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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>Non-Intrusive Fatigue Detection for Pilots</title>
      <link>https://trid.trb.org/View/2712086</link>
      <description><![CDATA[Pilot fatigue represents a critical concern in aviation safety, as it can significantly impair cognitive functions, decision-making abilities, and reaction times. In addition to decreasing performance, in-flight chronic fatigue has negative long-term health effects. Possible causes of fatigue include sleep loss, extended time awake, circadian phase irregularities and workload. Conventionally, the risk due to fatigue in aerospace is reduced by flight time limits and controlled rest requirements. Despite regulations limiting flight time and enabling optimal rostering, fatigue cannot be prevented completely. Hence, there is need to detect pilot fatigue in real time.There is ongoing research to detect pilot fatigue using devices that can capture Electroencephalogram (EEG) and Electrocardiogram (ECG). Though these devices have high fidelity, they are intrusive and can limit pilot activity. This limitation could potentially be overcome by non-intrusive devices such as a smart watch/wrist band/goggles which can measure physiological parameters that provide insights into pilot’s mental health. Heart rate variability (HRV) is one such physiological marker of interest for detecting pilot fatigue in real time. HRV can be effectively derived by processing raw Photoplethysmography (PPG) signals to gain insights into the autonomic nervous system, enabling the assessment of physiological state. Wearable devices such as a wristwatch are used in the current study to measure PPG data. Time and frequency domain analysis were performed to evaluate the potential of HRV indices. The analysis of R-R intervals and the Low Frequency / High Frequency (LF/HF) ratio plots, derived from HRV signals, revealed distinct characteristics that differentiate between an alert and a fatigued pilot. This study demonstrates a reliable non-intrusive method for detecting pilot fatigue and enhancing flight safety.]]></description>
      <pubDate>Wed, 10 Jun 2026 13:18:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712086</guid>
    </item>
    <item>
      <title>Research on Automotive Vibration Comfort Based on Psychological
          Indicators</title>
      <link>https://trid.trb.org/View/2614445</link>
      <description><![CDATA[In recent years, the vibration comfort of automobiles has become a key                     consideration for consumers when purchasing vehicles. This study introduces                     human electrocardiogram (ECG) signals and blood pressure, and proposes a comfort                     prediction model based on physiological indicators. The research steps include:                     obtaining riding indicators and subjective feelings on flat and bumpy roads, and                     analyzing the differences in heart rate variability indicators and blood                     pressure under different road conditions through paired sample tests; playing                     different sound signals on bumpy roads, and using repeated measures analysis of                     variance to explore their impacts on physiological indicators and subjective                     evaluations; conducting data validity tests on the subjective evaluation                     results, and constructing a comfort prediction model based on correlation                     analysis and support vector regression algorithm. The results show that there                     are significant differences in indicators such as the average RR interval and                     standard deviation of normal-to-normal intervals (SDNN) under different riding                     environments; music in the frequency band of 200Hz to 600Hz can significantly                     improve comfort, and the average relative error of the prediction model is                     8.209%. This study can provide data support for automobile manufacturers to                     optimize the design of suspension systems and seats. At the same time, by                     monitoring the physiological indicators of passengers, the vehicle system can                     adjust the sound signals in real time to alleviate the discomfort caused by                     bumps and enhance the driving experience.]]></description>
      <pubDate>Mon, 27 Oct 2025 17:04:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2614445</guid>
    </item>
    <item>
      <title>Objective and Subjective Evaluation of the Interaction of Automated Vehicles and Human Drivers in Take-Over Scenarios</title>
      <link>https://trid.trb.org/View/2539070</link>
      <description><![CDATA[The research activity aims at defining specific Operational Design Domains (ODDs) representative of Italian traffic environments. The paper focuses on the human-machine interaction in Automated Driving (AD), with a focus on take-over scenarios. The study, part of the European/Italian project “Interaction of Humans with Level 4 AVs in an Italian Environment - HL4IT”, describes suitable methods to investigate the effect of the Take-Over Request (TOR) on the human driver’s psychophysiological response. The DriSMI dynamic driving simulator at Politecnico di Milano has been used to analyse three different take-over situations. Participants are required to regain control of the vehicle, after a take-over request, and to navigate through a urban, suburban and highway scenario. The psychophysiological characterization of the drivers, through psychological questionnaires and physiological measures, allows for analyzing human factors in automated vehicles interactions and for contributing to advance AD technologies. Physiological signals, including electrocardiographic (ECG) and electroencephalographic (EEG) are acquired synchronously with eye-tracking and instrumented steering wheel signals throughout the entire test. The use of dynamic driving simulation enhances the study’s efficacy, facilitating early-stage development insights crucial for the advancement of AD technologies.]]></description>
      <pubDate>Tue, 15 Apr 2025 13:56:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2539070</guid>
    </item>
    <item>
      <title>Psychology-Driven and AI-Neuroscientific Methods for Investigating
     Low-Altitude Flight Service Acceptance</title>
      <link>https://trid.trb.org/View/2464322</link>
      <description><![CDATA[This study aims to explore the multifaceted influencing factors of market                     acceptance and consumer behavior of low-altitude flight services through online                     surveys and advanced neuroscientific methods (such as functional magnetic                     resonance imaging fMRI, electroencephalography EEG, functional near-infrared                     spectroscopy fNIRS) combined with artificial intelligence and video                     advertisement quantitative analysis. We conducted an in-depth study of the                     current trends in low-altitude flight vehicle development and customer                     acceptance of low-altitude services, focusing particularly on the survey methods                     used for market acceptance. To overcome the influence of strong opinion leaders                     in volunteer group experiments, we designed specialized surveys targeting                     broader online and social media groups. Utilizing specialized knowledge in                     aviation psychology, we designed a distinctive questionnaire and, within just 7                     days of its launch, gathered a significant number of valid responses. The data                     was then analyzed using AI to provide original, insightful data on the                     acceptance of low-altitude services. Furthermore, we addressed the limitations                     of traditional manual survey methods by designing an advanced system combining                     EEG and AI analysis to automatically generate surveys by measuring neural and                     physiological responses while subjects watched video advertisements for                     low-altitude services. Our research offers a comparison with existing online                     survey forms and proposes specific predictions to potentially improve the                     accuracy of online surveys.]]></description>
      <pubDate>Wed, 27 Nov 2024 11:03:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2464322</guid>
    </item>
    <item>
      <title>Modeling of Human Thermal Comfort</title>
      <link>https://trid.trb.org/View/2406682</link>
      <description><![CDATA[Current vehicle climate control systems are dramatically overpowered because they are designed to condition the cabin air mass in a specified period of time. A more effective and energy efficient objective is to directly achieve thermal comfort of the passengers. NREL is developing numerical and experimental tools to predict human thermal comfort in non-uniform transient thermal environments. These tools include a finite element model of human thermal physiology, a psychological model that predicts both local and global thermal comfort, and a high spatial resolution sweating thermal manikin for testing in actual vehicles.]]></description>
      <pubDate>Wed, 24 Jul 2024 16:12:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2406682</guid>
    </item>
    <item>
      <title>The ICE Model: Evaluating In-Cockpit Child-Centric Interaction
     Solutions</title>
      <link>https://trid.trb.org/View/2325758</link>
      <description><![CDATA[Effective smart cockpit interaction design can address the specific needs of                     children, offering ample entertainment and educational resources to enhance                     their on-board experience. Currently, substantial attention is focused on smart                     cockpit design to enrich the overall travel engagement for children. Recognizing                     the contrasts between children and adults in areas such as physical health,                     cognitive development, and emotional psychology, it becomes imperative to                     meticulously customize the design and optimization processes to cater explicitly                     to their individual requirements. However, a noticeable gap persists in both                     research methodologies and product offerings within this domain. This study                     employs user survey to delve into children’s on-board experiences and                     utilization of current child-centric in-cockpit interaction solutions (C-SI                     Solutions), that over 50% of the interviewees (children) got on-board at least                     several times per week and over half of the parents would pay for C-SI                     Solutions, but less than 8% of the interviewees reported actual usage. By                     employing an interdisciplinary approach that harmonizes Design Thinking and                     Developmental Psychology, this research reveals that the traditional cockpit is                     actually a liminal space for children, and introduces the ICE Model (Evaluation                     Model for In-Cockpit Child-Centric Interaction Solutions) for providing insights                     into C-SI solution design. This model is consisted of two modules: IPO-Based                     Structured Module and I&C (Intelligence & Consciousness) Evaluation                     Module. IPO-Based Structured Module is based on the IPO (Input-Process-Output)                     Model and for interpreting C-SI Solution’s structure, so that to realize the                     paradigm shift in Design Thinking. I&C Evaluation Module, the second one, is                     for analyzing C-SI Solution’s psychological developmental function. The ICE                     model is then applied to conduct market research, aiming to identify challenges                     and shortcomings with current C-SI Solutions. Subsequently, this research offers                     recommendations and possibilities for the improvement of designing C-SI                     Solutions, that it requires not only seamless cooperation between designers and                     engineers, but also interdisciplinary collaboration.]]></description>
      <pubDate>Mon, 22 Jan 2024 15:43:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2325758</guid>
    </item>
    <item>
      <title>Dynamics of Adopting Electric Vehicles in India: A Grounded Theory
                    Approach</title>
      <link>https://trid.trb.org/View/2218996</link>
      <description><![CDATA[
                
                Through connectivity with the electric grid, electric vehicles (EVs) minimize or
                    eliminate the need for fossil fuels. Despite the rapid adoption of EVs in recent
                    times, most government adoption objectives have not been attained. This article
                    aims to comprehend the reasons behind the limited uptake of electric scooters in
                    India and the driving aspects. This research used a grounded theory methodology.
                    Using a snowball sampling technique, we conducted 25 in-depth interviews with EV
                    owners, mainly based in Delhi and Mumbai. As an outcome of the study, four
                    drivers and four impediments to the adoption of EVs have been formulated. The
                    study shows that there are Financial, Technological, Operational, and
                    Psychological drivers and Technological/Infrastructural, Operational, and
                    Psychological impediments to the adoption. The study identifies the key concern
                    areas in the form of categories of drivers and impediments, which can be
                    considered in industrial and public policymaking. This research broadens our
                    understanding of India’s uptake of EVs and provides key insights to
                    organizations and policymakers regarding EV adoption in India.
            ]]></description>
      <pubDate>Mon, 24 Jul 2023 16:54:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2218996</guid>
    </item>
    <item>
      <title>Evaluation of Objective Sound Quality in Electric Drive System with
          Multi-power Levels and Full-Operational Conditions</title>
      <link>https://trid.trb.org/View/2060994</link>
      <description><![CDATA[In electric vehicles (EVs), the ear-piercing acoustic noise contributed by the                     electric drive systems (EDSs) has become a critical issue in sensitive                     situations. This paper provides a comprehensive sound quality evaluation                     associated with objective psychological parameters in EDSs with multi-power                     levels and full-operational conditions. The experimental test sets, prototype                     categories and acoustic samples are firstly proposed to reveal the sound                     pressure level distributions. Then, the objective psychological parameters are                     introduced and divided into six dimensions. The principal component analysis                     (PCA) method has been employed to achieve dimensionality reduction, in which the                     original six dimensions can be reduced to two dimensions. The calculated and                     evaluated results show that the loudness and sharpness are the main contributing                     components with a cumulative contribution of 99.93%. All results are sensitive                     to the operational conditions. The proposed work and the related results can be                     seen as guidance for comfort requirements, as well as NVH design, in EV                     applications.]]></description>
      <pubDate>Mon, 14 Nov 2022 16:36:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2060994</guid>
    </item>
    <item>
      <title>Estimation Parameters of Braking of Vehicles Category M1 at Definition of Circumstances Road Accidents</title>
      <link>https://trid.trb.org/View/2035278</link>
      <description><![CDATA[The study of the distribution of the deceleration of vehicles of category M1 when performing various maneuvers is intended to develop methods for assessing the parameters of maneuvering of cars in the study of the circumstances of the occurrence of road accidents. Experimental studies were carried out on passenger cars, which are equipped with automated braking force control systems, for various driving styles. M1 category vehicles were maneuvered on dry asphalt pavement in the range of speeds from 11 to 25 m / s, which is typical for most road traffic accidents. It was found that when braking a vehicle of category M1, longitudinal deceleration increase according to a second-order polynomial dependence in the range of deceleration variation from 1.39 to 5.86 m/s2. This fact is well explained by the peculiarities of the operation of automated brake force control systems that are equipped a vehicle and the psychological behavior of the driver, who carries out the process of braking the vehicle before the occurrence of the road traffic accident. It has been established that the vehicle deceleration may differ by 50-55% from the vehicle deceleration value obtained during its emergency braking in conditions not leading to a road traffic accident. The study showed that the presence in the design of a modern vehicle of category M1 of automated systems for regulating the braking force makes it possible to expand the range of its possible lateral displacements up to 65%, change the heading angle up to 82% and reduce the required longitudinal distance for maneuvering the vehicle by 25%, while maintaining stability vehicle movement.]]></description>
      <pubDate>Mon, 03 Oct 2022 17:04:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2035278</guid>
    </item>
    <item>
      <title>Assessing Low Frequency Flow Noise Based on an Experimentally Validated Modal Substructuring Strategy Featuring Non-Conforming Grids</title>
      <link>https://trid.trb.org/View/2004650</link>
      <description><![CDATA[The continuous encouragement of lightweight design in modern vehicles demands a reliable and efficient method to predict and ameliorate the interior acoustic comfort for passengers. Due to considerable psychological effects on stress and concentration, the low frequency contribution plays a vital rule regarding interior noise perception. Apart other contributors, low frequency noise can be induced by transient aerodynamic excitation and the related structural vibrations. Assessing this disturbance requires the reliable simulation of the complex multi-physical mechanisms involved, such as transient aerodynamics, structural dynamics and acoustics. The domain of structural dynamics is particularly sensitive regarding the modelling of attachments restraining the vibrational behaviour of incorporated membrane-like structures. In a later development stage, when prototypes are available, it is therefore desirable to replace or update purely numerical models with experimental data. To this end, an original strategy has therefore been developed to estimate the vibro-acoustic response due to aerodynamic excitation based on a modal coupling approach. The incorporated acoustic and structural modes can be obtained either from numerical models or through experimental modal analysis. The presented work begins with the principles of modal vibro-acoustic substructuring and the practical workflow employed. Its applicability is demonstrated by an experimentally validated automotive structure subject to transient aerodynamic load.]]></description>
      <pubDate>Wed, 10 Aug 2022 11:32:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2004650</guid>
    </item>
    <item>
      <title>Influence of Autonomous Vehicles on Short and Medium Distance Mode Choice for Intercity Travel</title>
      <link>https://trid.trb.org/View/1836612</link>
      <description><![CDATA[In order to study the influence of autonomous vehicles on short and medium distance mode choice for intercity travel, this paper incorporates the latent psychological variables that affect the choice behavior of autonomous vehicles into the latent class conditional logit model and establishes a hybrid choice model to conduct the empirical research based on the theory of planned behavior. The results show that compared with the traditional multinomial logit model, the latent class conditional logit model has higher fitting goodness. Travelers can be divided into three subgroups: class1, class2, and class 3, accounting for 40.7%, 24.4%, and 34.9%, respectively. At a 5% confidence level, gender, education, occupation, monthly household income, children, and IC card significantly affect the sample’s latent class. The value of in-vehicle time of class1 and class3 are 2.400 yuan/min and 2.169 yuan/min, which is slightly higher than the total in-vehicle time value of the sample (1.799 yuan/min); the access and egress and waiting time value of class1 is as low as 0.702 yuan/min, while the value of class3 is 8.607 yuan/min. Travelers from class 1 are more sensitive to the travel costs of autonomous vehicles and intercity buses than travelers from class 3 based on the elasticity analysis.]]></description>
      <pubDate>Thu, 09 Dec 2021 10:38:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1836612</guid>
    </item>
    <item>
      <title>Comparative Study of Olfactory Stimuli Influences on Hand-Eye Co-ordinated Tasks in Operators Fatigued by Circadian Effects</title>
      <link>https://trid.trb.org/View/1834102</link>
      <description><![CDATA[Several studies in the field of hedonics using subjective responses to gauge the nature and influence of odors have attempted to explain the complex psychological and chemical processes. Work on the effect of odors in alleviating driver fatigue is limited. The potential to improve road safety through non-pharmacological means such as stimulating odors is the impetus behind this paper. This is especially relevant in developing countries today with burgeoning economies such as India. Longer road trips by commercial transport vehicles with increasingly fatigued drivers and risk of accidents are being fuelled by distant producer - consumer connections. This work describes a two stage comparative study on the effects of different odors typically obtainable in India. The stages involve administration of odorants orthonsally and retronasally after the onset of circadian fatigue in test subjects. This is followed by a small cognitive exercise to evaluate hand-eye coordination. Instead of actual driving tests on public roads, this test safely and objectively gauges the effects of the odors on cognitive impairment due to circadian fatigue. In addition, details of precautions taken during the experiments to avoid pitfalls such as odor contamination by ambient atmosphere, olfactory desensitization, odorant conflicts etc. are also provided. The experimental findings and results shall present a picture of the relative effects of the various odors typically available in India on cognitive impairment due to operator fatigue and suggest future avenues of research.]]></description>
      <pubDate>Thu, 09 Dec 2021 10:38:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/1834102</guid>
    </item>
    <item>
      <title>An Improvement on Optimal Preview Acceleration Driver Model on Urgent Cornering</title>
      <link>https://trid.trb.org/View/1832173</link>
      <description><![CDATA[Driver model has been developed since 1950s and quite a lot of attention has been attracted on this aspect. Today there is a body of knowledge regarding driver mathematic model. Since driving behavior is highly complex, involving psychology and physiology factors, it is not easy to use a simple driver model to represent all characteristic features comprehensively, according to the utilization of driver model, some assumptions are necessarily proposed in order to tackle the specific problem easily.         Optimal Preview Acceleration Driver Model was put forward based on the Preview-Following Theory proposed by Prof. Guo in 1983. This driver model is quite simple and easy to understand, and accurate for great curvature path following. However, recent study has shown that more work is needed to improve the path following ability for sharp corner or urgent corner (higher frequency steering input). This paper will investigate and analyze the Optimal Preview Acceleration Driver Model in details, and propose an improvement based on this classical driver model to make it suitable for more specific conditions, especially for urgent cornering. Finally, the modified driver model will be verified to be more capable of realizing high frequency steering behavior than the previous driver model.]]></description>
      <pubDate>Thu, 09 Dec 2021 10:37:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1832173</guid>
    </item>
    <item>
      <title>Research on the Effect of Urban Road Traffic Soundscape on Drivers' Psychological Acoustics</title>
      <link>https://trid.trb.org/View/1829960</link>
      <description><![CDATA[Like outside scenery, the car interior noise and road condition will affect the driver's mental state when driving. In order to explore the influence of external visual and auditory factors on the driver's mood in the driving process based on research of traffic soundscape, this paper has selected four backbone roads of Tianjin city (China) to test and drive a gasoline passenger vehicle at different speeds. Near Acoustic Holographic was used to scan interior acoustic field distribution, while the tracking shot of the driver's location was recorded by a Sony camera. People with different characteristics were invited to watch the video and completed a self-designed survey questionnaire. The external factors affecting the driver's mood were explored by analyzing all these data. After the investigation, we found that the sound field distribution inside the car could be affected directly and significantly by the opening and closing the car window when driving; in the case of keeping the window closed, the acoustic characteristics of the car cabin was relatively stable; and the visual impact factor of the driver's mood is mainly related to the traffic congestion degree and the construction quality of road surface, whereas the road appearance and aesthetics, which people usually concern about have very little influence.]]></description>
      <pubDate>Thu, 09 Dec 2021 10:37:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/1829960</guid>
    </item>
    <item>
      <title>Dashboard Reachability and Usability Tests: A Cheap and Effective Method for Drivers' Comfort Rating</title>
      <link>https://trid.trb.org/View/1829955</link>
      <description><![CDATA[General comfort may be defined as the “level of well-being” perceived by humans in a working environment. The state-of-the-art about evaluation of comfort/discomfort shows the need for an objective method to evaluate the “effect in the internal body” and “perceived effects” in main systems of comfort perception.         In the early phases of automotive design, the seating and dashboard command can be virtually prototyped, and, using Digital Human Modeling (DHM) software, several kinds of interactions can me modeled to evaluate the ergonomics and comfort of designed solutions. Several studies demonstrated that DHM approaches are favorable in virtual reachability and usability tests as well as in macro-ergonomics evaluations, but they appear insufficient in terms of evaluating comfort. Comfort level is extremely difficult to detect and measure; in fact, it is affected by individual perceptions and always depends on the biomechanical, physiological, and psychological state of the tester during task execution. These parameters cannot be modeled using software and instead have to be tested on physical models.         A seating buck is often used to prototype a driver's seat, and virtual, mixed, and augmented reality devices help designers to improve ergonomics and comfort of a human-machine interface (HMI). In such environments, both postural and cognitive comfort can be evaluated, but often, testers' opinions are affected by devices, their interaction with designers, and especially, posture analysis systems. One solution to this kind of perception alteration can be found in non-invasive acquisition methods, such as acoustic, magnetic, or optical methods. Each has its own advantages and disadvantages, but all share the same characteristics: they are expensive and difficult to calibrate and use.         This paper presents a new method for objectifying and evaluating postural and cognitive comfort levels based on human posture analysis and a questionnaire to evaluate cognitive performance. The posture acquisition method employs commercial low-cost cameras on tripods. The comfort evaluation methods, previously developed at the University of Salerno, are based on several experimental test campaigns, statistical processing, and biomedical studies. The method was tested in terms of reachability and usability for automotive drivers and was performed in a B-segment car (FIAT Grande Punto).         A sensitivity analysis was performed to correlate the low resolution of the photographic acquisition with the consequent errors in the comfort evaluation. Posture acquisition errors were analyzed using DHM (DELMIA) software.]]></description>
      <pubDate>Thu, 09 Dec 2021 10:37:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/1829955</guid>
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