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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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Wireless Interference and Regulatory Frameworks for Frequency Allocation in V2X Communication Systems</title>
      <link>https://trid.trb.org/View/2579222</link>
      <description><![CDATA[Intelligent Transportation Systems (ITS) and Vehicle-to-Everything (V2X) communication technologies are revolutionizing the transportation sector by enhancing traffic efficiency, safety, and overall user experience. However, the performance of these systems can be significantly hindered by various types of interference. This paper provides a comprehensive overview of the regulatory framework for frequency allocation in V2X communication, identifies the types of interference affecting these systems both co-channel and adjacent channel, and explores strategies for managing and mitigating such interference. It includes an overview of current frequency allocations in the USA, EU/United Kingdom, China, Australia, Japan, South Korea, and Singapore, and discusses the implications of interference on ITS/V2X. The findings underscore the need for robust regulatory frameworks to ensure the successful deployment and operation of ITS and V2X communication systems worldwide.]]></description>
      <pubDate>Tue, 31 Mar 2026 16:34:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579222</guid>
    </item>
    <item>
      <title>Strategies to Improve Reporting of Impaired and Distracted Driving in Motor Vehicle Crashes</title>
      <link>https://trid.trb.org/View/2683256</link>
      <description><![CDATA[This report provides procedures for determining the extent of misreporting impaired and distracted driving crashes, as well as methods to improve the reporting of impaired and distracted driving in motor vehicle crashes. Misreporting comprises a variety of issues, including underreporting, overreporting, errors in crash data recording, and misclassification. Guidance and methodologies developed as part of this research will help states and local jurisdictions identify the misreporting of impaired and distracted driving and improve crash data collection and analysis. This report will be of interest to state highway safety offices and other stakeholders concerned with improving the reporting of impaired and distracted driving in motor vehicle crashes.]]></description>
      <pubDate>Mon, 30 Mar 2026 11:10:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2683256</guid>
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    <item>
      <title>Dual-Control Inference Diffusion Model via Multi-Sensor High-Frequency Signal for Space Transportation Engine Anomaly Detection</title>
      <link>https://trid.trb.org/View/2561864</link>
      <description><![CDATA[Liquid Rocket Engine, as the key power device of the space transportation system, the anomaly detection of operation status is the key to its reliable operation. However, in the face of multi-sensor high-frequency monitoring signals under extreme operating conditions, limited by the ability of model data modeling, the existing methods, based on classification and reconstruction strategies, are difficult to further improve the anomaly localization precision. To address the challenges and overcome the limitations of existing methods, this paper proposes a Dual-control Inference Diffusion Model (DIDM), which reconstructs and inferences on specified sensor samples to achieve accurate anomaly detection. The reverse diffusion inference process is controlled by the channel condition and mask prior, combined with two loss functions for alternating training, which enables inference for samples from specified sensors at specific moments. We evaluate the model based on the static ignition test data of a certain type of LRE. The results show that DIDM outperforms the state-of-the-art methods in terms of detection accuracy, which demonstrates the effectiveness and superiority of DIDM. Furthermore, by combining the error distributions of the inference results, we can achieve a more accurate location of anomaly in the time and frequency domains, which could increase the efficiency of rocket launches and air and space transportation, and enhance the potential of the academic results for industrial applications.]]></description>
      <pubDate>Mon, 23 Mar 2026 17:14:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2561864</guid>
    </item>
    <item>
      <title>Review of Development Trends of Anomalous Driving Detection Technologies Providing Driving Support</title>
      <link>https://trid.trb.org/View/2674211</link>
      <description><![CDATA[In recent years, traffic accidents caused by drivers' operation errors or intentional dangerous driving have become a serious social problem in Japan. The development of Level 4 autonomous driving technology is progressing. However, many issues still need to be resolved. Thus, it needs to continue promoting preventive safety technology to prevent accidents. In this study, we clarify the development trends of anomalous driving detection technologies. Furthermore, based on the review results, we propose detection technology that will be helpful for traffic safety.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:21:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2674211</guid>
    </item>
    <item>
      <title>Evaluating the Resilience of Two-dimensional Genetic Algorithm-based Centralized Traffic Signal Control versus Maxpressure-based Decentralized Control When Operating with Input Error.</title>
      <link>https://trid.trb.org/View/2669844</link>
      <description><![CDATA[Investigations on impact of errors in traffic input data on the resilience of real time traffic signal control systems are scarce. The present paper investigates the impact of underestimating vehicular volumes and queue length on performance of a real time decentralized as well as a centralized traffic signal control system. The decentralized system applies Maxpressure algorithm to determine control plans. The centralized system relies on a link model to predict traffic flow, integrates a rolling horizon framework, and uses a two-dimensional genetic algorithm to obtain optimal phase plans, green times, and offsets. Findings from the study highlight advantages of using centralized over decentralized control, integration of predictive model and rolling horizon framework while designing optimal controls, as well as the necessity of early interventions to avoid spillback conditions. These observations are beneficial to traffic engineers, urban planners and researchers invested in designing and implementing real time traffic signal control systems.]]></description>
      <pubDate>Mon, 23 Mar 2026 15:21:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/2669844</guid>
    </item>
    <item>
      <title>Independent versus collaborative double-checking for errors on a simulated rail control task</title>
      <link>https://trid.trb.org/View/2643948</link>
      <description><![CDATA[Double-checking is a safety practice performed by workers across high-risk industries.We aimed to examine the effectiveness of two types of double-checking (independent versus collaborative) for the detection of errors. We also examined the effect of two classes of checking tasks (matching versus critical analysis and assimilation) and interruptions on error detection. A total of 198 participants completed a 32-min rail control simulation. The primary objective for participants was to identify misrouted trains. Participants worked in pairs and performed tasks that involved matching versus critical analysis and assimilation, with interruptions occurring during the tasks. Independent double-checking was associated with greater response accuracy for identifying misrouted trains compared with collaborative double-checking. Response accuracy was also greater when participants engaged in matching compared to critical analysis and assimilation. Interruptions were not associated with task performance. Our findings suggest that independent double-checking may be superior to collaborative double-checking for the detection of errors.]]></description>
      <pubDate>Wed, 04 Mar 2026 09:16:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2643948</guid>
    </item>
    <item>
      <title>Error Consideration for Geocoding Police Reported Collision Data in California</title>
      <link>https://trid.trb.org/View/2635335</link>
      <description><![CDATA[Geographic Information Systems (GIS) are frequently used to analyze collision data. In order to utilize GIS, the data must be geocoded, or assigned a latitude and longitude coordinate by translating a descriptive location onto street network data. However, the ability for accurate spatial analysis can be limited by geocoding errors that may occur due to limitations in data collection technologies, incorrect data entry due to human error, or inaccurate street reference data. In the state of California there is an increased opportunity for data entry errors, given the long sequence of events and resulting paper trail that is required prior to finalizing each collision record. Data entry errors can occur during the initial traffic collision report completion, statewide database entry, state highway reference location input, or during a separate process to geocode fatal collisions. These data entry errors are incorporated into any geocoding process and frequently cause geocoding errors; but even in the absence of data entry errors, discrepancies in street network data can also result in geocoding inaccuracies. The objective of this paper is to summarize the sources of geocoding errors that occur before and after collision data are compiled into the California state database and the federal database of fatal collisions. Consideration is also given to the potential errors that can arise from the use of Global Positioning System coordinates as an alternative to geocoding. Finally, the impact of geocoding errors on traffic safety analysis is discussed in the context of specific applications currently available in California.]]></description>
      <pubDate>Sat, 28 Feb 2026 17:17:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2635335</guid>
    </item>
    <item>
      <title>Enhanced adaptability of UWB/INS for unmanned surface vehicles in GPS-denied environments: Ranging error identification and compensation</title>
      <link>https://trid.trb.org/View/2633971</link>
      <description><![CDATA[The navigation performance of global positioning system (GPS) and inertial navigation systems (INS) integrated navigation systems is severely degraded under bridges or in harbors, greatly affecting the navigation safety of unmanned surface vehicles (USVs). Ultra-wideband (UWB) ranging technology is a competitive alternative to GPS. However, it is significantly affected by non-line-of-sight (NLOS), limited diffraction line-of-sight (LD-LOS), and signal interruption errors. Therefore, this paper mainly designs a positioning estimation based on the model and an event-triggered mechanism to identify and compensate for ranging errors of the UWB to improve navigation accuracy in GPS-denied environments. First, the USV models are used to estimate the current position. The distance between the estimated position and the UWB base stations is a reference for calculating ranging errors. An event-triggered mechanism is introduced, and an error threshold is set as the trigger signal. Outliers are compensated, and their associated trust weights are adjusted. Finally, the confidence weights provided by the event-triggered mechanism are utilized in the extended Kalman filter (EKF). The advantages of the proposed algorithm over EKF and UWB are experimentally verified, and the positioning errors are reduced by 42.6 % and 69.2 %, respectively.]]></description>
      <pubDate>Mon, 23 Feb 2026 11:24:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633971</guid>
    </item>
    <item>
      <title>Efficient Estimation of Deep Learning-Based Vehicle Detection Error Distribution Leveraging Polynomial Chaos Expansion</title>
      <link>https://trid.trb.org/View/2613009</link>
      <description><![CDATA[Three-dimensional (3D) object detection is a fundamental and important technology in many applications, such as autonomous driving. Despite the emergence of many works focusing on 3D object detection, the detection error distributions from a complex deep neural network model are not investigated. To address this issue, we propose a vehicle detection error (VDE) model to efficiently approximate the 3D object detection error distribution using the polynomial chaos expansion (PCE). Moreover, a constrained VDE (CVDE) model is also proposed to improve the approximation performance by imposing constraints on the mean and variance of the estimated distributions. Experiments on the KITTI data set indicate that the proposed model can accurately estimate the 3D object detection error distribution by solely using dozens of samples and significantly outperform the naive sampling method. Considering the complexity in error distribution estimation, the proposed method presents potential to be used in robust perception applications and efficient collaborative perception.]]></description>
      <pubDate>Fri, 20 Feb 2026 15:28:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613009</guid>
    </item>
    <item>
      <title>An evaluation approach of the communication error risk of a metro operation team based on the cloud model</title>
      <link>https://trid.trb.org/View/2630546</link>
      <description><![CDATA[Problems in aspects including team structure, team members’ collaboration, personality differences and language application ability can potentially give rise to communication failures of the entire team and systemic risks. Scant studies have focused on the distinctive risk factors of communication errors and the methods for quantifying these risks. For Zhengzhou metro, critical event technology is employed to construct the factors influencing the risk of communication error of the metro operation team, i.e., interpersonal risk, language application risk and external risk. The analytic hierarchy process (AHP) is utilized to assign weights to each index, and the cloud model is adopted to evaluate the risk of communication error quantitatively. The results indicate that the risks were in the order of interpersonal > external > language application, and the main contributing factors are the risks of information management (U13), global awareness (U14), parallel task processing (U32) and time pressure (U34).]]></description>
      <pubDate>Fri, 09 Jan 2026 16:58:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2630546</guid>
    </item>
    <item>
      <title>MPF: A Multi-Noise Perception Framework to Enhance Online Map Matching Algorithms</title>
      <link>https://trid.trb.org/View/2553317</link>
      <description><![CDATA[Map matching is crucial to facilitating location-based services, and recent advancements in map matching have demonstrated excellent performance with high-quality data. However, the use of low-precision devices often introduces high measurement noise, and the slow update rate of maps may result in errors in digital maps. Consequently, multiple types of noise significantly impact the performance of map matching algorithms. To tackle this issue, this paper presents a novel multi-noise perception framework, named MPF, aiming to enhance the performance and robustness of existing map matching algorithms. The main challenge lies in detecting anomalies during map matching, identifying the root causes, and devising appropriate solutions. Firstly, we propose a matching quality assessment (MQA) method that assesses abnormal variance in matching probability. Secondly, we introduce a multiple noise discrimination (MND) mechanism to effectively differentiate between measurement noise and map errors. Thirdly, we present a missing segment generation (MSG) scheme that dynamically fills in map gaps to prevent significant detours. To validate the effectiveness of MPF, we conduct experiments using real-world taxi trajectories from four cities, covering a total distance of 79,670.6 km. MPF is compare with seven online map matching algorithms and is used to optimize their performance. The experiments show that MPF outperforms the top baselines by 15.6%-26.9% and enhances their performance by 18.7%-38.2%.]]></description>
      <pubDate>Mon, 22 Dec 2025 17:03:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2553317</guid>
    </item>
    <item>
      <title>A Current Measurement Error Compensation Strategy for SPMSM Based on an Improved ADALINE Filter</title>
      <link>https://trid.trb.org/View/2604064</link>
      <description><![CDATA[This article proposes an improved adaptive linear neuron (ADALINE) filter with phase compensation for surface-mounted permanent magnet synchronous motor (SPMSM) to suppress the speed pulsation, dq-axis current ripple, and phase current imbalance caused by current measurement error, while still achieving excellent dynamic motor performance. First, the structure of ADALINE is enhanced to enable simultaneous compensation for the first- and second-order pulsating components, as well as the dc residual error of the d-axis current. Then, to solve the problem of mutual coupling between the external load periodic disturbance and the current measurement error disturbance, the orthogonal relationship between the dq-axis current measurement error is used to indirectly obtain the q-axis current compensation value. Afterward, the impact of introducing ADALINE on system stability is analyzed. Drawing on the idea of phase compensation in a resonant controller, a phase shift unit is innovatively introduced into the conventional ADALINE to improve the system vector margin, and the selection criteria for the learning rate and compensation phase angle are given. Finally, the experimental results show that the proposed method can achieve accurate compensation of current measurement error with a small computational burden, regardless of the presence of periodic load disturbances. The generalization of compensation parameters was verified on another SPMSM with different electrical and mechanical characteristics, and the cross-platform robustness of this method was verified.]]></description>
      <pubDate>Fri, 19 Dec 2025 10:18:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604064</guid>
    </item>
    <item>
      <title>Trust Dynamics in Driving Automation: The Effects of Driver Expectations and Error Consistency</title>
      <link>https://trid.trb.org/View/2633007</link>
      <description><![CDATA[The advancement of driving automation systems is transforming surface transportation. Understanding how drivers develop trust in these systems is crucial for their effective implementation. This study investigated the influence of drivers’ initial expectations and the consistency in system errors on trust in a Level-3 automated driving system (ADS). Participants read descriptions that characterized system capabilities to be either high or low, following which their initial levels of expectation were assessed. Error patterns (no, consistent, inconsistent errors) were manipulated across three simulated drives. Subjective trust ratings after each drive and reaction time to takeover requests (TORs) were measured. Results showed that initial expectations did not significantly impact overall trust or TOR performance; instead, trust was adjusted based on the system’s actual performance. These suggested a greater influence of direct experience over drivers’ preconceived expectations. The perceived predictability of the system partially mediated the effect of error consistency on trust, with inconsistent errors worsening TOR performance. The study highlighted the need for predictable ADS designs and driver-system interactions to enhance trust and road safety.]]></description>
      <pubDate>Wed, 03 Dec 2025 09:19:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2633007</guid>
    </item>
    <item>
      <title>A Framework for Refining Error Metrics in Surrogate Models for Engineering Applications</title>
      <link>https://trid.trb.org/View/2604474</link>
      <description><![CDATA[Model-Based Systems Engineering (MBSE) is a growing field in engineering design, enabling rapid prototyping and deployment of concepts. However, the quality of engineering simulations depends heavily on the quality of the models used. As a result, quantifying and reducing model error is critical in MBSE. To do this effectively, examining how model error is measured is crucial. Error metrics reduce the complex relationship between predicted and measured behavior to a single scalar value. This compression can introduce bias, but it is necessary for error quantification and surrogate generation. This paper examines the impact of this compression on model behavior and offers a decision framework for choosing error metrics. While not all uncertainty is reducible, modelers should decide which uncertainties are acceptable and how they are measured.]]></description>
      <pubDate>Tue, 02 Dec 2025 09:25:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604474</guid>
    </item>
    <item>
      <title>Pixels, Chisels and Contours - Technical variations in European road traffic noise exposure maps</title>
      <link>https://trid.trb.org/View/2547810</link>
      <description><![CDATA[Motorized traffic often causes road noise directly in front of our homes and windows. Yet long-term exposure to noise impact life’s quality and can potentially cause negative effects on human health. Furthermore, social and behavioral effects have been measured. To protect people’s health and well-being from such noise, the European Noise Directive (END, 2002/49/EC) obliges countries to produce strategic noise maps every five years for large agglomerations and along major roads, which are then used for noise action planning. Besides that, the official noise maps are a valuable data source for environmental exposure analyses. However, the END has some limitations. The definition of urban agglomerations is vague, different input parameterizations lead to data inconsistencies across administrative units, undefined post processing methods introduce geometric artifacts, and topological errors incompliant to the common Simple Features Implementation Specification hinder working with the published geodata. The aim of this article is to provide practical insights for end-users and stipulate for concise regulations. Moreover, we highlight that these variations limit the comparability of maps in environmental impact assessments. We compile 84 separate noise assessments in Germany reported according to the END to review shape and structure of the geographic data. Graphical representations are used to show in particular how vertices are connected to polygons in noise contour maps and that these geometric alterations effect the eventual statistics on exposed population shares. We aggregate spatial metrics to assess the reported data’s spatial properties in an automatic manner, e.g. when receiving data in future mapping rounds. Along with our quality assessment, a nation-wide dataset on road traffic noise was produced. Depicting the yearly averaged noise level indicator Lden, which integrates exposure at day, evening and night, for 2017, it serves as common ground for environmental health analyses. The examination of different raster to polygon conversion implementations is fundamental to other geodata managers outside the domain of noise mapping, as well.]]></description>
      <pubDate>Fri, 21 Nov 2025 08:44:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2547810</guid>
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