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    <title>Transport Research International Documentation (TRID)</title>
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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>International Standard for Electric Road System</title>
      <link>https://trid.trb.org/View/2581448</link>
      <description><![CDATA[This paper describes the international standard for the electric road system for the sustainable mobility and transportation for smart city and communities. The international standard is being created by ISO/TC268/SC2/WG2. The electric road system is particularly needed for long-haul transport battery powered electric vehicles. The framework, concept of operations (How roadside feeding electric road system can be configured and integrated in a sustainable mobility and transportation), and system components are explained.]]></description>
      <pubDate>Thu, 13 Aug 2026 17:00:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2581448</guid>
    </item>
    <item>
      <title>Analysis of Multi-Modal Energy Supply and Power Systems Adaptability for eVTOL and UAV Applications in the Low-Altitude Economy</title>
      <link>https://trid.trb.org/View/2736774</link>
      <description><![CDATA[The rapid growth of the low-altitude economy (LAE), driven by urban air mobility, aerial logistics, and emerging aviation services, underscores an urgent need for diversified and flexible energy supply solutions. The unique, highly dynamic energy demands and pronounced spatiotemporal load fluctuations of LAE applications also present unprecedented challenges to existing power systems. In response, this paper systematically explores the necessity and feasibility of multi-modal energy supply strategies to support large-scale and sustainable deployment of heterogeneous LAE aircraft--specifically electric vertical takeoff and landing vehicles and unmanned aerial vehicles--and analyzes their implications for power system adaptability. The study first characterizes the energy consumption profiles and load distribution patterns of key LAE scenarios, based on representative operational models, highlighting the distinctive spatiotemporal variability and stringent reliability requirements that set LAE aircraft loads apart from conventional urban and transportation loads. It then examines the core principles and implementation pathways of major multi-modal supply technologies, including wireless charging, fast wired charging, and battery swapping, highlighting their respective advantages and application contexts. Through simulation analysis of representative city clusters, the impacts of different supply modes on battery performance and lifespan, grid load, and LAE operational efficiency are evaluated, demonstrating how the multi-modal energy supply framework optimizes social, economic, and environmental benefits compared to single-mode strategies. Finally, the paper identifies the main barriers to large-scale deployment of LAE applications, discusses the prospects for emerging technologies, and offers targeted recommendations, providing a multidimensional theoretical and practical reference for building a future-oriented energy ecosystem for the low-altitude economy.]]></description>
      <pubDate>Wed, 12 Aug 2026 14:59:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2736774</guid>
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    <item>
      <title>Flexible future grid integration possibilities of electric vehicles: A review</title>
      <link>https://trid.trb.org/View/2735317</link>
      <description><![CDATA[Electric Vehicles (EVs) have become a key component of modern powertrains, driven by advances in power electronics, energy storage systems, and control technologies. As renewable energy sources (RES) penetrate the grid, EVs not only consume energy but also serve as mobile energy storage units, supporting grid operations through bidirectional power flow. However, large-scale EV integration has introduced unavoidable technical challenges for power systems, including grid instability, charging infrastructure constraints, and power quality issues. This paper presents a comprehensive review of EV integration possibilities in future power grids, focusing on various charging methods and the advantages and challenges of each approach. The paper also highlights bidirectional energy transfer mechanisms, including vehicle-to-grid (V2G), Vehicle-to-Home (V2H), and Vehicle-to-Building (V2B), and critically analyses their role in enhancing grid flexibility and reliability. The impact of EV penetration on grid performance, including voltage instability, harmonic distortion, and energy management, is also discussed. In addition, the challenges of EV integration and solutions such as control strategies, smart charging, and coordinated energy management are examined. This review focuses on common EV-grid interaction scenarios and does not consider region-specific grid differences or special application cases. Finally, future research directions are outlined to facilitate the seamless, efficient integration of EVs into next-generation power systems. This review serves as a valuable resource for understanding the complex dynamics involved in EV integration and contributes to the development of a reliable, efficient, and environmentally sustainable power grid.]]></description>
      <pubDate>Wed, 12 Aug 2026 14:59:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2735317</guid>
    </item>
    <item>
      <title>An Impedance Self-Adjustment Method Via Variable Inductors in Integrated LCC-LCC-Based IPT System for Efficiency Improvement Versus Air-Gap Variation</title>
      <link>https://trid.trb.org/View/2735100</link>
      <description><![CDATA[In an inductive power transfer (IPT) system, due to the presence of ferrite cores, changes in the air gap can alter the coil parameters (self-inductance and mutual inductance), leading to system detuning, resulting in efficiency degradation. To address this problem, an impedance self-adjustment method based on an integrated LCC-LCC topology with two variable inductors is proposed for IPT systems to enhance efficiency. Combined with the Second-Generation Nondominated Sorting Genetic Algorithm (NSGA-II) for system parameter design, the proposed method can mitigate secondary-side detuning and offer variable input impedance to realize wide-range zero-voltage switching (ZVS) of the inverter with phase-shifting (PS) control. The proposed method does not need additional components or complex controls. Experimental results show that with the air-gap variation from 30 to 60 mm (the self-inductance variation is 17.47%, and the mutual inductance variation is 80.91%) and the load variation of 50%, an accurate output is achieved with the PS control, and the system efficiency ranges from 92.6% to 94.23%. Compared with the traditional method, the maximum efficiency improvement is up to 16.92%.]]></description>
      <pubDate>Tue, 04 Aug 2026 09:34:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2735100</guid>
    </item>
    <item>
      <title>Optimizing Smart Wireless Charging and Data Acquisition for Uavs with Battery Life Prediction</title>
      <link>https://trid.trb.org/View/2731639</link>
      <description><![CDATA[As network technology advances rapidly, the use of unmanned aerial vehicles (UAVs) is rapidly growing across diverse applications, revealing unprecedented potential for widespread deployment. However, these UAVs often encounter the challenge of insufficient power during their missions. To overcome this problem, this study addresses mission interruption and energy wastage due to insufficient power by charging UAVs with a Charging UAV (CUAV). Traditional research in this area is mostly based on one key assumption: constant battery capacity. However, the battery capacity actually decreases gradually with the usage time, a fact that imposes constraints on the operational range and duration of UAVs. To address this issue, this paper proposes a wireless energy charging strategy for UAVs based on battery life prediction. The strategy first predicts the remaining lifetime of the UAV battery, and then based on this, a charging UAV is deployed to charge the UAV on mission to ensure that it can continue to fulfill its mission without having to return to the base station to recharge or replace the battery. This paper further explores a practical application scenario where multiple UAVs perform data collection from multiple sensor nodes, and these UAVs are charged by CUAVs. To achieve efficient task scheduling, this study proposes and implements a UAV scheduling algorithm based on Deep Reinforcement Learning (DRL). Through large-scale simulation evaluation, we demonstrate that the proposed scheme enables UAVs to explore and optimize the scheduling strategy more efficiently and exhibits significant advantages in system performance compared to traditional schemes when considering the battery life factor.]]></description>
      <pubDate>Fri, 31 Jul 2026 16:05:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2731639</guid>
    </item>
    <item>
      <title>DC Off-Board Vehicle to Grid/Building/Home: A Survey and Gap Analysis</title>
      <link>https://trid.trb.org/View/2685810</link>
      <description><![CDATA[In recent years, the research interest in bidirectional charging of electric vehicles has increased significantly, driven by improved accessibility to charging and payment information as well as the increasing emphasis on integrating variable renewable energy sources more effectively into the grid. Integrating bidirectional charging with the grid/building/home can also reduce grid congestion. Despite this, broader implementation of this technology has not yet been achieved. In this context, this article comprehensively surveys direct current (DC) off-board vehicle to grid/building/home chargers and analyses the gaps which prevent the technologies’ wide implementation. These gaps are analysed by considering areas such as the development direction of bidirectional charging technology, battery cost and its degradation, V2G applicable standards, grid codes and charging protocols, deployment of V2G chargers (off-board versus on-board/wireless), market feasibility of V2G services, and the cost of bidirectional off-board chargers. The first survey of twenty-five commercial bidirectional chargers is presented and investigated in relation to the above-mentioned areas. Four key (technical, regulatory, financial, and behavioural) barriers are identified and discussed for the wide implementation of vehicle to grid/building/home charging.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685810</guid>
    </item>
    <item>
      <title>Analysis, Design, and Demonstration for Rotation-Type Experimental System of Dynamic Wireless Power Transfer</title>
      <link>https://trid.trb.org/View/2685803</link>
      <description><![CDATA[Experiments on dynamic wireless power transfer (DWPT) for electric vehicles (EVs) typically require vast testing grounds and significant costs, making them difficult to implement. As a solution, experimental systems utilizing rotational motion for DWPT have been proposed. However, few such systems have been developed and their design methods and fundamental characteristics remain unclear. This paper presents the construction of a rotation-type experimental system for DWPT and discusses its design methodology and basic characteristics. In developing the prototype, mechanical stability was verified through simulations analyzing stress and critical rotational speed of the rotating components. A sector-shaped transmitter coil, suitable for this system, was designed and analyzed using electromagnetic field simulations, confirming similar characteristics to conventional linear-rail-based systems. Furthermore, the effects of misalignment between transmitter and receiver coils and the electrical characteristics of slip rings and brushes were evaluated. Finally, power transfer characteristics were validated through experiments at a linear velocity equivalent of 40 km/h and 3.3 kW power transfer.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685803</guid>
    </item>
    <item>
      <title>Efficient Far-Field Wireless Charging for Green Wireless Sensor Networks Using Multiple Uavs</title>
      <link>https://trid.trb.org/View/2730897</link>
      <description><![CDATA[Wireless sensor networks (WSNs) often face chronic energy supply issues, hindering their long-term continuous operations. To alleviate this issue, many existing works suggest using uncrewed aerial vehicles (UAVs) to wirelessly charge WSNs. However, most of these works rely on a single UAV for charging, which is impractical for a large-scale network due to the limited energy capacity of a single UAV. In this work, we propose leveraging multiple green energy powered UAVs to charge a large-scale WSN, aiming to extend its operational lifespan. We first develop energy models for UAVs, sensor nodes (SNs) and green base station (GBS), and then formulate an optimization problem to maximize the minimum residual energy level among all SNs, thus prolonging the WSN's lifespan. Given the NP-hard nature of this problem, we present a two-step solution to solve it. In Step One, we introduce the UAVs Charging Load Balancing (UCLB) algorithm to determine the minimum number of needed UAVs and balance their energy consumption. This algorithm enables each UAV to charge as many SNs as possible, thereby reducing the overall number of UAVs required. Once the minimum required number of UAVs is established, in Step Two, we propose the SNs Energy Balancing (SEB) algorithm to ensure that all the SNs have as much energy as possible, and nearly equal residual energy levels after wireless charging. Finally, extensive simulations demonstrate the effectiveness of our proposed solution in extending the lifespans of the SNs.]]></description>
      <pubDate>Thu, 30 Jul 2026 10:07:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2730897</guid>
    </item>
    <item>
      <title>Public perceptions of dynamic wireless power transfer technology: A case study of Greater Lafayette, Indiana</title>
      <link>https://trid.trb.org/View/2689815</link>
      <description><![CDATA[The widespread adoption of electric vehicles (EVs) faces three main challenges: purchase price, lack of charging infrastructure, and long charging time. Dynamic Wireless Power Transfer (DWPT) is a promising solution because it maintains the level of charge of the EV while in motion, potentially reducing battery size, vehicle cost, and charging inconvenience. This study investigates public perceptions of DWPT in Indiana, where the Indiana Department of Transportation is piloting the technology. It also provides policy recommendations to increase acceptance of DWPT technology, especially through public education and engagement. Using a mixed-methods approach and based on the Social Acceptability Framework, we analyzed data from a survey (n = 275) disseminated during the DWPT testbed construction in the Greater Lafayette area in Indiana. Our analyses identified three major thematic categories of interest to respondents: economics, health and the environment, and barriers to EV adoption. Our results suggest that some respondents thought the technology can improve the availability of EVs and expand charging infrastructure. Others looked forward to more affordable EVs through new government incentives or reduced battery sizes and costs enabled by DWPT. Respondents also raised questions about funding, emphasizing that infrastructure investments should benefit all the local population. Cost concerns were statistically related to party affiliation and EV ownership status. While respondents recognized the public health benefits of EVs, others expressed skepticism about DWPT’s environmental footprint, citing concerns over lifecycle emissions and construction-related impacts. This research enhances our understanding of local perspectives on DWPT and highlights the importance of public education and engagement. Our findings also inform outreach strategies to broaden support for roadway electrification.]]></description>
      <pubDate>Wed, 29 Jul 2026 16:55:51 GMT</pubDate>
      <guid>https://trid.trb.org/View/2689815</guid>
    </item>
    <item>
      <title>Design, Validation, and Field Testing of a Reconfigurable Holographic Metasurface-Enabled System for Magnetic Beamforming and Steering in Wireless Power Transfer for Electric Vehicles</title>
      <link>https://trid.trb.org/View/2730807</link>
      <description><![CDATA[Wireless Power Transfer (WPT) for electric vehicles (EVs) is a transformative technology that accelerates EV adoption and enhances charging convenience. However, existing wireless charging systems suffer from inefficiencies and require precise alignment between the transmitter (Tx) and receiver (Rx), leading to energy losses and extended charging times. To address this challenge, this paper proposes a reconfigurable WPT system utilizing a holographic metasurface for dynamic magnetic beamforming. The system comprises planar coil Tx and Rx, along with a metasurface consisting of 20 × 6 reconfigurable coil elements. By dynamically adjusting the surface impedance, the metasurface enables precise magnetic beam steering, significantly improving alignment tolerance. Designed for the 950 MHz WPT standard, our system achieves approximately ± 175 mm misalignment correction, as validated through experimental measurements on a commercial SUV, demonstrating a substantial enhancement in power transfer efficiency (PTE).]]></description>
      <pubDate>Tue, 28 Jul 2026 16:13:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2730807</guid>
    </item>
    <item>
      <title>Joint Trajectory and Resource Optimization for Ris-Uav Assisted Secure Swipt Systems</title>
      <link>https://trid.trb.org/View/2730713</link>
      <description><![CDATA[The Internet of Things (IoT) has been widely adopted across various industries, but the limited battery capacity of IoT devices and the security of their communications remain significant challenges. To address these issues, the integration of reconfigurable intelligent surface assisted uncrewed aerial vehicle (RIS-UAV) with simultaneous wireless information and power transfer (SWIPT) offers a promising solution, mitigating energy constraints while enhancing the security of communications. In this letter, we consider a RIS-UAV assisted secure SWIPT system, with the goal of maximizing the average secrecy rate. Owing to the difficulty of directly solving this problem, we break it down into four subproblems and solve them using methods such as the penalty-based semidefinite relaxation (SDR), successive convex approximation (SCA) and Lagrange duality method. Ultimately, we suggest an alternating iterative optimization algorithm to tackle the original problem. Simulation results indicate that our algorithm outperforms other benchmark schemes.]]></description>
      <pubDate>Mon, 27 Jul 2026 11:16:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2730713</guid>
    </item>
    <item>
      <title>Multi-Uav Enabled Integrated Sensing and Wireless Powered Communication: A Robust Multi-Objective Approach</title>
      <link>https://trid.trb.org/View/2727890</link>
      <description><![CDATA[The integration of sensing and communication functions is a fundamental paradigm for enabling robust and resource-efficient unmanned aerial vehicle (UAV)-assisted wireless networks. This paper addresses the optimization of integrated sensing and communication (ISAC) systems in UAV-aided wireless networks featuring wireless power transfer (WPT). We propose a novel architecture wherein multiple UAV-based radars concurrently serve multiple clusters of energy-limited communication users while performing sensing tasks. Initially, radars sense the environment, enabling users to harvest and store energy from radar transmissions. Subsequently, this stored energy facilitates uplink communication from nodes to UAVs. Our multi-objective design problem optimizes UAV trajectories, radar transmit waveforms, radar receive filters, time scheduling, and uplink powers to enhance both radar and communication system performance. Incorporating user location uncertainty, we formulate a robust non-convex optimization problem. To address this, we employ an alternating optimization approach, complemented by fractional programming, S-procedure, and majorization-minimization (MM) techniques. Numerical examples illustrate the efficacy of our method across diverse scenarios.]]></description>
      <pubDate>Mon, 27 Jul 2026 11:16:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727890</guid>
    </item>
    <item>
      <title>Mechanical performance of rigid pavement with embedded dynamic wireless power transfer technology: A simulation-based assessment</title>
      <link>https://trid.trb.org/View/2692510</link>
      <description><![CDATA[Embedding Dynamic Wireless Power Transfer (DWPT) technology into pavement structures enables in-motion wireless charging of electric vehicles, but introduces new mechanical interactions between the charging hardware and the host pavement. This study presents a simulation-based mechanical assessment of a full-scale rigid pavement section instrumented with an embedded DWPT unit, using a field-calibrated three-dimensional finite-element model, the first validated numerical investigation of its kind for a full-scale slab. Model calibration and validation employed slab strain records and falling-weight deflectometer (FWD) measurements collected from the test section, yielding close agreement between observed and simulated responses. The calibrated model was used to isolate the influence of interface bonding conditions on surface deflections, bottom-of-slab tensile strains, localized stress concentrations along the DWPT-concrete interface, and the resulting effects on predicted allowable fatigue repetitions. Under conditions of full bonding, the DWPT-integrated slab exhibited uniform load transfer and surface deformation patterns comparable to conventional rigid pavement. In contrast, partial or complete debonding generated pronounced stress concentrations at the interface, amplified bottom tensile strains by up to several times, and produced substantial reductions in allowable fatigue life. These mechanistic results indicate that interface adhesion is a principal control on the structural performance of DWPT-embedded pavements. We conclude by discussing implications for installation quality control, monitoring strategies, and maintenance protocols to preserve interface integrity and ensure long-term serviceability of embedded wireless charging systems.]]></description>
      <pubDate>Fri, 24 Jul 2026 08:40:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2692510</guid>
    </item>
    <item>
      <title>Dynamic Wireless Charging for Electric Vehicles</title>
      <link>https://trid.trb.org/View/2724733</link>
      <description><![CDATA[This paper investigates the electromagnetic and circuit-level performance of an inductive power transfer (IPT) system for dynamic wireless charging of electric vehicles (EVs). Key design parameters affecting power transfer efficiency (PTE) are examined through a simplified Series–Series (SS) compensated IPT model using a Double-D coil geometry with shielded ferrite backing, developed in MATLAB. The framework evaluates the effects of air gap, lateral misalignment, load resistance, and operating frequency on overall system efficiency. Results show that PTE is highly sensitive to spatial alignment, with significant efficiency losses at air gaps greater than 10 cm and misalignments beyond 15 cm. A combined 3D surface plot confirms the compounded nonlinear influence of both parameters. Load resistance analysis identifies an optimal range of approximately 10–15 O, while frequency analysis indicates peak performance near 85 kHz, consistent with standard guidelines. These findings validate trends reported in previous literature and highlight the importance of early-stage IPT system evaluation for dynamic wireless charging applications.]]></description>
      <pubDate>Tue, 21 Jul 2026 11:41:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/2724733</guid>
    </item>
    <item>
      <title>Towards continuous and on-time operation of electric shared autonomous vehicles with dynamic wireless charging</title>
      <link>https://trid.trb.org/View/2686715</link>
      <description><![CDATA[Dynamic wireless charging (DWC) technology is rapidly emerging as a promising solution to alleviate range anxiety in electric shared autonomous vehicles (SAVs). However, SAVs’ service quality depends not only on efficient charging but also on adherence to service time windows. Existing routing strategies for static charging typically treat charging and time-window scheduling as independent processes, failing to capture their spatiotemporal interdependence under dynamic charging scenarios. To address the SAV’s Pick-up, Delivery and Dynamic Charging Problem with Time Windows (SPDCP-TW), this study proposes a Spatio-Temporal Heterogeneous Deep Reinforcement Learning (STH-DRL) strategy that minimises route costs and stabilises battery state-of-charge levels while ensuring on-time service. Specifically, we introduce a Spatio-Temporal Heterogeneous Attention mechanism to explicitly encode time-window features and an adaptive multi-constraint masking mechanism to distinguish between early, on-time, and late arrival scenarios. A comprehensive simulation platform, incorporating real-world road networks, traffic flows, and taxis’ travel data, has been developed to evaluate multiple time-window-related metrics. Experimental results across three cities and multiple scales show that, compared with heuristic and state-of-the-art DRL methods, our proposed strategy consistently achieves superior performance in terms of total cost, on-time ratio, and battery state stability. Experiments across three cities and multiple operational scales demonstrate that our approach consistently outperforms heuristic and state-of-the-art DRL methods in terms of total cost, on-time ratio, and battery charging state stability. In 24-h continuous operation tests, the proposed strategy maintains on-time ratios of 90-99% while optimising charging schedules. Furthermore, analysis using real taxi datasets reveals that 9–29 continuously operating SAVs can replace 115 conventional taxis. Finally, sensitivity analysis provides practical insights for DWC deployment and battery capacity optimisation, showing that with 5.5% DWC road coverage, a 25-50 kW power range achieves a balanced trade-off, halving battery capacity, and significantly reducing route costs.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:31:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2686715</guid>
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