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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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    <language>en-us</language>
    <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>Game theory-based lane-changing decisions in adverse weather conditions</title>
      <link>https://trid.trb.org/View/2688590</link>
      <description><![CDATA[Adverse weather significantly impacts driving safety and increases road accidents. Lane-changing is essential for efficient vehicle operation, but its influencing factors are complex under adverse weather. This study presents an improved lane-changing safety distance model by introducing the fuzzy evaluation quantification value of severe weather for the decision-making of lane-changing. In addition, the Gazis-Herman-Rothery model, an anchoring effect model and the full velocity difference model are refined. Based on a non-cooperative dynamic game (NCDG) model, a joint simulation environment is developed using Python. Simulation of urban mobility is conducted to simulate experiments. The simulation results show that using the improved lane changing model and NCDG model, the optimal reduction rates for NIC and ICS are 12.7% and 15.7%, respectively, and the optimal increase in successful lane changing frequency is 16.9%. Vehicles can optimise driving strategies in conflicts, improving efficiency and safety.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2688590</guid>
    </item>
    <item>
      <title>Integrated optimization of train stop planning, train timetabling, and maintenance planning for railway container system under passenger transport mode</title>
      <link>https://trid.trb.org/View/2686681</link>
      <description><![CDATA[The Railway Container System under Passenger Transport Mode (RCSPTM) is an organizational strategy that applies passenger train operating practices to container transport, aiming to enhance transport efficiency. Its efficient operation requires the integrated coordination of three key planning tasks: train stop planning, timetabling, and maintenance planning. As these plans are highly interdependent, sequential optimization often leads to suboptimal results. To address this challenge, this paper proposes an integrated optimization approach, formulated as a mixed-integer linear programming model that embeds stop decisions into the timetabling process and represents maintenance operations as a “virtual train” scheduled together with real trains. The model addresses three aspects of train operations: it allocates container demand across services, avoids scheduling conflicts among trains, and minimizes disruptions from maintenance activities. The effectiveness of the model is validated through computational experiments using the CPLEX solver on both small-scale cases and the Beijing-Shanghai railway corridor. Compared with pre-planned maintenance approaches, the integrated optimization method eliminates unnecessary stops and reduces computation time by 47.5%, demonstrating its computational and operational efficiency. More importantly, it shortens the system-wide committable transit period from 3 days to 2 days, thereby enabling guaranteed delivery within stricter time windows for time-sensitive shipments.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686681</guid>
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    <item>
      <title>Maritime container transportation efficiency through robotic process automation: a digital transformation perspective</title>
      <link>https://trid.trb.org/View/2685407</link>
      <description><![CDATA[Organizations increasingly use robotic process automation (RPA) as a transformative technology to improve operational efficiency and accuracy, by automating rule-based, repetitive tasks. Operating 24/7, RPA enables organizations to reduce processing time, minimize errors, and enhance workflow continuity across business functions. This study bridges theory and practice by applying established automation concepts to a real-world maritime logistics setting through a large-scale field implementation. We present an empirical case study from a major container shipping company, examining the deployment of RPA across three core operational processes: booking, invoicing, and inter-system transfers. The study follows a pre–post-field evaluation design over a one-month period, combining system log analysis with operational observations to assess efficiency, accuracy, and execution stability. Prior to implementation, a structured RPA program was conducted, including organization-wide training and a participatory process-identification phase, enabling the systematic selection and prioritization of automation candidates based on operational criticality, feasibility, and workforce input. The findings demonstrate that RPA delivers substantial reductions in cycle times, significantly lowers human error incidence, and maintains stable execution performance under continuous operation. Beyond operational gains, the study adopts a theoretical lens grounded in Diffusion of Innovations and Socio-Technical Systems theory to interpret organizational readiness, employee perceptions, and alignment between technology and work practices. The results show that RPA can be integrated as a core operational capability rather than a peripheral efficiency tool. Overall, the study provides a replicable, practice-oriented framework for maritime firms seeking to industrialize automation while maintaining organizational alignment and operational resilience. The findings highlight the role of RPA as a foundational enabler of maritime digital transformation and a practical stepping stone toward AI-assisted logistics workflows.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:29:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685407</guid>
    </item>
    <item>
      <title>A multi-objective approach for the integrated allocation of quay cranes, internal trucks, and yard cranes in container terminal considering actual handling efficiency</title>
      <link>https://trid.trb.org/View/2684676</link>
      <description><![CDATA[The growth of maritime container trade volume and the frequent berthing of ships require container terminals to shorten the ship turnaround time. As the main production tool of container terminal, the reasonable allocation of equipment resources is conducive to minimizing the ship turnaround time and the operating cost of container terminal. In order to provide a reasonable and refined equipment configuration scheme, this paper studies the joint allocation of quay cranes (QCs), internal trucks (ITs), and yard cranes (YCs) in container terminal with consideration of container batch operations. Two formulas are proposed to measure the relationship between the number of IT, QC work efficiency, and YC work efficiency. A multi-objective mixed integer programming model for the joint allocation of QCs, ITs, and YCs is established to minimize the ship turnaround time, the operating cost of the terminal side, and the operating cost of the yard side. Among them, three configuration profile decision variables are proposed to describe the equipment allocation scheme. To solve this problem, an enhanced multi-objective evolutionary algorithm based on the fitness evaluation mechanism of fuzzy correlation entropy is designed, and an adaptive local reinforcement search strategy founded on tabu search and multiple neighborhood structures is introduced to improve the global search capability. Finally, the Shanghai Port is taken as a case study, and experiments of different scales verify the effectiveness of the model and method.]]></description>
      <pubDate>Wed, 01 Jul 2026 09:36:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2684676</guid>
    </item>
    <item>
      <title>From gate to runway: A systematic review of airport ground operations optimization</title>
      <link>https://trid.trb.org/View/2681277</link>
      <description><![CDATA[Over the past few decades, the domain of airline and airport ground operations has been extensively studied by numerous researchers. Many of these studies have focused on optimizing various aspects of airline and airport ground operations using operations research techniques. We provide an in-depth review of the literature in this domain comprising 199 scientific papers. We have employed bibliometric and network analysis tools to complete a systematic literature mapping, identifying 7 key functional areas in airport ground operations: airport gate assignment, boarding process and strategies, turnaround process, baggage handling, ground workforce planning and scheduling, aircraft taxiing and ground movements, and ground support equipment handling. For each area, we explore problems, modeling approaches, and solution methods. Furthermore, the review identifies specific future research directions relevant to the 7 key functional areas of ground operations. The overarching prospective research paths center on algorithmic advancements, adaptability to uncertainty, integration between subdomains, and inclusion of external aspects.]]></description>
      <pubDate>Tue, 30 Jun 2026 16:54:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2681277</guid>
    </item>
    <item>
      <title>Psychosocial demands of subordinate work in delivery platform companies: Control procedures and effects on the health of delivery workers</title>
      <link>https://trid.trb.org/View/2708810</link>
      <description><![CDATA[Background:The management of precarious work of delivery workers (DW) by delivery platform companies (DPC) incorporates technologies that deepen the subordination of this workforce. The demands placed on DW to carry out their tasks can compromise their health.Objective:To analyze the contradictory demands of work subordinated to DPC and their repercussions on health, as opposed to the regulation strategies adopted by DW to prevent illnesses and accidents.Methods:A situated analysis of the activity of DW was carried out based on the assumptions of Ergonomic Work Analysis in Salvador, Bahia, Brazil, in 2022. General and systematic observations were carried out, emphasizing the tasks of waiting for and receiving delivery orders and collecting goods, as well as self-confrontation interviews with DW.Results:DPC are new spaces for the exploitation and precariousness of work, still operating without regulation. DPC use technology to restrict decision-making and intensify work. This increases insecurity by reducing the spaces for regulation in the face of the unpredictability of street work and the pressure of low remuneration. Consequently, there are psychosocial and physical demands associated with work accidents and illness.Conclusion:Expanding the autonomy of these workers in terms of managing their own work and eliminating mechanisms that promote its intensification are measures required to prevent accidents and illness.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2708810</guid>
    </item>
    <item>
      <title>A Q-Learning-Based Neighborhood Search for Seaside Vehicle Dispatching and Resource Scheduling at Automated Container Terminals</title>
      <link>https://trid.trb.org/View/2617819</link>
      <description><![CDATA[The development of automated container terminals faces the challenge of bridging the gap between the increasing volume of container operations and restricted resources, particularly at the seaside of the terminal. Recognizing the pressing need for effective scheduling and decision-making processes, the industry targets two operational challenges: 1) managing limited apron resources, including vehicles, quay cranes, and traffic lanes; and 2) addressing the operation complexities brought by handling twist-locks. To address this gap, this study proposes a seaside vehicle dispatching and resource scheduling problem, which is formulated as a mixed integer linear programming model. A Q-learning-based neighborhood search is developed along with the proposal of a matheuristic method to obtain high-quality initial solutions. The experiments demonstrate that the proposed approach consistently delivers superior solutions over the benchmarks, significantly advancing the management of automated container terminal operations.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2617819</guid>
    </item>
    <item>
      <title>Privacy-Preserving and Passenger-Oriented Solutions for Air-Rail Multimodal Travels</title>
      <link>https://trid.trb.org/View/2671007</link>
      <description><![CDATA[Nowadays passenger travels are more and more multimodal. Often advocated as the way to follow to strike a balance between sustainability and travel time, air-rail is a prominent example of multimodality. To accommodate the fast-growing business the travel and tourism industry is experiencing, operators are going through a continuous digital transformation including solutions based on wireless connectivity, smart-sensors, Internet of Things, and Artificial Intelligence. The goal is twofold: improving passenger processing and operations, and passenger experience. On the other hand, significant challenges to tackle and opportunities to unfold in terms of security, privacy, and optimization, are still only partially addressed. The EU H2020 E-CORRIDOR project develops a secure, collaborative, and confidential framework for information sharing and analysis. Solutions for the air-rail multimodal pilot seek to improve passenger experience, perform seamless authentication, enhance the cybersecurity posture of the transport operators, break down data silos existing among stakeholders, and better support Passenger with Reduced Mobility (PRM) and coordination among operators. This paper presents some of such solutions where privacy is the keystone.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671007</guid>
    </item>
    <item>
      <title>The More You Know: Digital Twins of Travelers</title>
      <link>https://trid.trb.org/View/2670993</link>
      <description><![CDATA[Despite increasing digitalization, rail operators and other mobility service providers often need more real-time information regarding the occupancy of trains and stations. Worse, only general assumptions regarding passengers’ specific destinations, individual needs, and current and past experiences can be made. Digital Twins of Travelers (DTT) address the issue by holding real-time digital representations of passengers throughout their journey from start to destination. Being informed about a passenger’s route instead of isolated sections enables customized real-time forecasts, accessibility information for each transfer location, and veridical updates about how much time may be spent there. For example, a traveler would benefit directly when parts of a journey must be rescheduled due to delays on the original route. When continuing with means of transportation different from those chosen initially, forecasts and other information can be immediately adapted to the new route. In the same scenario, mobility service providers would benefit by being informed about occupancy changes, allowing them to prioritize scheduled connections if necessary. DTT consist of a real-world twin, its digital counterpart, and an interchange component linking them. The digital twin represents how travelers experience current events, holds information regarding their individual itineraries’ progress, and can exchange information with mobility service providers. DDT's purposes range from supporting passengers in real-time by providing information relevant to their journey milestones, analyzing the effect of events such as delays on the travel experience, to helping to align transport services with the existing demand.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2670993</guid>
    </item>
    <item>
      <title>Results from CEDR-Work Done Around Intelligent Access</title>
      <link>https://trid.trb.org/View/2670942</link>
      <description><![CDATA[The working group Road Freight Transport in CEDR (Conference of European Directors of Roads) performs different tasks. One is about Intelligent Access, later only referred to as IA. The used definition of IA is to ensure “the right vehicle on the right road at the right time with the right weight”. The goal for the work is to collect best practice of IA and recommendations for implementation. IA is a rather new concept in Europe but has been used in Australia for more than 15 years (TCA 2018). Conclusions from the work so far are. A survey and in-depth interviews show that National Road Authorities sees the concept of IA as something with many possibilities. Using IA as an enforcement tool is the most obvious interpretation of the concept and when scaling up also other opportunities become visible, such as better coordination of traffic and logistics, better use of infrastructure, control of emission zones, monitoring of abnormal transport and transport of dangerous goods. This gives possibilities for almost all stakeholders and therefore also for society. In this way, can also NRAs improve the quality of their services. The example from Italy, there you use IA for abnormal transports, shows a use case that give benefits to all involved and showing benefits and/or incentives for all involved will be important for the implementation of IA.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2670942</guid>
    </item>
    <item>
      <title>Vehicle Dynamics—Fundamentals</title>
      <link>https://trid.trb.org/View/2671962</link>
      <description><![CDATA[This Chapter presents the fundamental concepts of vehicle dynamics, in a rigorous yet relatively brief fashion. Bearing in mind the lack of unanimous conventions and stressing the need to fully control the hypotheses behind any model, formula or reasoning, this Chapter presents the three constituents of any (full) vehicle dynamics model: constitutive equations (tire model), congruence equations (kinematics), equilibrium equations (rigid body dynamics). Then, further insights and practical considerations are provided on a bunch of relevant aspects, including: radius of curvature (often misunderstood), sideslip angle (often not investigated with adequate depth), classical—and novel—perspectives on understeer and steady-state handling behavior.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671962</guid>
    </item>
    <item>
      <title>Optimization Control of Automotive Active Suspension Based on Deep Deterministic Policy Gradient Algorithm</title>
      <link>https://trid.trb.org/View/2711447</link>
      <description><![CDATA[The suspension system of a car is a core component that affects the smoothness and handling stability of the vehicle. Compared to traditional passive and semi-active suspensions, active suspension has greater potential for performance improvement by actively outputting control force through actuators. However, the design of its controller faces challenges such as model uncertainty, road excitation randomness, and multi-objective optimization. This article proposes an active suspension optimization control strategy based on the Deep Deterministic Policy Gradient (DDPG) algorithm. Firstly, a two degree of freedom 1/4 vehicle active suspension dynamic model was established, which includes actuator dynamics. Subsequently, a comprehensive reward function was designed with the optimization objectives of vehicle vertical acceleration, suspension dynamic stroke, and tire dynamic load, taking into account both actuator output force and energy consumption. The intelligent agent (Actor Critic network) learns the optimal control strategy through continuous interaction with the environment (suspension model), without relying on an accurate system model. The simulation experiment was conducted on the MATLAB/Simulink platform, using filtered white noise to simulate random road inputs. The results show that compared with traditional methods such as linear quadratic regulator and ceiling damping control, the proposed DDPG controller reduces the vertical acceleration (smoothness) of the vehicle body by about 31.2% and 22.5%, while constraining the suspension dynamic stroke and tire dynamic load within safety limits, demonstrating superior comprehensive performance and robustness. This study provides new ideas for intelligent control of active suspension under complex working conditions.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2711447</guid>
    </item>
    <item>
      <title>Real-Time Detection of Ground Taxiing Conflicts at Multi-Runway Airports: Spatiotemporal Trajectory Association Algorithm Based on Graph Neural Networks (GNNs)</title>
      <link>https://trid.trb.org/View/2710822</link>
      <description><![CDATA[With the continuous increase in ground traffic density at large hub airports and the parallel operation of multiple aircraft in complex taxiway networks, the number of potential conflict points increases exponentially. Existing rule-based conflict detection methods suffer from high false alarm rates and insufficient real-time performance in dynamic environments. This paper proposes a spatiotemporal trajectory association algorithm based on graph neural networks (GNNs). First, the airport taxiway network is abstracted as a topological graph structure, with nodes representing taxiway intersections and parking positions, and edges representing taxiing paths. Second, a spatiotemporal graph convolutional module is constructed to capture the spatial dependence and temporal evolution characteristics of aircraft trajectories. Then, a multi-head attention mechanism is designed to dynamically associate the interaction behavior patterns of multiple aircraft. Finally, real-time prediction of conflict risks is achieved through end-to-end training. In a three-month validation study using real-world operational data from an international hub airport, the algorithm maintains a high collision detection accuracy of 93.5%-94.9%, with a median false alarm rate of 8.85% and a response time reduced to a minimum of 1.9 seconds, providing effective technical support for airport ground operations safety management.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2710822</guid>
    </item>
    <item>
      <title>Development and implementation of an advanced robust control strategy for quarter-car active suspension systems</title>
      <link>https://trid.trb.org/View/2701313</link>
      <description><![CDATA[This study investigates the development of an advanced robust control strategy for a quarter-car active suspension system to optimize ride comfort and road handling. Traditional PID controllers struggle with trade-offs between comfort and stability under real-world conditions like variable road profiles and parametric uncertainties. To address this, we propose a novel H8 robust control integrated with µ-synthesis, explicitly handling uncertainties in suspension parameters (sprung/unsprung mass, stiffness, damping, tire stiffness). Mathematical modeling and MATLAB/Simulink simulations demonstrate significant improvements: a 54% reduction in peak vertical body acceleration (3.95 m/s2 to 1.816 m/s2) and a 35% decrease in suspension deflection (0.078 m to 0.020 m) compared to passive systems. Frequency-domain analysis shows a 92.42% reduction in resonance peaks at 10 rad/s, with over 30% energy savings. Time-domain simulations confirm stability under transient disturbances, with actuator forces constrained to ±1.3 kN. The integration of µ-synthesis with H8 control efficiently manages parametric variations and unmodeled dynamics. Comparative evaluations highlight the approach’s superiority over passive and conventional active systems, offering promising applications for autonomous and electric vehicles. This work lays the groundwork for future research on adaptive, energy-efficient suspension systems.]]></description>
      <pubDate>Tue, 30 Jun 2026 09:45:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701313</guid>
    </item>
    <item>
      <title>Study on Vehicle Driving Stability under the Coupling of Ramp Circular Curve Radius and Pavement Wetness State</title>
      <link>https://trid.trb.org/View/2720230</link>
      <description><![CDATA[To clarify the coupled effects of ramp circular curve radius and pavement wetness state on vehicle driving stability, 26 ramp models with circular curve radii ranging from 30 to 280 m were constructed using Carsim software, and pavement friction coefficients were set as 0.85 (dry), 0.5 (wet), and 0.2 (rainfall) to simulate different wetness states. Lateral offset distance, lateral acceleration, and yaw rate were selected as key evaluation indicators to analyze vehicle dynamic response characteristics, and critical speed calculation models under different limit states were fitted. Two quantitative evaluation indicators, safety speed margin percentage (SSMP) and comfort speed margin percentage (CSMP), were proposed to characterize speed redundancy, and accident-prone zones of ramps were identified. Finally, the driving safety of four typical ramps at the Kunming Northwest Ring Expressway Hub Interchange was comprehensively evaluated. The results show that the pavement friction coefficient is the core external factor determining the ramp safe speed; when the friction coefficient decreases from 0.85 to 0.5 and 0.2, the allowable maximum speed (AMS) decreases by an average of 22% and 50%, respectively. Small-radius ramps (R < 100 m) and low friction coefficients (µ = 0.2) are dual risk factors, leading to severe vehicle yaw motion and increased skid/rollover risks. The main accident-prone zones are the transition sections from transition curves to circular curves, with narrower speed tolerance ranges on rainy days. For the four typical ramps, under wet condition (µ = 0.5), each has a certain safety speed margin, but under heavy rain (µ = 0.2), the safety speed of small-radius ramps (A, B) is lower than the design speed. The proposed SSMP and CSMP indicators and research results provide a theoretical basis and engineering reference for interchange ramp linear design, differentiated speed limit setting, and operational safety management.]]></description>
      <pubDate>Tue, 30 Jun 2026 08:56:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2720230</guid>
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