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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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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>Accelerating airport decarbonisation: Qualitative investigation of stakeholders’ perceptions and requirements towards hydrogen-powered ground support equipment</title>
      <link>https://trid.trb.org/View/2643049</link>
      <description><![CDATA[Hydrogen-powered ground support equipment (GSE) has the potential to reduce carbon emissions and accelerate airport decarbonisation, yet limited research has examined stakeholders’ perceptions of this emerging technology. To address this gap, this study conducted semi-structured interviews with key airport stakeholders, including airport operators, car manufacturers, hydrogen suppliers, and infrastructure providers, to explore their attitudes and operational needs regarding hydrogen-powered GSE. Following the thematic analysis, five core themes emerged: 1) Stakeholders viewed hydrogen-powered GSE as an ideal option for supporting airport decarbonisation, citing benefits such as zero emissions at point of use, low noise, fast refuelling, and long driving range. 2) Widespread adoption is constrained by high costs, limited refuelling infrastructure, and safety concerns and regulatory uncertainty. 3) Stakeholders felt limited refuelling infrastructure and vehicle range may initially impact staff experience with hydrogen GSE, but the long-term aim is a seamless operation. 4) Stakeholders saw the need for both technology-specific training and general hydrogen awareness training to ensure safety and build staff confidence. 5) Future investment should prioritise vehicles, hydrogen production, and infrastructure development. This study concludes that the adoption of hydrogen-powered GSE provides a strategic pathway for advancing sustainable air transport. Considering its successful deployment, it recommends collaboration among policymakers, airports, manufacturers, end-users, and academia is essential to improve understanding of hydrogen risks and guide safety standards.]]></description>
      <pubDate>Tue, 24 Feb 2026 09:01:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643049</guid>
    </item>
    <item>
      <title>Analysis of the timeliness of the aircraft ground handling process using the PERT method</title>
      <link>https://trid.trb.org/View/2627803</link>
      <description><![CDATA[The article presents issues related to analyzing the time of the aircraft ground handling process at the airport. The article aimed to perform a probabilistic assessment of the time of completion of the handling process using the PERT method. The analysis included observing 30 Airbus A321 aircraft, determining the process’s time parameters and identifying the critical path. The results obtained allowed for the estimation of the probability of the process implementation within the assumed time horizon. The results obtained in the work constitute the basis for assessing the risk of delays in implementing the aircraft ground handling process activities. They also constitute an element of support for the decision-making process in organizing the course of ground handling operations on the airport apron.]]></description>
      <pubDate>Tue, 27 Jan 2026 16:16:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2627803</guid>
    </item>
    <item>
      <title>Competitive advantage in the aviation in the context of resource dependence theory: The case of ground handling services</title>
      <link>https://trid.trb.org/View/2636276</link>
      <description><![CDATA[This study examines competitive advantage in the aviation sector within the context of resource dependency theory, specifically focusing on the ground handling services sector. The aim of the study is to identify the resources on which ground handling services companies depend within the context of resource dependency theory, to examine the competition experienced in the sector, and to determine the strategies used to achieve competitive advantage. The scope of the study consists of Group A ground handling companies operating in Türkiye. A qualitative research method was used in the study, and the data collected using semi-structured interviews were analyzed with the MAXQDA2020 program. The analysis revealed that the ground handling sector in Türkiye is costly and volatile, while competition in the sector is balanced and low. In ground handling companies, there is a greater reliance on outsources such as equipment, training, and workforce-human resource. The high cost of resources, regulatory compliance, frequent audits, and lack of alternative suppliers create a situation of forced dependency. Although competition within the sector is balanced and low, the competition between companies cannot be ignored. Ground handling companies generally provide services that are standardized by regulations and do not vary greatly, but they have advantages over their competitors in cargo-warehouse services and platinum services. In addition, ground handling companies have advantages in terms of sustainability, safety, and size. In this regard, ground handling companies implement collaboration-focused, quality-focused, cost-focused, and customer-focused strategies to gain a competitive advantage. Effective management of the procurement process for resources used in the ground handling services sector and dependency relationships related to resources provides companies with a competitive advantage. Companies manage dependency relationships by incorporating available resources into their own structures. However, due to the specialized areas of expertise, the necessity of the relationship, and the high costs involved, companies resort to outsourcing when necessary.]]></description>
      <pubDate>Mon, 05 Jan 2026 09:53:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2636276</guid>
    </item>
    <item>
      <title>Embracing AI automation to enhance customer experience, employee knowledge and build a smarter airport ecosystem</title>
      <link>https://trid.trb.org/View/2604245</link>
      <description><![CDATA[The aviation industry has long been a cornerstone of global connectivity and has been adapting over the years to meet rising demand. As technology progresses, artificial intelligence (AI) has emerged as a transformative power, reshaping the aviation landscape. This paper explores the significant role of AI and automation in the ground operations ecosystem and the new airport era of digitalisation. Smart airports are offering solutions that enhance operational efficiency, improve customer experiences and empower employees with advanced tools and knowledge. The paper also examines the implications of AI, addressing the challenges of adoption, including system compatibility, cost concerns and regulatory compliance. It highlights what stakeholders can expect from emerging innovations, including enhanced efficiency, transparency and safety. As aviation embraces technological advancements, a collaborative effort between operators, employees and technology providers is essential. By focusing on innovation with a clear vision, the industry is likely to achieve a future where efficiency and passenger satisfaction reach the highest levels. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.]]></description>
      <pubDate>Mon, 22 Dec 2025 17:03:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604245</guid>
    </item>
    <item>
      <title>Harnessing digital twin technology for enhanced aircraft turnaround efficiency</title>
      <link>https://trid.trb.org/View/2601477</link>
      <description><![CDATA[The aircraft turnaround operation is a critical component of air transportation, traditionally carried out using manually coordinated devices. Consequently, the operational efficiency is often constrained by the volume of labor and individual capabilities. To address this, some airports are exploring the potential of automated turnaround operations, where flights are serviced by newly designed smart devices. This study proposes a unique method for predicting the efficiency of automated turnaround operations using a digital-twin model. First, we designed a sandbox-based apron to simulate the physical environment, as no automated apron currently exists. Next, we applied network planning technique to establish coordinated operation rules among the smart devices, creating an optimized procedure for aircraft automated turnaround operation. Our results indicate that, compared to the statistical efficiency of manual-device coordinated operations, the time required for an automated turnaround operation for a single flight can be reduced by approximately 24.53 %.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2601477</guid>
    </item>
    <item>
      <title>Hourly Load Profile Dataset for Electric Airport Ground Support Equipment in the United States</title>
      <link>https://trid.trb.org/View/2589136</link>
      <description><![CDATA[Ground support equipment (GSE) plays an important role in airport operations, servicing aircraft between flights. This equipment is responsible for tasks such as refueling, towing, passenger transport, cargo handling, deicing, and firefighting. As of 2024, more than 80% of U.S. GSE fleets remain primarily powered by fossil fuels, with 25% exclusively reliant on them. Despite this, 65% of airports have adopted at least one piece of electric ground support equipment (eGSE), and nearly 70% plan to increase investment in eGSE in the future (Smith 2024). Electrifying GSE represents a near-term opportunity for reducing the environmental impact of airport operations (Greer, Rakas, and Horvath 2020). However, achieving this will require strategic investments in electric infrastructure to accommodate the increased electricity demand, emphasizing the need for proactive planning. Currently, there are limited data on the magnitude and timing of electricity demand from eGSE across U.S. airports. To address this gap, this study presents a modeling approach for an initial estimation of hourly annual electricity demand from eGSE at the 50 largest U.S. commercial airports (by total enplanements). These datasets, accessible at data.nrel.gov/submissions/279, provide critical insights into the potential grid impacts and electricity demand associated with eGSE adoption.]]></description>
      <pubDate>Mon, 08 Sep 2025 14:53:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2589136</guid>
    </item>
    <item>
      <title>A comprehensive review of ground support equipment scheduling for aircraft ground handling services</title>
      <link>https://trid.trb.org/View/2587303</link>
      <description><![CDATA[Aircraft ground handling (GH) services are critical to ensuring the efficient operation of airport systems, necessitating the optimization of ground support equipment (GSE) scheduling. This study investigates the characteristics of various GH services as well as their interdependent processes, and provides a comprehensive analysis of GSE scheduling methodologies. Existing models and algorithms designed for nine types of GSE are examined, including ferry, baggage, refueling, garbage, sewage, freshwater, catering, de-icing, and towing vehicles. Particular attention is given to their similarities and distinctive features in operation, shaped by the unique requirements of their respective services. Then, with the growing emphasis on the concept of airport collaborative decision-making, recent studies regarding multi-type GSE coordination are reviewed. Based on the analysis of the literature, this study identifies current research gaps and outlines directions for future research.]]></description>
      <pubDate>Tue, 02 Sep 2025 08:49:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2587303</guid>
    </item>
    <item>
      <title>Multi-agent task allocation and path planning for autonomous ground support equipment</title>
      <link>https://trid.trb.org/View/2577201</link>
      <description><![CDATA[The authors aim to contribute to the automation of ground handling tasks using autonomous ground support equipment (GSE) at airports. Automation of airside operations has recently become critical for the airports to achieve higher levels of safety and efficiency under growing traffic demand and requires solving a complex scheduling and path planning problem. To address this problem, the authors present a multi-agent task allocation and path planning model for handling airside operations on the apron. In the problem, the ground handling tasks are to be allocated to the equipment, the trips of vehicles should be scheduled within specific time windows considering the flight schedules, and the collisions of vehicles on the apron and service roads should be avoided. The authors present a centralized multi-agent task allocation and routing model which aims to optimize the allocation and routing of various types of ground handling tasks over a heterogeneous set of GSE vehicles. They convert the allocation and routing problem into vehicle routing problem with time windows, pick-ups, deliveries and solve the problem using a warm start mixed integer linear programming (MILP) model. The authors also introduce a nonlinear objective function which converts the MILP model into a mixed integer nonlinear programming (MINLP) model, to minimize the time service locations at the stands are occupied. Then, they solve the corresponding path finding problem to find collision free paths for the GSE, by the multi-agent path finding model. The proposed model outperforms the decentralized approach in previous research regarding the allocation rate of assigning tasks to vehicles and the performance indicators of finding conflict free paths, and in CPU time. The mean deviations from shortest paths were considerably small in path planning which means that the solution quality was high. Furthermore, the CPU time of allocating tasks has been reduced by 48% compared to the CPU time of decentralized allocation.]]></description>
      <pubDate>Thu, 21 Aug 2025 09:14:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2577201</guid>
    </item>
    <item>
      <title>Human Factors and Acceptance Framework for Airport Autonomous Systems</title>
      <link>https://trid.trb.org/View/2588332</link>
      <description><![CDATA[Airports worldwide are testing and adopting autonomous systems to enhance efficiency, safety, and operational capabilities. The Federal Aviation Administration (FAA) has recognized this trend with its February 2024 CertAlert 24-02 on “Autonomous Ground Vehicle Systems (AGVS) Technology on Airports,” noting that testing these systems “has recently become more prevalent, both domestically and internationally.” These technologies include autonomous ground vehicles for baggage transport, aircraft towing, and ground crew activities, which are transforming airport operations. However, despite these technological advances, considerations of human factors and user acceptance remain critically important, as they significantly impact overall system performance, safety, reliability, and successful implementation. 

While airports are implementing autonomous technologies, the frameworks are limited when addressing human factors and user acceptance during the integration of these systems into their airport ecosystem. Research is needed to develop a human factors and acceptance framework for airport autonomous systems, grounded in interdisciplinary principles of human–technology interaction, service design, safety science, security, and reliability.

 OBJECTIVE: The objective of this research is to develop a guide on human factors and acceptance framework that provides airport practitioners with strategies and resources to safely, securely, and reliably integrate autonomous systems into the airport ecosystem. ]]></description>
      <pubDate>Tue, 12 Aug 2025 10:16:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2588332</guid>
    </item>
    <item>
      <title>Towards solving the airport ground workforce dilemma: A literature review on hiring, scheduling, retention, and digitalization in the airport industry</title>
      <link>https://trid.trb.org/View/2548146</link>
      <description><![CDATA[The airport ground workforce is critical for a smooth operation of the entire aviation industry. This fact has been embarrassingly exposed during the recovery from the COVID-19 pandemic in Summer 2022, when various airlines and airports had to cut flights to reduce excessive delays, lost luggage, and other downstream effects, in absence of ground workforce sufficient to handle the rising travel demands. The authors' study discusses the challenges inherent to solving this airport ground workforce dilemma, partially caused and amplified by excessive layoffs during the peak of COVID-19. These industry challenges are dissected into four categories: Hiring new talents, workforce scheduling, staff retention, and digitalization. For each challenge, the authors review the existing literature on the subject and discuss potential avenues for solving the existing airport ground workforce dilemma. The review covers more than 100 papers from the highly scattered literature on the subject and, accordingly, the authors believe that their study may serve as a starting point for coordinated efforts by the scientific community to tackle this challenging problem.]]></description>
      <pubDate>Thu, 10 Jul 2025 16:38:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2548146</guid>
    </item>
    <item>
      <title>Electric Taxiing System. Kinetic Energy Recovery System as an Electric Taxiing Solution: Economic and environmental analysis</title>
      <link>https://trid.trb.org/View/2548125</link>
      <description><![CDATA[The aviation industry has thrived in recent years, with a significant increase in passenger numbers, leading to the development of larger aircraft fleets and the expansion of airport infrastructure. In 2019, more than 4.5 billion passengers traveled by airplane, which represents an 80% increase compared to 2009. As a consequence, this growth has also resulted in longer taxiing times for aircraft, increasing fuel consumption and operational costs. The industry's CO₂ emissions have quadrupled since the 1960s, with over 1 billion tons released in 2019, contributing to global warming. Given that the improvements being made to current propulsion systems and the production of over 600 million liters of SAF (Sustainable Aviation Fuel) in 2023 do not seem sufficient to meet the ambitious goals set by regulators and operators, the logical solution would be to develop a system capable of moving the aircraft on the ground using alternative, cleaner, and cheaper energies, such as electric power. This paper explores the latest advancements in electric propulsion systems, specifically focusing on external and onboard systems. After the state of the art is established, this paper will cover a case study and propose a new alternative for an onboard system called ETS – Electric Taxiing System. The ETS is a 100% electric system for ground handling operations designed to use only the kinetic energy stored in a battery pack, which is recovered during aircraft landing and braking events. Although there are some studies on this topic, the author considers this paper to be more comprehensive as the results computed here take into account 96 variables, 60 simulations, several flight plans, and real-world data. The case study focuses on the implementation and dimensioning of the ETS, considering electric motor power and torque, and battery capacity for the Embraer Phenom 300. A brief economic and environmental analysis was also conducted, considering the operation of NetJets Europe, the world's leading and largest private jet company.]]></description>
      <pubDate>Wed, 09 Jul 2025 13:59:32 GMT</pubDate>
      <guid>https://trid.trb.org/View/2548125</guid>
    </item>
    <item>
      <title>Research on Anti-Slip Traction Control for Aircraft Engine-off Towing System</title>
      <link>https://trid.trb.org/View/2539310</link>
      <description><![CDATA[When the aircraft towbarless towing vehicle (TLTV) drives on road surfaces that are wet, icy, oily, or covered with debris, as well as under conditions such as overloaded towing, uneven distribution of aircraft weight, sudden acceleration and sharp turns, brake system failures, or severe tire wear, it may slip due to a mismatch between traction force and ground adhesion. As a key piece of ground support equipment at airports, the anti-slip performance of TLTV is crucial for ensuring safe and efficient ground movement of aircraft. With continuous advancements in control technology, extensive research has been conducted on anti-slip control strategies for TLTV. This paper reviews relevant literature in the field of anti-slip control for TLTV in recent years, focusing on the current status of anti-slip control technology development, control strategies, and the application of co-simulation technology in anti-slip control. Based on co-simulation using Matlab and Adams software, this paper employs a fuzzy PI control algorithm to optimize the traditional PI control algorithm for dual closed-loop control and analysis of the rotational speed and current of the Permanent Magnet Synchronous Motor (PMSM) in the TLTV. The results indicate that the control algorithm is a primary factor affecting stability. A comparative analysis of stability data before and after optimization reveals that the optimized control system exhibits stronger anti-interference capability, thereby enhancing the stability of the TLTV system. The control strategy demonstrates significant effects in improving the anti-slip performance of TLTV. The use of Matlab and Adams co-simulation technology provides effective means for analyzing and verifying anti-slip control strategies. The future development trend of anti-slip control technology for TLTV will emphasize intelligence, precision, and integration to adapt to diverse airport operating environments and improve the safety and efficiency of traction operations.]]></description>
      <pubDate>Tue, 15 Apr 2025 13:56:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2539310</guid>
    </item>
    <item>
      <title>The Logistic Lasso and Ridge Regression Algorithm-Based Airline
          Passenger Satisfaction Prediction Model</title>
      <link>https://trid.trb.org/View/2533693</link>
      <description><![CDATA[Airline passenger satisfaction is important for airline operation service quality                     management. When airline companies carry out advertisement campaigns or plan a                     marketing strategy, the resources and budgets are not unlimited. Thus, an                     airline can only focus on improving a few factors that drive passenger                     satisfaction. To understand the key satisfies for the young and the old adults,                     respectively, we leverage five airline passenger satisfaction methods to                     identify the key factors that explain the airline service satisfaction of                     different passengers. In particular, we investigate and compare the ridge and                     the Lasso regularization in terms of the resulting model’s sparsity and                     computational efficiency. The top three important factors that influence the                     old’s satisfaction are departure and arrival time convenience, legroom service,                     and baggage handling. Our findings indicate that the young people place a higher                     value on entertainment, while the old adults place a higher value on usefulness                     and comfort. The Lasso is the most accurate model with the overall error of                     9.65% to predict the young passenger’s satisfaction, while the Best Subset with                     BIC with the overall error of 10% is the best mode for the old adults. It’s                     suggested that airline companies could use the Lasso model for predicting the                     airline satisfaction of the young people, and use the best subset with BIC for                     predicting the airline satisfaction of the old adults. The study findings would                     help the airlines improving their state-of-the-art operations to have                     outstanding service.]]></description>
      <pubDate>Thu, 03 Apr 2025 10:16:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2533693</guid>
    </item>
    <item>
      <title>From bricks to bytes: AI-based airport digital transformation in practice</title>
      <link>https://trid.trb.org/View/2470814</link>
      <description><![CDATA[Air travel is one of the most developed and advanced forms of transport, the success of which is reflected in a high level of innovation and the safety and comfort of passengers. In the context of long-term growth in air travel, constant cost and capacity pressures at airports and rapid advancements in innovative technologies, numerous opportunities arise. The greatest risk for any airport would be to neglect digital transformation. Technological improvements based on innovative, sustainably oriented technologies have significant potential. This paper discusses how to address current challenges at airports using evolving technologies and artificial intelligence (AI). It examines the dynamics of ground handling operations and highlights the transformative impact of technology and innovation. Unlike landside operations, many airside processes at most airports remain manual and inefficient. The paper introduces an advanced solution for monitoring aircraft ground handling, enabling proactive management of flight delays and resource shortages due to changes in flight schedules. This tool offers insights into potential efficiency gains by using a system of cameras and AI for the automatic recognition of the start and end of aircraft turnaround processes, without human intervention in the process itself.]]></description>
      <pubDate>Wed, 18 Dec 2024 15:57:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2470814</guid>
    </item>
    <item>
      <title>Light Airfield Management UAV Based on TurMass
     Technology</title>
      <link>https://trid.trb.org/View/2464296</link>
      <description><![CDATA[The advent of the low-altitude economy represents a novel economic paradigm that                     has emerged in recent years in response to technological advancement and an                     expanding social demand. The low-altitude economy is currently undergoing a                     period of rapid development, which underscores the importance of ensuring the                     safety of airfield operations. To enhance operational efficiency, unmanned                     aerial vehicles (UAVs) can be utilized for the inspection of the surrounding                     area, runway inspection, environmental monitoring, and other tasks. This paper                     employs TurMass technology, the TurMass gateway is miniaturised as the                     communication module of FT24, and the TK8620 development board replaces the LoRa                     RF module in the ELRS receiver to achieve the communication transmission between                     the remote control and the receiver. Additionally, a TurMass chip is integrated                     into the UAV to transmit beacons, while an airfield management aerial vehicle is                     employed to receive nearby UAV data, thereby preventing collisions. A new ground                     test device was employed to mitigate the risks associated with the actual test.                     The article provides a comprehensive account of the underlying principles,                     system architecture, pivotal technologies, and prospective applications of the                     aerial vehicle.]]></description>
      <pubDate>Wed, 27 Nov 2024 11:03:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2464296</guid>
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