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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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      <link>https://trid.trb.org/</link>
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      <title>One Light, Two Light, Red Light, Green Light: An Analysis of Signal Priority on the Metro G Line</title>
      <link>https://trid.trb.org/View/2610610</link>
      <description><![CDATA[Los Angeles County Metropolitan Transportation Authority (LA Metro) planning staff, working alongside engineers from the Los Angeles Department of Transportation (LADOT) seek to make improvements to the Metro G Line (Orange) busway to address a number of operational problems with the popular line. The Metro G Line is the backbone of transit in the San Fernando Valley, serving more than 22,000 pre-COVID-19 pandemic weekday boardings. Part of the problem for public transit in a chronically traffic congested place like Los Angeles is that buses typically have to compete for road space with private automobiles. As a result, buses get stuck in traffic. Light rail vehicles, when travelling on surface streets with cars, get stuck in traffic as well. The G line busway thus has a significant advantage, as it runs on its own dedicated route. Efforts to further separate the G line from nearby traffic, such as grade separated over- and under-passes or railroad-style gate arms at street crossings, will require complex planning and take considerable time and resources to implement. However, speeding up the G line with current infrastructure is possible by improving transit signal priority (TSP). TSP prioritizes a direction along a roadway by extending green time at signals so priority vehicles (in this case buses) can pass through an intersection without stopping. This report explores the current signal regime along the G line alignment, some of the history of the TSP system, and draws on case studies to develop applicable lessons to the Metro G line.]]></description>
      <pubDate>Fri, 14 Nov 2025 08:43:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2610610</guid>
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    <item>
      <title>An implemented Operative-TCO analysis to assess the company cost of hydrogen compared to diesel and CNG-fueled buses</title>
      <link>https://trid.trb.org/View/2571378</link>
      <description><![CDATA[In the context of the transport sector’s decarbonization efforts, targeting zero direct emissions in urban areas by 2040, Local Public Transport (LPT) companies within the European Union (EU) are mandated with the task of fleet renewal, gradually replacing internal combustion engine (ICE) vehicles with electric vehicles, including those powered by hydrogen fuel cells electric (HFCE).Integrating novel vehicle technologies associated with the utilization of green energy carriers poses an additional challenge for LPT companies concerning the management of service production costs.For economic evaluation purposes, an effective method relies on Total Cost of Ownership (TCO) analysis, which encompasses both fixed and variable costs associated with vehicles and their corresponding functional systems over their operational lifespan. However, TCO analysis fails to encompass a segment of company costs attributable to operational vehicle performance aspects.This paper proposes and elucidates an implementation of the Operative-TCO (OTCO) methodology, which additionally incorporates costs stemming from vehicle operational constraints, such as mileage range and energy recharging time, as a function of the service requirements along a designated route.Utilizing data from the monitoring of an Italian LPT corporate fleet as a case study, the TCO and OTCO of green/grey-HFCE vehicles are computed in comparison to diesel and compressed natural gas (CNG) vehicles. The findings are presented and discussed in a comparative framework, inclusive of the assessment of emission-related costs.]]></description>
      <pubDate>Fri, 29 Aug 2025 10:03:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2571378</guid>
    </item>
    <item>
      <title>A hybrid econometric–machine learning framework to support market development in intercity passenger transport: the causal and predictive analytics of economic mobility features</title>
      <link>https://trid.trb.org/View/2548176</link>
      <description><![CDATA[Capturing potential travel demand is crucial for carriers to improve their market performance, especially in developing economies with an emerging middle class and increasing socioeconomic inclusion. However, the impact of upward economic mobility on deregulated transport systems and how carriers can capitalize on this trend to increase revenues remain unclear, as this phenomenon is influenced by several confounding factors. This study aims to estimate and decompose the impact of the inclusiveness boom and bust in Brazil on its domestic intercity travel industry. By utilizing Instrumental Variables Least Absolute Shrinkage and Selection Operator (IV-LASSO) and Quantile Regression, the authors' high-dimension sparse approach intends to estimate the effects of a set of economic mobility features on travel markets. The authors also employ a meta-machine learning approach based on Stacking Regression to assess the contribution of these features to revenue generation. The authors' findings suggest that airlines are more efficient than bus carriers at implementing market development strategies to achieve effective market inclusion. The customer retention rate for bus carriers is 32% lower, indicating the need to enhance demand management. Moreover, Stacking outperforms base machine learners in predicting revenues for both transport modes. Finally, an event study carried out for the economic downturn period shows a persistent adverse effect on demand and prices and identifies the moments when the machine learning models perform most poorly.]]></description>
      <pubDate>Fri, 11 Jul 2025 08:42:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2548176</guid>
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    <item>
      <title>Travel Washington Intercity Bus Program: 2024 Study Update</title>
      <link>https://trid.trb.org/View/2505760</link>
      <description><![CDATA[This study evaluates the existing intercity bus service within Washington and presents the outcomes of a feasibility study to determine where potential service expansions will be most cost-effective, while addressing the program’s goal of linking rural areas and restoring meaningful connections to the existing intercity network. The Washington State Department of Transportation (WSDOT) structured this study around three goals and accompanying objectives, equity, accessibility, and safety and comfort. The report contains the following chapters: Chapter 2: Background on Intercity bus service in Washington State; Chapter 3: Existing intercity bus network; Chapter 4: Existing operator characteristics; Chapter 5: User characteristics and network travel patterns; Chapter 6: Public engagement; Chapter 7: Summary of key gaps and needs; Chapter 8: Potential service expansion scenarios; Chapter 9: Priority expansion scenarios; and Chapter 10: Recommendations.]]></description>
      <pubDate>Tue, 11 Feb 2025 15:52:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2505760</guid>
    </item>
    <item>
      <title>U.S. Department of Transportation, Climate Change Center Climate Strategies That Work: Intercity Bus</title>
      <link>https://trid.trb.org/View/2499187</link>
      <description><![CDATA[Intercity buses bridge critical transportation gaps in rural areas, between urban centers, and during high traffic periods, by offering sustainable, accessible, and convenient travel options. This report looks at intercity bus transportation as a strategy to reduce greenhouse gas (GHG) emissions. On a per-passenger basis, particularly for journeys between 200 and 500 miles, bus travel has much lower greenhouse gas emissions per trip than single-occupancy vehicles and air travel. The report examines: the GHG reduction potential of intercity buses, co-benefits, cost considerations, and funding opportunities. Case studies are also provided.]]></description>
      <pubDate>Wed, 05 Feb 2025 13:22:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2499187</guid>
    </item>
    <item>
      <title>Performance-based transit subsidy allocation scheme to fulfill multiple policy criteria</title>
      <link>https://trid.trb.org/View/2434266</link>
      <description><![CDATA[Performance-based subsidy allocation schemes are typically intended to satisfy a single policy goal (e.g. social welfare maximization) and often do not include objective approaches to quantifying bus service efficiency. This paper proposes a framework for network data envelopment analysis and introduces an innovative transit subsidy allocation scheme with a fixed budget that fulfills multiple policy criteria. The proposed basic scheme minimizes the maximum deviation from efficient allocation in proportion to the operating scales across all routes in a two-stage production system. Multiple policy criteria are then added to the basic scheme as additional goal components. The proposed scheme is evaluated by using an empirical dataset of 344 subsidized intercity bus routes collected from 20 Taiwanese bus operators. The results demonstrate that the subsidies allocated on the basis of the proposed scheme can satisfy the policy criteria incorporated into the scheme. The proposed modeling framework is flexible, and therefore, local governments can easily incorporate policy criteria into the scheme according to their own interests and needs.]]></description>
      <pubDate>Thu, 17 Oct 2024 09:15:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2434266</guid>
    </item>
    <item>
      <title>Optimization of Scheduling and Timetabling for Multiple Electric Bus Lines Considering Nonlinear Energy Consumption Model</title>
      <link>https://trid.trb.org/View/2389679</link>
      <description><![CDATA[Timetabling and scheduling of electric buses (EBs) are crucial for a sustainable city transportation system. Most studies mainly focus on the scheduling and timetabling for one EB line based on the assumption that energy consumption of a battery is linear with distance. In this study, timetabling and scheduling for multiple EB lines are investigated by considering nonlinear energy consumption due to the dynamic load of buses. The optimization objectives are to minimize the number of vehicles and total operation costs, in which the constraints include the limitations of operation range and nonlinear energy consumption of the battery and the capacity of buses can be simultaneously charged at charging stations. Further, an improved particle swarm optimization algorithm is developed to obtain the optimal solution set. Compared with the existing schedule, the proposed schedule can not only reduce the number of vehicles and total charging costs but also distribute the charging periods during off-peak hours to reduce the impact on the urban electricity grid.]]></description>
      <pubDate>Tue, 01 Oct 2024 09:48:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2389679</guid>
    </item>
    <item>
      <title>A microscopic public transportation simulation framework based on machine learning</title>
      <link>https://trid.trb.org/View/2427848</link>
      <description><![CDATA[The evaluation of performance of public transportation, such as bus lines for example, is a major issue for operators. To be able to integrate specific and local behaviors, microscopic simulations of the lines, modelling each buses on a daily basis, brings an actual added value in terms of precision and quality. A scientific deadlock then appears regarding the parameterization of the simulation model. In order to be able to gather relevant performance indicators on a potential evolution of the configuration of the line, validated and modifiable simulation models need to be developed. This study aims at proposing a model development methodology based on a multi-agent simulation framework and data inputs extracted by a hybrid approach combining machine learning (ML) trained on actual bus data to predict travel times and probabilistic distributions to accurately estimate travel time variability. It also aims to propose a two-step validation framework that exhibits the performance of the obtained model on a case study based on actual data. The results of the proposed approach are validated by a real case study of three bus lines, including a number of simulation scenarios, to study the impacts of bus recovery time and bus control strategies on bus punctuality. The results obtained show that proposed hybrid approach combining ML with probabilistic distributions outperforms probabilistic distributions on average. Overall, the results show a good fit with the actual Key Performance Indicator (KPI) used by bus operators.]]></description>
      <pubDate>Mon, 30 Sep 2024 08:43:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2427848</guid>
    </item>
    <item>
      <title>The impact of ‘competition for the market’ regulatory designs on intercity bus prices</title>
      <link>https://trid.trb.org/View/2204345</link>
      <description><![CDATA[Spain regulates its intercity bus market by means of a ‘competition for the market’ mechanism, whose design has been modified several times in the last years. This implies that current services are operated under contracts whose conditions are heterogeneous. The authors take advantage of such fact to empirically measure the impact that regulatory designs may have on fares paid by the users. Controlling for the different determinant of bus prices at route level the results show very large differences between routes whose contracts were awarded under relatively open conditions compared to regionally regulated routes or old contracts whose concessions were extended in 1987 and have not been retendered since then. The observed difference between the cheapest and the most expensive services is to a great extent explained by the difference in the regulatory designs used to award each contract.]]></description>
      <pubDate>Mon, 02 Sep 2024 11:59:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2204345</guid>
    </item>
    <item>
      <title>Bi-Level Programming Model for Urban Bus Lanes' Layout</title>
      <link>https://trid.trb.org/View/2282678</link>
      <description><![CDATA[Planning of urban bus lane network is one of the most important measures to improve buses' efficiency and to embody bus priority fully. For effective arrangement of bus lanes, on the basis of traffic zones' division, considering accessibility constraint and the total bus lanes' length constraint, the bi-level programming model for urban bus lanes' layout is set up. The upper level problem is a multi-objective function which is to minimize the total travel time and the total bus lanes' length and the total transfer times; the lower level of the model is a capacity-constrained traffic assignment model that describes passenger flow assignment on bus lines. By this bi-level programming model, the optimal bus lines are selected from all possible bus lines, and so the corresponding bus lane network with the selected bus lines is also ascertained. The solution method using genetic algorithm of the bi-level programming model is also presented and by an example the design process is demonstrated.]]></description>
      <pubDate>Wed, 28 Aug 2024 17:00:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2282678</guid>
    </item>
    <item>
      <title>The Choice and Reasoning of the Bus Rapid Transit Systems for City Transport</title>
      <link>https://trid.trb.org/View/2417283</link>
      <description><![CDATA[The presented research is focused on the design of a new driving cycle of the Bus Rapid Transit (BRT) for the Kyiv city. This cycle consists of a complex of two types of sections. Each of them includes various phases of the traffic. A mathematical model was specified, which serves for defining the efficiency properties indices and for regimes of bus transport. The BRT are used within the bus lines. It was found, that two articles articulated buses are the most suitable choice, the MAZ-215 among them, for exploitation. At the same time, they provide the smallest fuel consumption together with the shorter operation time on the bus line as well as higher average speed at full and half loading. The optimal driving speeds of the steady traffic are the values of 50 km/h for section up to 1 km and 60 km/h or 70 km/h for section over 1 km. It was evaluated, that depending on the steady motion speed and the load level, the driving time of the BRT on the line varies from 20.1 min to 23.4 min, which is much lower than the driving time of a trolleybus on the same line according to the traffic schedule.]]></description>
      <pubDate>Tue, 20 Aug 2024 16:17:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2417283</guid>
    </item>
    <item>
      <title>Optimal design of electric bus short turning and interlining strategy</title>
      <link>https://trid.trb.org/View/2411035</link>
      <description><![CDATA[Short turning and interlining lines allow transit agency to circulate a small number of vehicles between high demanded segments and are efficient strategies for addressing the problem of vehicle underutilization in peak period. With the electrification of urban transit system, the application of these strategies is faced with new challenges due to the limited battery capacity and long charging time of battery electric buses. Without rigorous charging scheduling, the short turning and interlining strategies may not perform as intended. This study presents a comprehensive framework to deal with the joint problem of short turning and interlining line planning, frequency setting and charging scheduling. The authors formulate the problem as a mixed-integer nonlinear programming model and propose an exact solution approach. Numerical experiments have been carried out for the Beijing Third Ring bus network; the potential benefits of the strategy-based operation are demonstrated by compared with the optimized normal operation.]]></description>
      <pubDate>Fri, 16 Aug 2024 09:52:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2411035</guid>
    </item>
    <item>
      <title>Resilience-Based Approach to the Measurement of Headway Inconsistency</title>
      <link>https://trid.trb.org/View/2410536</link>
      <description><![CDATA[Maintaining a consistent headway is a primary goal in bus operation, but it poses a significant challenge because of fluctuating traffic conditions and uneven passenger demand. This leads to inconsistent headways and even bus bunching, resulting in negative consequences such as increased travel time and reduced vehicle capacity. Various control strategies have been developed to alleviate headway inconsistencies, but most of them have focused on whether an inconsistency occurs while overlooking its duration. This study proposes a resilience-based approach to measure headway inconsistencies considering both the depth and duration of the impacts with deviations from the optimal headway. The approach is devised to analyze the cumulative impacts of inconsistent headways comprehensively. It goes beyond addressing only extreme cases, such as bus bunching, and considers persistently uneven headways. We first identify vehicle trajectories from smart card data, then compute deviations from the center of the preceding and following vehicles as an index of impact. Using the concept of resilience, cumulative impacts are measured and their distribution is utilized to set the failure criterion. The approach is applied to 320 bus lines in Seoul to measure the deviations of headways and is used to analyze the characteristics of the bus lines and links where inconsistencies frequently occur. The proposed method enables transportation planners to identify factors that can lead to headway inconsistency, facilitating tailored and data-informed planning processes. This study provides a comprehensive framework that recognizes line-specific and link-specific factors, thereby contributing to enhancing the reliability and efficiency of public transportation systems.]]></description>
      <pubDate>Fri, 02 Aug 2024 08:43:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2410536</guid>
    </item>
    <item>
      <title>An Optimization Strategy for Truncating Ultralong Bus Lines Integrated with Metro Networks</title>
      <link>https://trid.trb.org/View/2399912</link>
      <description><![CDATA[For most ultralong bus lines, low punctuality rates and vehicle bunching are two main challenges. One potential strategy to solve these two problems is to split an ultralong line into two or three shorter lines according to historical passenger flow patterns as well as other presetting objectives and constraints. Thus, in this paper, a multiobjective optimization model is first established in consideration of both passenger flow distribution and coline metro networks. Then, the optimal truncated stop is determined by estimating the model results generated by enumerating each potential bus stop derived from related metro stops. The nondominated sorting genetic algorithm II (NSGA-II) is applied to solve the model efficiently. A case study conducted on a real bus line associated with metro networks in Beijing, China, demonstrates the efficiency of the optimization strategy adoption in terms of operating cost and passenger travel time, even with a slight increase in passenger cost. Besides, the multivehicle type is also referred in the experiments to verify economic efficiency to reduce operational costs.]]></description>
      <pubDate>Thu, 11 Jul 2024 13:52:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2399912</guid>
    </item>
    <item>
      <title>Subsidy Allocation Problem with Bus Frequency Setting Game: A Trilevel Formulation and Exact Algorithm</title>
      <link>https://trid.trb.org/View/2389471</link>
      <description><![CDATA[Typically, governments subcontract the operation of urban bus systems to several bus operators. In particular, the government aims to promote the service quality for passengers by introducing competition among bus operators and subsidizes bus operations to ensure affordable fares. However, most existing studies about subsidy allocation typically do not account for the competitive factors among bus operators and thus may underestimate the associated benefits. In this study, the authors investigate how the government allocates subsidies to minimize social costs, taking into account the competition among bus operators and passenger route decisions. The authors describe this problem as a trilevel optimization model and use a game-theoretic approach to characterize the market equilibrium of bus operators. Next, the authors transform the trilevel model into a mixed-integer programming problem with quadratic constraints and solve it using an exact algorithm with acceleration techniques. The results of numerical experiments demonstrate the computational efficiency of the proposed algorithm. Several valuable insights are derived: First, lines served by competing bus operators typically do not require subsidies. Second, competitive behavior decreases social costs (including bus operating costs and passenger travel costs) more effectively in cities in which the passengers assign higher value to time. Third, the competitive behavior may be guided by exogenous parameters, such as ticket prices, to approximate the optimum of urban bus systems.]]></description>
      <pubDate>Wed, 12 Jun 2024 16:03:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2389471</guid>
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