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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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    <item>
      <title>Analyzing ridesharing systems with flexible riders and fixed bus lines: case study from Norway</title>
      <link>https://trid.trb.org/View/2658005</link>
      <description><![CDATA[Ridesharing allows owners of private cars to share these with other travelers, filling up vacant seats. Based on a real case from Norway, we define and study the Ridesharing Problem with Flexible Riders and Fixed Lines (RPFRFL), where flexible riders can act either as passengers or drivers that can pick up other passengers. Moreover, the RPFRFL also considers fixed (bus) lines, to which drivers can deliver picked up passengers at a terminal for public transportation to their final destinations. We propose a mixed integer programming model and a path flow solution method to solve this problem. Based on a large number of test instances for our case study, we study the effects of considering flexible riders and the integration with fixed bus lines and show, for example, that more than 10% additional passengers can be serviced when 25% of the riders are flexible compared to the situation without these. Furthermore, our analyses indicate that there is great value in integrating the ridesharing planning with public transportation, i.e., where passengers can be transported through ridesharing to a bus terminal for further transport. These results demonstrate that including the terminal delivery option gives 17.2% higher average number of serviced passengers compared to the case without. Furthermore, we analyze the riders’ willingness to participate in ridesharing under different conditions and compare the performance of our solution method with an existing ridesharing platform. The results show that our modeling approach and the path flow solution method have the potential to significantly improve the efficiency of the ridesharing system compared to the ridesharing platform currently in use.]]></description>
      <pubDate>Fri, 27 Mar 2026 10:13:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658005</guid>
    </item>
    <item>
      <title>When flexibility beats fixed routes: Quantifying microtransit efficiency-emission trade-offs using AMOID</title>
      <link>https://trid.trb.org/View/2659606</link>
      <description><![CDATA[Microtransit is emerging as a key solution for short-distance travel, yet the efficiency-environmental trade-offs between demand-responsive and fixed-route systems remain unclear. We introduce AMOID, a data-driven model leveraging individual travel trajectories to automate hybrid system planning and evaluation. Departing from aggregate data methods, AMOID tailors solutions to individual demand, considering multi-modal collaboration. In Tampa, Florida, demand-responsive microtransit achieves 229% higher operational efficiency, 183% more ridership, 40% lower greenhouse gas emissions than fixed-route systems. However, fixed-route systems dominate when demand exceeds 800 trips/(day·mile2). Operational scale dynamically shifts these thresholds: reducing the fleet by half lowers the efficiency crossover threshold for fixed-route dominance by 40–46%; conversely, expanding the service area by 135% decreases the threshold by 60%. These findings reveal how demand and operational scale mediate modal efficiency, providing insights for planners to optimize microtransit deployment. AMOID bridges the gap between theoretical models and practical decision-making, enabling sustainable urban mobility.]]></description>
      <pubDate>Thu, 26 Feb 2026 09:22:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2659606</guid>
    </item>
    <item>
      <title>Modeling boardings and alightings by route at transit stops</title>
      <link>https://trid.trb.org/View/2625364</link>
      <description><![CDATA[This research develops stop-level models for boardings and alightings by route for fixed route bus-based services. All previous research on stop-level ridership models has captured the effect of land use or socioeconomics only in the proximity of the subject stop. However, this study also captures the effect of land use in the proximity of transit stops that are located downstream or upstream of the subject stop. We have used ridership data from 1188 transit stops in the city of Gainesville (Florida, USA) for the month of October 2019 (pre-pandemic sample). The models indicate that boardings/alightings at a stop can change not only because of land-use changes in the vicinity of the stop but also because of the changes downstream/upstream of the stop along the transit route. The models also capture the effect of opportunities for transfers upstream/downstream of the subject stop on the alightings and boardings at the subject stop. All these additional empirical insights were obtained after controlling for service characteristics and land-use and socio-economic factors in the vicinity of the stops and variables capturing the service characteristics.]]></description>
      <pubDate>Thu, 19 Feb 2026 10:53:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2625364</guid>
    </item>
    <item>
      <title>Partnering with transportation network companies (TNCs) for low-demand service: is it viable and beneficial for transit agencies?</title>
      <link>https://trid.trb.org/View/2606313</link>
      <description><![CDATA[In low-demand areas or during off-peak hours, fixed-route bus services often show low productivity when maintaining regular headways. Reducing headways further decreases service quality, presenting a challenge for transit agencies. This paper proposes a novel approach to solve the low productivity issue, by forming a partnership between transit agencies and Transportation Network Companies (TNCs), where TNC vehicles substitute fixed-route buses in certain segments. The study introduces a decision-making framework to help transit agencies assess when and where such partnerships are operationally feasible and financially sustainable. It identifies key factors that influence the viability of TNC substitution, including vehicle hours, mileage, and passenger loads. Based on these factors, the paper explores various compensation schemes and determines the cost of TNC operations—a critical component of the framework. The proposed framework is evaluated using a real-world case study in Long Beach, California, USA. Findings suggest that in low-demand scenarios, specifically when the number of passengers per stop is fewer than 0.5, replacing buses with TNC services reduces operating costs. The results also indicate that transit agencies should consider both cost savings and passenger experience while making substitution decisions, as truncating longer route segments may yield lower savings but may improve service for additional passengers. Overall, this research provides valuable insights for transit practitioners seeking to reduce expenses and enhance service quality in low-demand areas and off-peak hours through innovative public–private partnerships with TNCs.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2606313</guid>
    </item>
    <item>
      <title>Synthesizing Microtransit and Fixed Route Transit via Rider Hand Off to Improve Transit Efficiency</title>
      <link>https://trid.trb.org/View/2640190</link>
      <description><![CDATA[Microtransit programs can improve local mobility, but they often operate separately from fixed route bus networks. This separation can create gaps in connectivity and reduce the potential efficiency of both systems. This project will study how rider hand off strategies, where microtransit vehicles bring passengers directly to fixed route transit, can strengthen system performance. Using data from CTtransit, microtransit logs, and synthetic demand models, the research will simulate multimodal operations and evaluate how pickup schedules and transfer points influence wait times, travel times, and network utilization.

The project will develop an optimization framework to identify operating strategies that improve rider transfers and increase the efficiency of both modes. Scenario testing will measure the effects of integration on cost, ridership patterns, and service quality. The results will provide agencies with practical guidance on how to coordinate microtransit and fixed route services in ways that improve reliability and expand access to transit. These findings can support broader efforts to enhance mobility in Connecticut and inform similar initiatives in other regions.]]></description>
      <pubDate>Thu, 11 Dec 2025 13:47:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2640190</guid>
    </item>
    <item>
      <title>Optimal Design of Bimodal Electric Bus Networks with Solar Battery Swapping Assistance</title>
      <link>https://trid.trb.org/View/2573066</link>
      <description><![CDATA[The collaboration of demand-responsive transit and fixed-route transit enhances public transport efficiency and competitiveness. With the trend of promoting electrification, electric buses would face challenges such as range anxiety and power grid strain, especially in large cities with multimodal public transport systems. The integration of solar photovoltaic and battery swapping technology is anticipated to provide effective solutions to these issues through utilizing solar energy and achieving rapid replenishment of electric bus energy. Existing literature rarely discusses the impact of solar battery swapping on the operation of electric bus systems, nor does it investigate the macroparameter design of electric bus networks. To fill this gap, in this study, a continuous approximation-based model is established to optimize the density of bus stops, solar battery swapping stations, and time-varying headway within a bimodal electric bus network in which demand-responsive transit serves as paired lines of fixed-route transit. Results indicate that (1) compared with the conventional electric bus systems with depot charging modes, adapting the proposed system contributes to simultaneously enhancing service quality while reducing system costs. System cost and agency cost can be significantly reduced by 7.36% and 16%, respectively. (2) The system presents greater advantages under high irradiance conditions, with system costs decreasing as the solar panel areas increase when solar power is abundant. (3) The system exhibits economies of scale, such that cities with ample passengers and higher value of time can enjoy more benefits from the proposed mode. Such results can be utilized to provide a reference for designing large-scale electric bus networks with solar battery swapping from a strategic level for varied cities.]]></description>
      <pubDate>Fri, 26 Sep 2025 13:39:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2573066</guid>
    </item>
    <item>
      <title>Carbon emission reduction potential of on-demand transit replacing fixed-route transit</title>
      <link>https://trid.trb.org/View/2599174</link>
      <description><![CDATA[This study examines the potential of on-demand transit to reduce carbon emissions compared to fixed-route transit in Shanghai, China, with both services using electric vehicles. The authors first analyze how carbon emission reductions vary across different time periods. The results show that on-demand transit is more effective in replacing fixed-route transit during evening and night periods to achieve carbon emission reduction. Next, the authors use CatBoost models to explore how route characteristics influence carbon emission reduction. For per capita carbon emission reductions, demand, route length, and route curvature are important factors. On the other hand, when considering the maximum demand for achieving carbon emission reductions (critical demand threshold), the distribution of passengers across the route (sectional load factor) plays more important roles than the physical characteristic of the route. Additionally, increasing the number of vehicles while reducing their capacity can accommodate more passengers and improve the potential for emission reduction.]]></description>
      <pubDate>Wed, 24 Sep 2025 15:31:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2599174</guid>
    </item>
    <item>
      <title>Transforming travel experience in low density areas: evidence from a DRT pilot study and simulation model</title>
      <link>https://trid.trb.org/View/2571406</link>
      <description><![CDATA[In low density areas, due to limited economic resources, public transport (PT) companies usually operate services with low frequency, poor accessibility and reliability and high waiting times at stops. Several studies highlighted that introducing Demand Responsive Transport Services (DRTs) can improve PT performance in these areas. In Italy, several DRTs have been launched, characterized by flexible schedules with different operational configurations: fixed route, with and without detours and flexible route. Considering the importance of sharing lessons from pilots, the paper presents a DRT pilot study, conducted in Palermo (Italy) within the WEAKI TRANSIT project, identifying strategies for planning and designing on-demand shared systems. The pilot was conducted in a suburban area in the north of Palermo, covering about 10.5 km² with the neighbourhoods of Partanna Mondello and Tommaso Natale. This area is poorly served by PT companies with low-frequency and low-reliability bus lines, thus a stop-based DRT service with two fixed routes and detours was hypothesized. The pilot was conducted during November and December 2022, with four cars, operating from 3 to 7 p.m., except Sunday. The service, free of charge, was addressed to students and teaching staff by University of Palermo. Through SP surveys, simulation model and pilot, the authors evaluated operational performance of the services (i.e. travel distance, waiting and in-vehicle times). The authors found the introduction of DRTs lead to increasing accessibility to main transit hubs and facilities, and a decrease in waiting times at stops and travel times. Nevertheless, considerations about financial feasibility and legal framework are highlighted.]]></description>
      <pubDate>Tue, 02 Sep 2025 08:50:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2571406</guid>
    </item>
    <item>
      <title>Optimal design of fixed-route and demand-responsive transit with a dynamic stop strategy</title>
      <link>https://trid.trb.org/View/2578331</link>
      <description><![CDATA[To address the high detour costs associated with Demand-Responsive Transit (DRT) when feeding Fixed-Route Transit (FRT), this paper proposes an integration between FRT and DRT based on a dynamic stop strategy. This strategy allows passengers to, with an acceptable walking distance, connect their origins/destinations with dynamic stops. These stops have spacings that are randomly and uniformly distributed and are assigned to passengers upon their requests for DRT services. In this way, DRT does not need to pick up/drop off passengers at their origins/destinations, hence reducing the detour distance especially when the origins/destinations are far from FRT stops. Passengers may walk, take DRT directly, or combine the two to access FRT services. To deal with the modeling complexity that arises from the relationship between the three feeder modes, the authors divide the catchment zone of a FRT stop into different areas corresponding to different feeder modes, and evaluate transit agency and user costs based on the shapes of these areas using a parsimonious continuum approach. The optimal design for the integrated system is then formulated as a mixed-integer program that aims to minimize the total system cost, a combination of agency and user costs. Numerical experiments are conducted to compare the performance of the proposed system with two related transit systems in different scenarios. The results show that the proposed system could reduce agency costs by over 15% across different transit demand levels at the expense of minor changes in system costs, and demonstrate strong robustness to various potential changes in future.]]></description>
      <pubDate>Thu, 21 Aug 2025 09:19:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2578331</guid>
    </item>
    <item>
      <title>Simulation based pre-implementation cost evaluation framework for integrated public transit services</title>
      <link>https://trid.trb.org/View/2562534</link>
      <description><![CDATA[The growing demand for integrated and shared mobility services has resulted in a number of public–private partnerships, where public transit agencies and mobility companies collaborate to expand transit service coverage. Nonetheless, many collaborative efforts have failed due to financial restraints and low ridership. The failure of many of the integrated systems can be ascribed to the ineffective pre-implementation evaluation of the integrated system. The lack of a reliable performance evaluation tool capable of assessing the integrated system’s performance prior to implementation could be the case of such failures. Considering this gap, this paper proposes a support tool for decision process of multimodal integrated transport system that examines the viability of an integrated mobility service system comprised of a Fixed Route Transit (FRT) service system and on-demand services. The decision process is powered by an agent-based simulation framework that tests scenarios covering various modal integration strategies. The on-demand services could be Demand Response Transit (DRT) and Transportation Network Company (TNC) services, that particularly act as feeders for FRT to ensure first and last-mile connectivity. This study proposes four integration-strategies with ten potential integration scenarios and four non-integration scenarios, comprising a total of fourteen possible scenarios to complete a trip between any origin–destination pair. Using the agent-based simulation model, various scenarios can be constructed for origin–destination pairs, and based on the generalized system cost, the preferred integration strategy can be selected. The proposed model analyzed the generalized system cost for each scenario by incorporating three key cost components: user cost, agency cost, and external costs. The proposed method was implemented on two different networks, which are the Sioux Falls network and a real-world case study of the Morristown city network in Tennessee, United States. Simulation outcomes indicate that 69% of trips in the Sioux Falls network and 73% of trips in Morristown could be connected to the existing FRT network using feeder services as first and last-mile connectivity solutions. The results suggest that a properly evaluated integrated system could enhance the accessibility of FRT significantly. Therefore, the proposed methodology assesses the advantages of the integrated system prior to its implementation, assisting transit planners and policymakers in the efficient execution of integration strategies and enhancing user experience and mobility.]]></description>
      <pubDate>Thu, 26 Jun 2025 16:12:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2562534</guid>
    </item>
    <item>
      <title>Joint Design of Fixed-Route and Paratransit Services with Autonomous Pods</title>
      <link>https://trid.trb.org/View/2563759</link>
      <description><![CDATA[This study envisions a jointly designed transit system comprised of a fixed-route (FR) service and a paratransit (PT) service. The integration of the two services is inspired by the potential application of modular autonomous vehicles, or pods, in transit. Constrained by a fixed budget, the operator of the joint system  aims to minimize the total user cost by optimally allocating pods between the two services. To formulate the operator’s design problem, the authors propose a stylized model, in which the FR service features a simple 2D grid route structure overlaying on a square city, and the PT service is designed as a general on-demand system that can be configured in different modes of operations. A case study is conducted using transit data from the Chicago region. The authors find that joint design helps prevent resource misallocation that could render a service dysfunctional under insufficient budgets, although its potential to reduce total user cost is limited. Enforcing the equal-access constraint—requiring that PT users incur no greater cost than FR users—tends to help PT users at the expense of FR users, though the overall impact on total user cost is insignificant. Modularity enables the formation of pod trains using small pods, which benefits FR operations, particularly when the design is not tightly constrained by budget. In contrast, automation delivers greater service improvements for PT users, whose more labor-intensive cost structure makes them more sensitive to efficiency gains, especially under tight budgets. Among the PT service modes, ridesharing is the most flexible, allowing for a wide range of service levels based on the available budget.]]></description>
      <pubDate>Fri, 20 Jun 2025 17:03:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2563759</guid>
    </item>
    <item>
      <title>Impact of Modularized Autonomous Vehicles on Transit System Design and Operations</title>
      <link>https://trid.trb.org/View/2559152</link>
      <description><![CDATA[This study envisions a jointly designed transit system comprised of a fixed-route (FR) service and a paratransit (PT) service. The integration of the two services is inspired by the potential application of modular autonomous vehicles, or pods, in transit. Constrained by a fixed budget, the operator of the joint system aims to minimize the total user cost by optimally allocating pods between the two services. To formulate the operator's design problem, the authors propose a stylized model, in which the FR service features a simple 2D grid route structure overlaying on a square city, and the PT service is designed as a general on-demand system that can be configured in different modes of operations. A case study is conducted using transit data from the Chicago region. The authors find that joint design helps prevent resource misallocation that could render a service dysfunctional under insufficient budgets, although its potential to reduce total user cost is limited. Enforcing the equal-access constraint—requiring that PT users incur no greater cost than FR users—tends to help PT users at the expense of FR users, though the overall impact on total user cost is insignificant. Modularity enables the formation of pod trains using small pods, which benefits FR operations, particularly when the design is not tightly constrained by budget. In contrast, automation delivers greater service improvements for PT users, whose more labor-intensive cost structure makes them more sensitive to efficiency gains, especially under tight budgets. Among the PT service modes, ridesharing is the most flexible, allowing for a wide range of service levels based on the available budget.]]></description>
      <pubDate>Thu, 12 Jun 2025 13:25:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2559152</guid>
    </item>
    <item>
      <title>Time-series analysis approach for improving energy efficiency of fixed-route passenger vessel in short-sea shipping</title>
      <link>https://trid.trb.org/View/2557338</link>
      <description><![CDATA[Improving ship energy efficiency is critical for reducing operational costs and meeting increasingly stringent climate regulations. However, existing approaches often target variable-route vessels and overlook the specific operational constraints of short-sea, fixed-route passenger services. This paper presents a novel data-driven framework that applies time-series analysis techniques to optimize the speed profiles of fixed-route passenger vessels. The framework introduces a spatiotemporal aggregation method for fusing operational, environmental, and navigational data from onboard IoT devices and external sources, enabling the derivation of a new efficiency score that jointly considers fuel consumption and voyage duration. By applying clustering techniques to this efficiency metric, voyages are categorized for targeted optimization. The framework evaluates four distinct time-series models across a dataset of 1755 real-world voyages collected over 15 months in southern Sweden. The findings highlight the effectiveness of time-series analysis approach for optimizing vessel voyages within the context of constrained landscapes, as often seen in short-sea shipping.]]></description>
      <pubDate>Sat, 31 May 2025 15:16:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2557338</guid>
    </item>
    <item>
      <title>Research on speed optimization of fixed route ship with low data dependence</title>
      <link>https://trid.trb.org/View/2545018</link>
      <description><![CDATA[A low data demand long-term fuel consumption prediction model suitable for variable pitch propeller ships has been established for the first time, and a segmented route speed optimization method has been provided. The event triggered Informer (ET-Informer) algorithm has the ability to predict long-term high-precision sequences and capture key data to reduce data redundancy and improve computational efficiency. The event triggering mechanism allows for data loss at a certain stage, improving the algorithm's fault tolerance and reducing communication requirements. An ordered sample clustering algorithm based on the weighted event-triggered mechanism is introduced, enabling the adjustment of clustering weights according to demand. The threshold for dynamically adjusting similarity measures triggered by events can solve the problem of uneven clustering distribution. This study reduces data dependency and improves the fault tolerance and accuracy of speed optimization through two aspects: fuel consumption model prediction and route segment speed optimization. The proposed algorithm was validated using real-world data from 24 passenger ferry voyages on major international routes in 2021, achieving a fuel consumption prediction accuracy of 98.4 % and a 4.4 % reduction in fuel consumption, while maintaining travel time. The results confirm the effectiveness, robustness, and practical applicability of the fixed-route speed optimization algorithm.]]></description>
      <pubDate>Tue, 27 May 2025 09:33:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2545018</guid>
    </item>
    <item>
      <title>Column-and-row generation based exact algorithm for relay-based on-demand delivery systems</title>
      <link>https://trid.trb.org/View/2540429</link>
      <description><![CDATA[This paper studies an operation optimization problem in a relay-based on-demand delivery system that uses couriers and drones to transport customers’ parcels. For a batch of customer orders with their delivery due times, the system must decide which orders to accept and which courier to dispatch to pick up each accepted order and transport it to a suitable station, from where a drone will transport it to another station and then another courier will transport it to its final destination. Using mixed-integer linear programing, this paper formulates a novel arc-based set-packing model with two types of columns, i.e., drone plans and courier plans, to maximize the profit from transporting a batch of orders. By combining branch-and-price, column-and-row generation, and some tailored acceleration tactics, an exact algorithm is designed and implemented to efficiently solve the model. Experimental results validate the efficiency of the proposed exact algorithm. Moreover, the authors find that large numbers of couriers, drones, or stations do not always substantially improve the system’s performance; if order due times are urgent, the benefit of drones (couriers) is more (less) significant. The model’s robustness and the applicability of the authors' methodology in large-scale applications are validated.]]></description>
      <pubDate>Tue, 27 May 2025 09:31:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2540429</guid>
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