference data of import and export movement to and from one of the major Australian ports. The model estimation results show that shipments' weight, distance, rail mode accessibility and monetary value are highly relevant to modal shift choices. Specifically, the higher the monetary value of commodities such as agricultural and livestock products, the less likely shippers will use rail. Moreover, distance, weight, and mode availability play a crucial role in the mode choice behaviour of shippers. For example, longer distance increases the likelihood of using rail compared to road, and heavier commodities such as coal products are more likely to be shipped by rail than by road.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367073</guid>
    </item>
    <item>
      <title>Evaluation of incremental deep learning approach on real-time traffic prediction</title>
      <link>https://trid.trb.org/View/2367072</link>
      <description><![CDATA[Traffic prediction is a crucial element in managing traffic. Its goal is to comprehend traffic patterns over time in order to anticipate future behavior. In recent times, many research papers have contributed to this area, with a focus on developing machine learning algorithms, particularly deep learning algorithms. Despite producing promising outcomes, real-time traffic prediction faces obstacles due to traffic data being a subset of big data streams that are continuously updated. Nonetheless, over the years, incremental learning has evolved to tackle real-time problems. To address this challenge, this paper evaluates an incremental deep learning approach using overlapping rolling window, tap delay line method and LSTM on a real-world traffic flow dataset collected in Melbourne.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367072</guid>
    </item>
    <item>
      <title>Improving crash frequency model estimation through multi-objective extensive hypothesis testing</title>
      <link>https://trid.trb.org/View/2367071</link>
      <description><![CDATA[Poisson regression is commonly used to model crashes as road accidents typically follow a Poisson process in homogeneous conditions. However, this approach becomes complicated when the data contains too many zero values and is not evenly distributed. To handle over-dispersed data, the Negative Binomial (NB) model is a better option. Recent research has extended the traditional NB approach to account for possible unobserved heterogeneity by using random parameters and considering possible heterogeneity in the means and variances of these parameters. One of the main advantages of random parameter models is their ability to provide a more flexible and accurate representation of the data. Several studies have suggested advanced variations of random parameter models, such as the correlated random parameters approach, which is useful for accounting for the correlation between different sources of unobserved heterogeneity. Despite extensive research and development to incorporate all these model variations, the time, knowledge, and complexity required for an analyst to perform these tasks can be limiting. To build precise and efficient crash prediction models without sacrificing interpretability, an optimization-based framework is needed. Veeramisti et al. (2020) proposed a promising approach that uses metaheuristic search to estimate clusterwise safety performance functions, enabling the simultaneous estimation of the optimal number of clusters and associated safety performance functions. However, their framework cannot estimate generalized crash prediction models considering multiple likely contributing factors, non-linearities, or random parameters. Nevertheless, a metaheuristic search-based approach is effective in generating complex heterogeneous models in practical time frames. Therefore, a metaheuristic solution algorithm is proposed to effectively test many hypotheses and capture the strengths of various modelling approaches while minimizing the sensitivity to human, time, bias, and analysis intervention.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367071</guid>
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    <item>
      <title>A meta-regression of autonomous vehicle value of time estimates</title>
      <link>https://trid.trb.org/View/2367070</link>
      <description><![CDATA[Value of Time (VOT) is a key factor in understanding transport benefits for new investment plans and policies. Several studies have estimated the VOT of Autonomous Vehicles (AVs) travel but no consensus has been reached and the heterogeneity of the variables is yet to be explored. Through a systematic review of the literature, this research paper presents a metaregression analysis of AV VOT estimates from 24 published studies (154 data points). Private AVs have significantly lower VOT than shared or pooled AVs. Travellers perceive more benefits of AV travel in commute trips. However, any secondary impacts on traffic congestion are not included in VOT estimates. AV VOT estimates are significantly lower in rural areas compared to cities. Higher-income riders exhibit higher VOT for AV travel. Methods of estimating AV VOT have a significant influence on the estimated VOT values. Mixed logit models predict VOT estimates a little lower than hybrid choice models. Methods of demonstrating AVs to survey respondents are significant; lower estimates were found for studies adopting animation videos in contrast to written explanations to demonstrate the possible benefits of AV travel. Respondents having a current driving license have lower estimates of AV VOT. Several other variables were tested but found to either have no effect or only a few examples in the published literature making inference of estimates in the analysis weak. Implications of the results for research and practice are discussed.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367070</guid>
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    <item>
      <title>Train horns use at level crossings: a driving simulation study to examine their effectiveness in alerting motorist drivers</title>
      <link>https://trid.trb.org/View/2367069</link>
      <description><![CDATA[Train horns are primarily used as a critical warning tool to encourage safety-compliant behaviours from road users. Comparable to United Kingdom regulations in Australia, train horns should not be blasted without a valid reason and are required when a dangerous situation is anticipated. However, focus groups with Australian train drivers revealed that train drivers viewed the train horn as an essential communication mechanism to interact with other road users. The principal objective of this research is to understand how train horns are perceived by motorist drivers and how they affect the driver’s behaviour around crossings in terms of safety by considering a range of relevant factors including level crossing type, train horn loudness, environmental noise and lighting condition (day/night).]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367069</guid>
    </item>
    <item>
      <title>Transport Cost Benefit Analysis: are the criticisms valid in practice?</title>
      <link>https://trid.trb.org/View/2367068</link>
      <description><![CDATA[The wide-spread use of Cost Benefit Analysis (CBA) to appraise transport investments is accompanied by a growing level of criticism of the methodology. This is difficult to reconcile with the fact that CBA has been used in Australia since the early 1970s and that, since then, there have been significant developments in its application. This paper investigates whether some of the common criticisms of CBA are valid in practice. Firstly, it identifies and explains the main criticisms. The validity of these criticisms is then assessed by observing whether they are due to shortcomings in the CBA methodology or stem from poor practice. Finally, the paper draws some conclusions.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367068</guid>
    </item>
    <item>
      <title>A comparative international review of suburban ring/loop metros to inform the Melbourne suburban rail loop project</title>
      <link>https://trid.trb.org/View/2367067</link>
      <description><![CDATA[This paper explores the case for the Melbourne Suburban Rail Loop (SRL), Australia’s largest urban transport project. It reviews available research literature and compares the performance of the SRL against similar ring or loop Metro systems internationally. The research literature is quite limited in this field largely because ring transit systems of this scale are not very common. Nevertheless, there appear to be merits in terms of network structure for ring/loop metro systems though these would very much depend on the scale of cross corridor trips that are better served by them. Ring/loop metro systems also appear to have merit in enhancing non-CBD development which is a major rationale for SRL though none of the previous research presents conclusive evidence this will actually happen. Evidence on the travel time competitiveness of the SRL is outstanding compared to orbital SmartBus routes and in particular the private car. The ring/loop metro comparative performance analysis looks at 8 existing systems and reports on the findings.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367067</guid>
    </item>
    <item>
      <title>Trajectory-user linking with a deep neural network</title>
      <link>https://trid.trb.org/View/2367066</link>
      <description><![CDATA[In recent years, the proliferation of GPS-enabled devices has led to an explosion of data, including vast amounts of trajectory data capturing user mobility and travel behavior. One important area of research in this field is trajectory user linking, which involves analyzing patterns of behavior to identify anonymous trajectories with the users who generated them. Trajectory user linking has a wide range of applications. For instance, by linking check-in trajectories on points of interest (POI) to specific users, advertisers can better understand users' preferences and interests and deliver more targeted and personalized recommendations. Trajectory user linking can also be used to identify and detect criminal/terrorist behavior or track the transmission of pandemics by mapping suspicious trajectories to potential suspects in the database system. Furthermore, trajectory user linking can also help improve transportation planning and traffic management by providing insights of the user's mobility patterns, including their commuting routes, their favorite leisure spots, and their travel habits. Generally, the performance of trajectory-user linking depends on several factors, such as the type of trajectory data, the length of the trajectories, and the sampling rate. To address these challenges, our work proposes a deep learning model that combines the power of GNN and Recurrent Neural Network (RNN) to capture the spatiotemporal information of different types of trajectories.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367066</guid>
    </item>
    <item>
      <title>Air travel and tourism in Malta: impacts of low-cost airline introduction</title>
      <link>https://trid.trb.org/View/2367065</link>
      <description><![CDATA[The introduction of low-cost carriers (LCCs) is strongly related to air traffic movements and the tourism sector. This is especially so for island destinations where the role of tourism is critical to maintain economic growth. This paper analyses the impacts of low-cost airline introduction in the islands of Malta. The impacts of low-cost aviation have been widely studied, with similar results of increased traffic and tourism at destinations. However, when the destination is an island state, and a member of the European Union with limited land and space resources, the impacts of increased LCCs and tourism activity can have significant impacts. This study investigates these impacts by looking at air travel and the contribution of LCCs. The study hopes to encourage other studies in small independent island states, in order to support sustainable travel and tourism]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367065</guid>
    </item>
    <item>
      <title>Understanding travelers’ satisfaction in ferry services: evidence from Brisbane, Australia</title>
      <link>https://trid.trb.org/View/2367064</link>
      <description><![CDATA[There has been little direct research on passenger satisfaction with ferry services, in part because these services are relatively uncommon. To help fill this gap, this paper investigates the effect of the built environment, weather, safety, security, operation, users’ sociodemographic characteristics, and their use of public transport to help explain their satisfaction with ferry services. This study focuses on the ferry services in Brisbane using the Translink customer experience survey from July to September 2019. Common statistical methods were used to examine the passengers’ reported satisfaction and the relative importance of different factors in their level of satisfaction. The results highlight the passengers’ satisfaction with the service overall; satisfaction with their last trip; satisfaction with the perceived safety when waiting at ferry terminals. We found that punctuality has the largest contribution to satisfaction with the last trip, followed by the total journey time, the level of safety on-board, and accessibility on board. The service aspects with the relatively highest importance for improving ferry service satisfaction are punctuality, journey time, fares, and the design of off-board facilities. The findings can provide insight to improve passenger satisfaction with, and perhaps attract more passengers to, the ferry services in Brisbane.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367064</guid>
    </item>
    <item>
      <title>Lightweight traffic anomaly detection: a case study with SCATS volume data of Melbourne</title>
      <link>https://trid.trb.org/View/2367063</link>
      <description><![CDATA[In this paper, we evaluate performance of an anomaly detection framework with real traffic count data collected by SCATS (Sydney Coordinated Adaptive Traffic System) loop detectors in Melbourne. The goal is to detect anomalous daily volume profiles within temporally large historical traffic data utilizing a lightweight and parameter-free approach and use it for live applications. To achieve this, daily volume profiles are first compressed into two dimensions benefiting from the Principal Component analysis (PCA). Then, a parameter-free version of DBSCAN is applied to the data with unique days of the week. Results from more than 20 different locations in Melbourne are fully visualized and the advantages and disadvantages of the method are discussed. We found that, with this approach, anomalous volume profiles can be accurately detected in a wide range of spatiotemporal data without any pre-training, parameter setting, or using complex learning methods.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367063</guid>
    </item>
    <item>
      <title>Simulations guiding on-demand services: the use of digital twins to shape service optimisation</title>
      <link>https://trid.trb.org/View/2367062</link>
      <description><![CDATA[The use of simulations and digital twins is contributing to the ability to understand how ondemand transit system performance can be optimized using service parameter adjustments. This paper demonstrates the use of a digital twin to replicate an active on-demand transit service in Auckland, New Zealand. It then shows the use of simulation  to explore opportunities to adjust service parameters to improve service outcomes. It then demonstrates the impact of service adjustment on service delivery, showing increases in ridership. Finally, it outlines potential use cases for simulations and digital twins to explore on-demand transit systems.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367062</guid>
    </item>
    <item>
      <title>Exploring the spatial-temporal influence of the COVID-19 pandemic on road crashes in Greater Perth</title>
      <link>https://trid.trb.org/View/2367061</link>
      <description><![CDATA[The COVID-19 lockdowns and restrictions in Greater Perth significantly affected the road network and safety outcomes. This paper uses a spatial-temporal approach to examine their impact on road safety and trends that emerged. The analysis revealed a 35% reduction in crashes during the early 2020 outbreak compared to the same period in 2019, before gradually increasing to pre-pandemic levels by 2021 as the network returned to ‘normal’. The temporary reduction in crashes was not uniform, with fatal and severe collisions showing a smaller decrease than other lower severity crashes while active transport users were overrepresented in the statistics during the lockdowns and restrictions. Demographic characteristics including occupation (‘white’ and ‘blue’ collar), distance from the Perth Central Business District (CBD) and vehicles per household also influenced the demand for the road network and crash trends. Interestingly, there was a significant reduction in crashes around strategic employment centres while there was a smaller decrease around neighbourhood centres as people still travelled for essential goods. Implications for policymakers include the continued need for targeted road safety campaigns and education to improve road safety to a level seen during the pandemic. Further, investment in active transport infrastructure and the application of frameworks such as Movement and Place may enhance safety by reducing conflicts between private vehicles and active transport users.]]></description>
      <pubDate>Mon, 15 Apr 2024 14:21:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367061</guid>
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