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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>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>Operationalizing social justice theory in transport resource allocation</title>
      <link>https://trid.trb.org/View/2652510</link>
      <description><![CDATA[Operationalizing social justice is challenged by the absence of a universal equity definition and inherent policy trade-offs. This study bridges theoretical social justice principles with operational decision-making by integrating four commonly discussed distributive justice theories—Utilitarianism, Rawls’ Egalitarianism, Prioritarianism, and Capabilitarian Sufficiency—into a bilevel bus frequency optimization model. It introduces linearized equity-oriented formulations to reflect the distinct distributive principles of these theories and proposes justice theory-driven equity metrics to evaluate distributive impacts using different ethical criteria. Using cumulative opportunity as a unit of distribution, the proposed frameworks and metrics are applied to Canberra’s southern suburbs. The results demonstrate that the choice of justice framework is not a neutral modelling decision but a normative one, with each framework producing distinct redistributive patterns and community-level trade-offs. This highlights the importance of aligning equity frameworks with policy objectives and governance contexts, as these choices ultimately shape public perception, political feasibility, and the long-term societal goals of transport investment.]]></description>
      <pubDate>Mon, 26 Jan 2026 08:41:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2652510</guid>
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    <item>
      <title>Resource Management in LTE-U Systems: Past, Present, and Future</title>
      <link>https://trid.trb.org/View/1862950</link>
      <description><![CDATA[With the tremendous growth in mobile data traffic, wireless cellular networks are facing a rigorous challenge to increase network capacity. Despite that many advanced technologies are used, the shortage of spectrum resource is still the main bottleneck for capacity enhancement. To address the challenge, the cellular networks have been motivated to seek for more fruitful radio spectra. Amongst many others, the unlicensed 5 GHz spectrum is a promising candidate due to its low channel attenuation, large available bandwidth, and easy to utilize. Therefore, the innovative technology of long-term evolution (LTE) using the unlicensed spectrum, known as LTE-Unlicensed (LTE-U), has been widely investigated as a promising means to increase the data rate of cellular networks. The unique characteristics of the unlicensed spectrum bring new challenges to resource management in the LTE-U system. During the last few years, there have been a lot of resource management designs for the newly-born but vigorous LTE-U technologies. This paper provides a comprehensive overview of the state-of-the-art resource management scenarios in LTE-U systems, including single small cell base station (SBS), multiple SBSs, device-to-device (D2D) networks, vehicular networks, and unmanned aerial vehicle (UAV) systems. The future research issues of resource management in LTE-U for 5G are also outlined.]]></description>
      <pubDate>Mon, 30 Aug 2021 14:49:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/1862950</guid>
    </item>
    <item>
      <title>Machine Learning Enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios</title>
      <link>https://trid.trb.org/View/1862949</link>
      <description><![CDATA[The application of Machine Learning (ML) techniques to complex engineering problems has proved to be an attractive and efficient solution. ML has been successfully applied to several practical tasks like image recognition, automating industrial operations, etc. The promise of ML techniques in solving non-linear problems influenced this work which aims to apply known ML techniques and develop new ones for wireless spectrum sharing between Wi-Fi and LTE in the unlicensed spectrum. In this work, the authors focus on the LTE-Unlicensed (LTE-U) specification developed by the LTE-U Forum, which uses the duty-cycle approach for fair coexistence. The specification suggests reducing the duty cycle at the LTE-U base-station (BS) when the number of co-channel Wi-Fi basic service sets (BSSs) increases from one to two or more. However, without decoding the Wi-Fi packets, detecting the number of Wi-Fi BSSs operating on the channel in real-time is a challenging problem. In this work, the authors demonstrate a novel ML-based approach which solves this problem by using energy values observed during the LTE-U OFF duration. It is relatively straightforward to observe only the energy values during the LTE-U BS OFF time compared to decoding the entire Wi-Fi packet, which would require a full Wi-Fi receiver at the LTE-U base-station. The authors implement and validate the proposed ML-based approach by real-time experiments and demonstrate that there exist distinct patterns between the energy distributions between one and many Wi-Fi AP transmissions. The proposed ML-based approach results in a higher accuracy (close to 99% in all cases) as compared to the existing auto-correlation (AC) and energy detection (ED) approaches.]]></description>
      <pubDate>Fri, 27 Aug 2021 14:58:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/1862949</guid>
    </item>
    <item>
      <title>Spectrum for Connected Vehicles</title>
      <link>https://trid.trb.org/View/1867473</link>
      <description><![CDATA[Connected vehicles, which are likely to be an important component of smart cities, require spectrum. As of December 2019, the US Federal Communications Commission and the US Department of Transportation were pursuing opposing visions of a spectrum policy for connected vehicles. Through extensive simulation, this project will provide both agencies with objective analysis to make informed decisions about how much spectrum to allocate for DSRC and/or C-V2X, and how to channelize the spectrum.]]></description>
      <pubDate>Fri, 27 Aug 2021 14:58:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/1867473</guid>
    </item>
    <item>
      <title>Adequacy of DSRC in 5.9 GHz Band for GDOT's Connected Vehicle Infrastructure</title>
      <link>https://trid.trb.org/View/1861547</link>
      <description><![CDATA[Vehicle-to-everything (V2X) communications are expected to take a critical role in a variety of transportation safety applications in connected and autonomous vehicle environment. However, Dedicated Short-Range Communications (DSRC), one of the representative technologies implementing the V2X communications, is encountering challenges due to the re-allocation of the 5.9 GHz spectrum by the Federal Communications Commission (FCC). The state of Georgia is leading the nation in the deployment of connected vehicle infrastructure with thousands of infrastructure units connecting vehicles based on DSRC. This project aimed at measuring the impact of the spectrum re-allocation on the performance of the Georgia's connected vehicle infrastructure. The project's particular technical focuses were to (i) model the performance of a DSRC system and (ii) design a protocol to improve the DSRC performance, under the FCC's reform of the 5.9 GHz band.]]></description>
      <pubDate>Mon, 26 Jul 2021 15:48:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/1861547</guid>
    </item>
    <item>
      <title>FCC approves proposal to proceed with changes to 5.9 GHz band rule</title>
      <link>https://trid.trb.org/View/1682617</link>
      <description><![CDATA[]]></description>
      <pubDate>Tue, 04 Feb 2020 11:45:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/1682617</guid>
    </item>
    <item>
      <title>FCC considers taking away spectrum designated for transportation safety uses</title>
      <link>https://trid.trb.org/View/1677281</link>
      <description><![CDATA[]]></description>
      <pubDate>Tue, 07 Jan 2020 11:23:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/1677281</guid>
    </item>
    <item>
      <title>Autos may lose grip on radio frequency : FCC could open V2V spectrum to others</title>
      <link>https://trid.trb.org/View/1585731</link>
      <description><![CDATA[]]></description>
      <pubDate>Tue, 19 Feb 2019 15:12:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/1585731</guid>
    </item>
    <item>
      <title>FCC evaluates sharing of spectrum by connected vehicles, Wi-Fi services</title>
      <link>https://trid.trb.org/View/1584236</link>
      <description><![CDATA[]]></description>
      <pubDate>Thu, 14 Feb 2019 15:57:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/1584236</guid>
    </item>
    <item>
      <title>Spectrum real estate</title>
      <link>https://trid.trb.org/View/1507450</link>
      <description><![CDATA[]]></description>
      <pubDate>Mon, 02 Apr 2018 11:37:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/1507450</guid>
    </item>
    <item>
      <title>Proposed mandate of connected vehicle technology faces opposition from cable industry, other groups</title>
      <link>https://trid.trb.org/View/1473442</link>
      <description><![CDATA[]]></description>
      <pubDate>Wed, 05 Jul 2017 14:15:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/1473442</guid>
    </item>
    <item>
      <title>A Unified Power-Allocation Framework for Bidirectional Cognitive Radio Communication</title>
      <link>https://trid.trb.org/View/1465459</link>
      <description><![CDATA[In this paper, the authors consider the power-allocation problem in orthogonal frequency-division multiplexing (OFDM)-based bidirectional cognitive radio (CR) relay networks. A joint optimization under the amplify-and-forward (AF) relaying protocol is formulated to maximize the throughput of secondary users (SUs) via power loading over different subcarriers at the three (two transceivers and a relay) nodes. For compatibility with practical systems, separate power constraints are considered at each transmitting node. Furthermore, to provide high-level protection to primary users (PUs) in underlay CR transmission, per-subcarrier-based interference constraints are assumed. For tractability of the solution, the authors adopt a decomposition framework where the joint power optimization (JPO) is split into two subproblems. Later, each subproblem is solved by exploiting the convex optimization techniques. Moreover, a low-complexity suboptimal solution of the joint power allocation at all nodes is also proposed. Simulation results are presented to validate the effectiveness of the proposed schemes.]]></description>
      <pubDate>Thu, 11 May 2017 15:57:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/1465459</guid>
    </item>
    <item>
      <title>Toward Cooperation by Carrier Aggregation in Heterogeneous Networks: A Hierarchical Game Approach</title>
      <link>https://trid.trb.org/View/1455650</link>
      <description><![CDATA[This paper studies the resource-allocation problem for a heterogeneous network (HetNet) in which the spectrum owned by a macrocell operator (MCO) can be shared by both unlicensed users (UUs) and licensed users (LUs). The authors formulate a novel hierarchical game theoretic framework to jointly optimize the transmit powers and subband allocations of the UUs and the pricing strategies of the MCO. In the authors' framework, an overlapping coalition formation (OCF) game has been introduced to model the cooperative behaviors of the UUs. The authors then integrate this OCF game into a Stackelberg game-based hierarchical framework. The authors prove that the core of our proposed OCF game is nonempty and introduce an optimal subband-allocation scheme for UUs. A simple distributed algorithm is proposed for UUs to autonomously form an optimal coalition formation (CF) structure. The Stackelberg equilibrium (SE) of the proposed hierarchical game is derived, and its uniqueness and optimality are proved. A distributed joint optimization algorithm is also proposed to approach the SE of the game with limited information exchanges between the MCO and the UUs.]]></description>
      <pubDate>Tue, 21 Mar 2017 09:14:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/1455650</guid>
    </item>
    <item>
      <title>Scalable Transmission over Heterogeneous Networks: A Stochastic Geometry Analysis</title>
      <link>https://trid.trb.org/View/1455664</link>
      <description><![CDATA[This paper focuses on the transmission of layered source information, such as scalable video coding, over heterogeneous cellular networks. Scalable transmission enables dynamic adaption of source information to the condition of user equipment (UE) devices and, thus, is suitable for cellular networks in which the transmission link quality substantially varies over space and time. Two novel transmission schemes are proposed, namely, layered digital transmission and layered hybrid digital–analog (LHDA) transmission. Leveraging tools from stochastic geometry, a comprehensive analysis is conducted focusing on three key performance metrics: outage probability, high-definition probability, and average distortion. The results show that both proposed transmission schemes can provide a scalable video experience for UE devices. For LHDA transmission, the optimal power allocation between digital and analog transmissions is also analyzed. When the proportion of frequency resource allocated to the femtotier exceeds a certain threshold, LHDA transmission is preferable by enabling continuous quality scalability, thus avoiding the cliff effect.]]></description>
      <pubDate>Tue, 28 Feb 2017 16:20:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/1455664</guid>
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