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    <title>Transport Research International Documentation (TRID)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <title>Can you fly it? Flight performance of novices and system designers with a simplified vehicle operations concept</title>
      <link>https://trid.trb.org/View/2714418</link>
      <description><![CDATA[The concept of Simplified Vehicle Operations (SVO) is proposed to reduce input complexity and training time for future Advanced Air Mobility (AAM) pilots. So far, flight controllers and input concepts for SVO are often evaluated using computational simulations or in small-scale experiments with professional test pilots. This paper presents findings from a quantitative user study on the flight performance of n = 31 novices and n = 7 system designers in the execution of standardized Mission Task Element (MTEs) in a flight simulator. These MTEs include complex transition phases with a switch from rotary-wing to fixed-wing flight and vice versa. Absolute values from multiple subjective, performance, and input-based parameters indicate the general adequacy of the tested SVO concept, even for beginners. At the same time, multiple parameters also show significant differences between the two groups. The paper discusses these findings and SVO concepts in general to improve the future design of SVO concepts for minimally trained pilots.]]></description>
      <pubDate>Wed, 23 Sep 2026 15:56:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714418</guid>
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    <item>
      <title>Incorporating pilot mental stress into no-fly zone boundaries through a human factors approach to safe separation design in urban air mobility</title>
      <link>https://trid.trb.org/View/2718226</link>
      <description><![CDATA[The outer boundaries of the no-fly zones in urban air mobility (UAM) are defined through factors such as weather conditions, noise and navigation. This study aimed to include human factors into the spatial envelop design of no-fly zones in low-altitude airspace. A simulating experiment of electric vertical take-off and landing (eVTOL) flights based on four obstacle avoidance distances was conducted. Psychological, physiological and behavioral indicators were extracted to reflect stress levels and capture the distance showing the surge of stress. To calculate the individual overall stress from the three modalities of indicators, this study proposed a J-shape guided multi-feature fusion framework through extracting the properties of monotonic increasing and slope increasing from the J-shape relationship between stressors and stress to execute reliable individual-level fusion. The results showed that 65.91% of the participants showed stress surge on the 50-to-25-meter separation, while the 75-to-50-meter separation covered 86.36% participants. Robustness analysis tested the stability of the 75-meter separation under different fusion, modality, feature and weighting settings. Therefore, the 75-meter separation with corresponding time-to-collision (TTC) as 3.18 s was selected for an engineering design reference of human factors-driven safety separation. These conclusions bring a new human-centric design for safety assurance in UAM.]]></description>
      <pubDate>Wed, 23 Sep 2026 15:56:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2718226</guid>
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    <item>
      <title>Dynamic Optimization and Conflict Avoidance of Helicopter Air Navigation_paths in Low-altitude Air Space Opens: an Investigation</title>
      <link>https://trid.trb.org/View/2775916</link>
      <description><![CDATA[The safety and efficiency of helicopter operations have become an urgent concern due to the present state of lax low-altitude airspace. Route optimization and conflict avoidance is discussed in this paper, and it presents a comprehensive strategy consisting of topology search, nonlinear model predictive control, a reciprocal collision avoidance algorithm, and chance constraints. Under the use of the RRT algorithm, this strategy creates a comprehensive topological skeleton under complex obstacle conditions, which guarantees the connectivity of paths. The time domain regression smooths trajectories with NMPC to introduce dynamic and energy constraints directly into the optimization algorithm. The velocity space is reduced depending on the ORCA technology using chance constraints and the uncertainty of the wind fields to provide a probabilistic safety protection system in the case of multi-aircraft operation systems. An experimental framework is built based on the data set of TartanAviation (2024-2025) to confirm the viability of this method within the framework of actual ADS-B movements. Results of analysis indicate that the performance metrics of this approach are much better compared to those of its counterparts and ensures the maintenance of real-time operation rate of between ten and twenty Hz. With this hybrid approach, the autonomous flight properties of helicopters in low-level environments are greatly enhanced, which can be used to inform future urban air mobility developments.]]></description>
      <pubDate>Wed, 16 Sep 2026 16:15:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2775916</guid>
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    <item>
      <title>Relationships Between Pilots’ Startle and Surprise Responses and Information-Processing Performance During Simulated In-Flight Events</title>
      <link>https://trid.trb.org/View/2714219</link>
      <description><![CDATA[Objective: We aim to investigate how pilots’ startle and surprise responses affect information-processing performance during simulated in-flight events. Background: Startle and surprise are distinct constructs, each with their own potential effects on pilot’s performance during unexpected in-flight events. Prior research suggests that startle may impair performance through stress-induced cognitive interference, whereas surprise may do so via cognitive demands associated with sensemaking. Thus, we hypothesized that both startle and surprise would negatively affect information-processing performance on a secondary auditory cognitive task. Method: Using a motion-based hexapod simulator and a twin-propeller aircraft model, 26 pilots each performed eight single-pilot flight scenarios, which were designed to elicit varying levels of startle and surprise responses. Linear mixed-effects models were employed to analyse the relationships between self-report startle and surprise with secondary task performance, while controlling for individual differences and differences between the scenarios. Results: The results revealed that higher startle was significantly associated with reduced information-processing speed. For surprise, no significant association was found. Conclusion: The findings suggest that, within the context of the tested scenarios, startle appeared to impose a more pronounced disruptive effect on pilots’ information-processing performance than surprise. Application: The study underscores the need for tailored interventions to enhance pilots’ resilience to startle and calls for further research on ecologically valid methods to induce surprise for research and training purposes.]]></description>
      <pubDate>Mon, 31 Aug 2026 10:38:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2714219</guid>
    </item>
    <item>
      <title>Decentralized Multi-Agent Motion Planning Using Cognitive Hierarchy and Gaussian Process Classification</title>
      <link>https://trid.trb.org/View/2685943</link>
      <description><![CDATA[In this paper, we present a motion planning algorithm designed to guide agents, termed as player agents, optimally through multi-agent 3D urban air environments. The method integrates a sampling-based path planner, model-free optimal control, and a cognitive hierarchy model to predict the motion of other agents. Each player constructs a path through the environment, which is dynamically re-planned as the obstacle space of the environment evolves based on its online observations and the observations of cooperating players. The cognitive hierarchy model predicts the behavior of each agent in the environment, while a Gaussian process classification method estimates an unknown agent's level of rationality in real-time by observing each agent's kinodynamic distance. Once another agent's motion planning strategy is inferred, the player agents construct a predicted obstacle space based on each agent's expected motion to avoid potential collisions. Each player then traverses its planned path using a Q-learning controller. We validate the effectiveness of the proposed method in numerical experiments of a 3D urban air environment containing four and ten agents. We demonstrate that this approach is effective for reducing distance traveled by agents to reach their goals, mitigating the risk of collisions, and preventing deadlocks.]]></description>
      <pubDate>Thu, 20 Aug 2026 09:55:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685943</guid>
    </item>
    <item>
      <title>The History of the International Powered Lift Conference: 40 Years of V/STOL Progress</title>
      <link>https://trid.trb.org/View/2761791</link>
      <description><![CDATA[This year, SAE International hosts the 2026 edition of the International Powered Lift Conference (IPLC), which focuses on the latest developments in vertical and/or short takeoff and landing (V/STOL) aircraft research, concepts and programs. IPLC is a joint technical meeting, held approximately biennially, co-sponsored by the American Institute of Aeronautics & Astronautics (AIAA), the Royal Aeronautical Society (RAeS), SAE International and the Vertical Flight Society (VFS). Because each technical society hosts the IPLC only once a decade, and because the event was originally begun in the 1980s, turnover of staff and volunteers with each of the organizations creates a lack of knowledge and historical context of the event. This paper provides a formal record of the history and legacy of the IPLC, as well as its role in highlighting the technical and programmatic progress of V/STOL over the ages.]]></description>
      <pubDate>Wed, 19 Aug 2026 16:02:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2761791</guid>
    </item>
    <item>
      <title>TIG*: Enhanced Tangent Intersection Guidance for Efficient 3D UAV Path Planning in Complex Environments</title>
      <link>https://trid.trb.org/View/2685825</link>
      <description><![CDATA[Navigating autonomous aerial vehicles (UAVs) efficiently and safely in complex 3D environments, especially those with unknown maps, remains a significant challenge for general autonomous applications. This paper introduces TIG*, an improved version of the Tangent Intersection Guidance algorithm designed to address this challenge by generating shorter and smoother paths with minimal computational time in environments with irregular shapes. TIG* operates by identifying obstacles and selecting optimal avoidance tangents using an optimized heuristic cost function. The evaluations in static environments show that TIG* outperforms static 3D-TG, PRM*, RRT*, and Informed RRT* across key metrics, including path length, smoothness, algorithm success, and computational time. In many cases, TIG* is capable of generating paths in less than 0.05 seconds, making it highly suitable for efficient pre-mission planning in diverse mission scenarios. Furthermore, for online scenarios, the proposed O-TIG* algorithm offers real-time adaptability, smoothly modifying paths in response to unforeseen obstacles. Comparative studies show that O-TIG* requires fewer path modifications, faster re-planning, and superior smoothness compared to dynamic 3D-TG, RH-RRT* and APF, even in dense clutter, which is crucial for UAV survivability and mission continuity in dense settings. TIG* represents a powerful and practical solution by integrating the geometric solution with optimized path calculation for next-generation UAV navigation, particularly for demanding and critical missions.]]></description>
      <pubDate>Thu, 06 Aug 2026 09:22:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685825</guid>
    </item>
    <item>
      <title>Visual Illusions in Aviation: Simulating the Black Hole Phenomenon</title>
      <link>https://trid.trb.org/View/2698326</link>
      <description><![CDATA[Objective: The aim was to evaluate the effectiveness of a Transport Canada Level 2 Instrument Proficiency Check Flight Training Device to elicit the disorientation caused by the black hole illusion. To evaluate the role of gender, we measured the relative susceptibility of men and women. Background: Spatial disorientation is a well-known causative factor in aviation mishaps. However, there is no simulation-based training protocol for visual illusions that cause spatial disorientation. Method: We simulated an approach-and-land scenario using an ALSIM simulator. Trainee pilots were instructed to maintain a 3° approach and land the aircraft under conditions with (nighttime) and without (daytime) the black hole illusion. We computed altitude errors by differencing the daytime and nighttime flight paths. Glideslope errors were calculated as deviations from the 3° approach. To assess the contribution of spatial abilities, participants completed a mental rotation test. Results: Most pilots showed a shallow final approach during night flight relative to day flights. The pilots who experienced the illusion had lower mental rotation scores than those who did not. Men had higher mental rotation scores, on average, than women, and showed less negative altitude and glideslope errors in the night relative to day conditions. These errors were not mitigated by flight experience. Conclusion: We reproduced the effects of the black hole illusion in a relatively low-cost aviation simulator. Gender and mental rotation skills were factors in black hole disorientation. Application: It is feasible to implement simulated visual illusion scenarios in aviation training. It is important to consider gender in designing and assessing flight scenarios.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2698326</guid>
    </item>
    <item>
      <title>Stall prediction and identification for civil aircraft based on a long short-term memory model</title>
      <link>https://trid.trb.org/View/2698270</link>
      <description><![CDATA[Stall is a major contributor to aircraft safety incidents. Most civil aircraft lack stall prediction, and existing warnings afford little reaction time, limiting pilots' ability to avert accidents. This paper proposes a deep learning-based stall identification approach. We first analyse flight-performance parameters for a representative civil aircraft and define identification methods of incipient stall. We then conduct cruise-phase stall simulations across 28 operating points for the same type and build a long short-term memory (LSTM) model to forecast the resulting time-series signals. Finally, we train and evaluate the model under varied train/test strategies and compare alternatives. Results show the proposed LSTM reliably anticipates stall and supports timely recovery guidance. The framework demonstrates that data-driven sequence modelling can extend crew reaction time and improve safety, offering a practical path toward onboard stall prediction systems for civil aviation. Performance remains robust under realistic noise and sensor latencies.]]></description>
      <pubDate>Wed, 29 Jul 2026 09:16:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2698270</guid>
    </item>
    <item>
      <title>Active Perception and Safe Planning for Quadrotor Navigation in Unknown Environments</title>
      <link>https://trid.trb.org/View/2727843</link>
      <description><![CDATA[This paper is concerned with the quadrotor navigation problem by proposing an integrated framework for active perception and safe planning, enabling quadrotors to navigate in unknown environments while autonomously avoiding areas with higher obstacle density during the planning process to generate collision-free trajectories. The active perception component leverages the quadrotor's onboard sensors to collect environmental data and dynamically adjusts its heading and path. By integrating real time sensor feedback with an active perception path planning algorithm, it maximizes the visibility and sensing coverage of regions of interest, enhancing the perception of key environmental features. Concurrently, a risk-aware safe flight corridor (SFC) is generated by constructing convex polyhedron around accessible areas using environmental data, with the corridors dynamically adapted based on obstacle density and proximity. This framework combines the optimization of model predictive control (MPC) to ensure that the planned trajectory is stable and dynamically feasible, adhering to the quadrotor dynamics. The motion of yaw angle is also planned in this framework to improve the quadrotor's perception efficiency and path optimization quality. Simulation results demonstrate the system's ability to navigate in unknown environments efficiently while maintaining a high safety margin and adaptability to different scenarios.]]></description>
      <pubDate>Mon, 27 Jul 2026 11:16:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727843</guid>
    </item>
    <item>
      <title>Revisiting the Boeing YC-14 and Ball-Bartoe Jetwing USB Powered-Lift Aircraft: Lessons Learned</title>
      <link>https://trid.trb.org/View/2724698</link>
      <description><![CDATA[This paper will revisit an area of Short Take-Off and Landing (STOL) operations and powered-lift aircraft design that has been limited in scope, and at best, very specialized when it comes to research, aircraft built, and experimentation: The Upper Surface Blowing (or USB) aircraft configuration.Five aircraft have been flown successfully using the Upper Surface Blowing powered-lift concept: The Boeing YC-14, the Ball-Bartoe Jetwing, the Antonov An-72, the NASA QSRA experimental aircraft, and the National Aerospace Laboratory (NAL) Aska or Quiet STOL Research aircraft. Only the Antonov An-72 (and its commercial follow-on, the An-74) reached any significant degree of production. This fact illustrates the uniqueness of the USB technology as applied to powered-lift.A background of the technology will be given, what connects them as far as the USB configuration, discuss the main lessons learned, and briefly dwell on other configurations that are close relatives of aircraft using the USB as a source of powered-lift. An extensive review of the existing literature has been fundamental for the development of this paper since many years have passed since the last USB configured aircraft design has flown (the last new USB design to take to the air did so in 1985).Although all the unclassified USB projects that have been constructed and flown will be mentioned in this paper (production and experimental), the main thrust of the paper will be the Boeing YC-14 prototypes and the Ball-Bartoe Jetwing. With respect to NASA’s QSRA demonstrator, the Antonov An-72 series, and the NAL Aska demonstrator, references will be listed for those readers wishing to review the technology and advances made by those aircraft. Their detailed review is beyond the scope of this paper; but the contributions of these aircraft to the state-of-the-art of USB powered-lift configuration is well established.]]></description>
      <pubDate>Tue, 21 Jul 2026 11:44:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2724698</guid>
    </item>
    <item>
      <title>Research on Calculation Methods for Climb Performance of Civil Aircraft</title>
      <link>https://trid.trb.org/View/2732305</link>
      <description><![CDATA[The climb gradient along the takeoff trajectory at each point during takeoff reflects the aircraft’s ability to clear obstacles and reach a safe altitude, ensuring the safety of civil flights. Airworthiness regulations specify certain requirements for the single-engine-out climb gradient. Given that the data used in conventional calculation methods are significantly influenced by the flight status during the process, this paper explores two new climb performance calculation methods based on the existing ones. A set of data was calculated, and the resulting errors were all no more than 10%, indicating that both new calculation methods are effective and reliable. Therefore, they provide a certain reference value for the climb gradient calculation of transport category aircraft.]]></description>
      <pubDate>Tue, 21 Jul 2026 11:33:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2732305</guid>
    </item>
    <item>
      <title>Load Analysis of Flap and Slat Actuators in Aircraft High-Lift Systems</title>
      <link>https://trid.trb.org/View/2732272</link>
      <description><![CDATA[This study develops an end-to-end load analysis scheme for flap and slat actuators, which comprise the aircraft’s high-lift system, and the analysis results are directly integrated into hardware optimization. Because they shoulder heavy responsibilities during the takeoff and landing phases, whether they can remain rock-solid under complex aerodynamic conditions or even remain unmoved in emergencies is directly related to their overall safety performance. This work process is closely linked and includes three major links. First of all, according to the CCAR-25.301 standard, the load envelope under normal working conditions is sorted out, and the limit cases of abnormal faults are exhausted. Subsequently, ANSYS Workbench pulled silk and peeled off the cocoons to capture the peak stress at the engagement between the output shaft and the gear. In the end, the closed-loop verification of the customized test bench made the theoretical calculations and the hardware-measured data exactly the same. The entire package provides designers with hardcore data support, and always uses airworthiness, not convenience, as the criterion when improving actuator performance.]]></description>
      <pubDate>Tue, 21 Jul 2026 11:33:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2732272</guid>
    </item>
    <item>
      <title>Pilot Workload Identification during Engine Failure Landings</title>
      <link>https://trid.trb.org/View/2691511</link>
      <description><![CDATA[Pilot workload is a critical factor affecting flight safety, particularly in emergency situations such as engine failure during forced landings. This study aims to assess pilot workload during engine failure-induced forced landings compared to normal landings using EEG signals. EEG data were recorded from 21 pilots using a flight simulator and EEG acquisition equipment during both forced and normal landings. Subjective workload scores were obtained using a subjective workload scale. EEG features were extracted, and nonparametric tests were applied to assess the significance of these features at different workload levels. Subsequently, machine learning algorithms (SVC, KNN, RF and LightGBM) were employed to develop models for workload evaluation. The LightGBM model achieved a peak accuracy of 99.5% using the top 80% of all features (time-domain, frequency-domain and nonlinear features) as inputs. This study provides an effective quantitative approach for assessing pilot workload during emergency situations and offers valuable insights for improving flight safety and optimising pilot training programs.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:45:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691511</guid>
    </item>
    <item>
      <title>Data-Driven Air Traffic Management: Forecasting Demand, Modeling Delay Propagation, and Demand Capacity Balancing</title>
      <link>https://trid.trb.org/View/2712161</link>
      <description><![CDATA[Air Traffic Management (ATM) must be familiar with the exact Aircraft Take-off Weights (ATOWs) of airplanes to make the most use of runways, maintain safety margins high, and keep utilization and resources in balance. This paper aims to present a dependable ATOW forecasting methodology that can assist the air transport industry in enhancing operational decision-making. This research used datasets acquired from the EUROCONTROL Performance Review Commission (PRC) 2024 Aircraft Take-Off Weight Estimation dataset featuring 527,000 flights over Europe containing aircraft details, air trips and flight conditions. Technique comprises structured data input, inspection of missing data, timestamp aggregation to identify demand cycles over time, and domain-specific feature engineering using distance_per_minute, block_minutes, taxiout_ratio, and a strong wake turbulence metric The two supervised learning models used were Linear Regression (LR) for understanding and XGBoost for performance prediction In comparison to LR's 4,409 kg MAE (mean absolute error), 7,061 kg RMSE (root mean square error), and 0.9825 R2 value, XGBoost significantly excelled with validation results showing an R2 value of 0.9992 and an RMSE of 1,514 kg In the absence of labelled test targets, cross-validation nevertheless showed a constant degree of generalizability The residual diagnostics showed that the model was reliable for practical execution with low-variance deviations that were unbiased An accurate ATOW estimate improves the demand-capacity balance and On-Time Performance (OTP) in ATM, which in turn affects the runway schedule, wake turbulence diversion, slot allocation, and fuel planning The results highlight the need to include ATOW predictions in both tactical and strategic planning to reduce delays, increase airspace usage, and promote sustainable aviation operation and possesses significant improvements will consist of weather and runway conditions, stochastic ambiguity computation, and drift monitoring to keep up with ever-changing operating variables while maintaining accurate forecasts.]]></description>
      <pubDate>Tue, 23 Jun 2026 10:38:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712161</guid>
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