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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>
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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>The URBANE Innovation Transferability Platform: Learnings for Decarbonising Last-Mile Delivery Networks</title>
      <link>https://trid.trb.org/View/2579471</link>
      <description><![CDATA[Logistics plays a crucial role in modern society, particularly in densely populated urban areas, facilitating the transportation of goods. Last-mile e-commerce deliveries are emissions-intensive, contributing significantly to CO2 levels and traffic congestion. Addressing this challenge requires systemic changes in last-mile delivery ecosystems. Based on this observation, in alignment with the EU decarbonisation goals, the URBANE project (GA101069782) aims to promote the adoption of sustainable and environmentally friendly last-mile delivery solutions by introducing a collaborative layered “Platform as a Service” (PaaS) paradigm. The initiative focuses on establishing Physical Internet (PI) inspired interventions combined with the implementation of innovative tools, such as agent-based and AI models, employing a Digital Twin platform addressing the operational and strategic planning challenges of city logistics networks. A multi-factorial impact assessment radar further enhances the evaluation of the PI interventions’ effectiveness. The platform fosters collaboration among urban logistics stakeholders governed through “green” smart contracts, addressing security and privacy concerns by using a blockchain infrastructure and digital IDs, creating a trustworthy system for collaboration. The paper showcases the applicability of the URBANE Innovation Transferability Platform in designing, measuring, testing, and validating targeted logistics interventions in Lighthouse Living Labs. Cities and logistic operators receive suggestions for informed data-driven decision-making coupled with integrated and transferable applications that can be standardised and structured, aligned with the targets set in a citie’s Sustainable Urban Logistics Plan (SULP).]]></description>
      <pubDate>Wed, 12 Aug 2026 17:07:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2579471</guid>
    </item>
    <item>
      <title>Bfrn-Iov: Blockchain and Fog-Enabled Route Navigation for Digital Twin-Based Internet of Vehicles</title>
      <link>https://trid.trb.org/View/2732109</link>
      <description><![CDATA[The rapid evolution of the Internet of Vehicles (IoV) necessitates secure, scalable, and low-latency route navigation mechanisms that can operate in highly dynamic vehicular environments. Emerging paradigms such as Vehicular Digital Twins (VDTs) further enhance IoV ecosystems by enabling real-time virtual representations of physical vehicles, facilitating predictive analytics, intelligent decision-making, and context-aware routing. However, conventional VANET-based approaches suffer from centralized trust dependencies, high computational overhead, and limited adaptability to real-time traffic conditions. This paper proposes BFRN-IoV, a blockchain- and fog-enabled route navigation framework that integrates lightweight ECC-HMAC-based mutual authentication, RSU-assisted fog routing, and global route validation via a Geo-Location Provider (GLP), while leveraging VDTs for enhanced situational awareness and dynamic route optimization. The framework ensures key security properties-including confidentiality, integrity, pseudonymity, unlinkability, and non-repudiation-using ECDH-derived session keys, HKDF-based key expansion, and HMAC verification, while preserving privacy through pseudonym-based identity management. A permissioned blockchain provides immutable and auditable logging of routing interactions without exposing vehicle identities. Simulation results using SUMO and implementation via Web3 demonstrate significant improvements in routing accuracy, along with reduced communication and computational overhead compared to existing approaches. Formal verification using the Scyther tool confirms robustness against replay, impersonation, and man-in-the-middle attacks. The proposed framework delivers a unified, secure, and efficient solution for real-time IoV route navigation, further strengthened by the integration of VDTs in next-generation intelligent transportation systems.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2732109</guid>
    </item>
    <item>
      <title>Reputation-Based Hyperledger Fabric for Private and Scalable Data Sharing in Cavs</title>
      <link>https://trid.trb.org/View/2732075</link>
      <description><![CDATA[The operation of Connected and Autonomous Vehicles (CAVs) is primarily driven by the continuous exchange of data from various sources, including in-vehicle sensors, neighbouring vehicles, and roadside infrastructure.This continuous data exchange results in the accumulation of large volumes of data with dimensionality, which is essential for accurate decision-making in autonomous driving functions. Shared data often encompasses highly sensitive data such as precise vehicular location, driver identification and behavioural patterns.As a result, there is an increasing public concern over the privacy implications associated with the extensive data exchanges. In this context, this research investigates access control mechanisms that ensure privacy and trust in CAVs. We propose a Reputation-based Hyperledger Fabric (RepHLF) framework, a novel privacy-preserving architecture that integrates across-channel Hyperledger Fabric blockchain with a dynamic, multi-metric reputation model for CAV environments. The reputation mechanism evaluates vehicles based on three parameters: behavioural integrity, legitimacy, and historical communication reliability. Each parameter evolves using exponential decay functions to reflect temporal relevance. Data access is subsequently restricted to trusted vehicles only, according to their computed reputation index. The performance of RepHLF is evaluated in terms of accuracy, latency, memory usage, privacy loss, and communication overhead using Hyperledger Caliper. Simulation results demonstrate ultra-low average latency of approximately 201 ms, minimal communication cost of 2.8 KB per transaction, Throughput of 4.99 TPS and high learning accuracy of 99.94%, while maintaining a bounded privacy loss of 3.12%. The integrated reputation mechanism within the consensus algorithm further enhances network reliability by dynamically identifying untrusted vehicles and restricting their transaction requests. Further analysis of the proposed model, RepHLF, against existing reputation-based models demonstrates superior dynamic trust evolution and robust privacy preservation.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2732075</guid>
    </item>
    <item>
      <title>Genai-Driven Quantum-Resilient Consensus Framework for Blockchain-Enabled Vehicular Digital Twins</title>
      <link>https://trid.trb.org/View/2732060</link>
      <description><![CDATA[Digital Twin (DT) technology is elevating the next-generation intelligent transportation systems industry to new heights, as it enables real-time monitoring, predictive maintenance, and adaptive control of connected and autonomous vehicles. However, the use of GenAI and DTs in interconnected vehicular technology ecosystems introduces new attack vectors, particularly from quantum computing, which can easily break classical encryption systems. This paper introduces Reputation-based Proof-of-Stake (R-PoS), a hybrid consensus mechanism tailored for lattice-based post-quantum cryptography (PQC) operations on vehicular edge devices. The core contribution is a lightweight hybrid consensus mechanism optimized for lattice-based PQC on edge devices, enabling secure and scalable synchronization between physical assets and their digital twins. Experimental results from a containerized IoT testbed using the Open Quantum Safe (OQS) library show that the proposed PQC-blockchain (PQC-BC) framework achieves an average throughput of 1178 transactions per second with latency of 0.78 second. These results affirm the framework’s efficacy in securing future interconnected vehicular environments and establishing a trust foundation for sustainable quantum-resistant digital twin applications.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2732060</guid>
    </item>
    <item>
      <title>Efficiency Optimization for Blockchain-Enabled V2v Energy Trading with Dynamic Clustering Based on Deep Reinforcement Learning</title>
      <link>https://trid.trb.org/View/2731839</link>
      <description><![CDATA[Vehicle-to-Vehicle (V2V) energy trading is a feasible solution to alleviate charging anxiety and enhance the range of electric vehicles (EVs). Clustering EVs can improve the efficiency of both energy transfer and V2V communication. However, in the complex large-scale Internet of Electric Vehicles (IoEV), the security and reliability of trading and communication, as well as the impact of cluster number and strategy on trading efficiency, require further discussion. This paper proposes a V2V energy trading system that leverages blockchain sharding and dynamic clustering to securely record energy trades as transactions on the blockchain. The system forms clusters using a clustering algorithm based on the mobility information and power levels of EVs, ensuring the reachability of energy trading. These trading clusters correspond to blockchain shards, enhancing transaction throughput through sharding scalability. Deep reinforcement learning (DRL) is employed to optimize the number of clusters, clustering algorithms, and parameters of the sharded blockchain system under security and latency constraints. The results demonstrate that the proposed scheme ensures timely power replenishment for low-power vehicles, improves overall economic utility and throughput for participants, and is effectively applicable to large-scale V2V energy trading scenarios.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:56 GMT</pubDate>
      <guid>https://trid.trb.org/View/2731839</guid>
    </item>
    <item>
      <title>A Privacy-Preserving Large-Scale Data Marketing System Based on Blockchain and Zero Knowledge Proof for Vanets</title>
      <link>https://trid.trb.org/View/2731858</link>
      <description><![CDATA[In the process of integrating the digital economy with the real economy, a vast and diverse supply of data has emerged. Among these, the exponential growth of data in vehicular ad-hoc networks (VANETs) hold immense commercial value. This further drives the demand for building large-scale data marketing platforms to support trading between vehicles and businesses in order to reduce the cost of local management. However, this must address several challenges related to security and performance, such as fairness, privacy protection, and data delivery efficiency. Therefore, this paper proposes a privacy-preserving large-scale data marketing system (PLDM), aiming to address these challenges. Specifically, this solution is based on blockchain to build a decentralized trusted third party to ensure the fairness of the trading process. In addition, we combine the S-protocol and Merkle tree to prove the validity of both the encryption of data to be traded and the identities of the trading participants. This not only achieves privacy protection for data and identities but also reduces the computational costs for vehicles. We provide the security analysis and experimental evaluation of PLDM. And the results show that PLDM performs well in fairness and privacy protection, supporting efficient delivery of large-scale data and low on-chain computational costs.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2731858</guid>
    </item>
    <item>
      <title>Enhancing Security in Parallel Federated Learning with Sharded Blockchain for Internet of Vehicles</title>
      <link>https://trid.trb.org/View/2731804</link>
      <description><![CDATA[The Internet of Vehicles (IoV) has experienced rapid growth, generating extensive data that can be leveraged for intelligentapplications. Federated learning provides a privacy-preserving approach to utilize this data but faces challenges in performing multi-task learning and ensuring security. To address these issues, we propose a secure Federated Learning framework with Sharded Blockchain (FLSB), where the blockchain design aligns with FL requirements to enhance security, robustness, and scalability. FLSB partitions the blockchain into sharded chains to support parallel FL tasks, while a main chain governs task management and security enforcement. To prevent malicious behaviors such as creating fake identities or disrupting consensus, we develop the Proof of List Update (PoLU) consensus on the main chain. For secure FL, we design a committee-based adaptive weighted aggregation algorithm, whcih dynamically adjusts the model weights during aggregation to defend against poisoning attacks. In addition, we introduce the Proof of Task Participation (PoTP) consensus on sharded chains to ensure trustworthy model aggregation and defend against adversarial manipulations. Experimental results on public datasets demonstrate that FLSB effectively balances FL task performance, security, and privacy, making it well-suited for IoV environments.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2731804</guid>
    </item>
    <item>
      <title>Secretcharge: A Blockchain-Based and Privacy-Preserving Scheme for Payment Information of Intelligent Connected Vehicles</title>
      <link>https://trid.trb.org/View/2731818</link>
      <description><![CDATA[In the development of urban transportation, Intelligent Connected Vehicle (ICV) technology has become a key force in promoting intelligence, sustainability, and efficiency. In particular, the rapid development of electric vehicles (EVs) has led to a growing demand for charging. However, this process risks exposing the private payment information of EV users, including the location of charging stations, the moment of charging, and users' identities. Our paper proposes a blockchain-based distributed privacy-preserving payment scheme named “SecretCharge”, designed to protect users' private information for ICV payment service scenarios. To meet the demands of large-scale applications of ICV, we propose an efficient group signature scheme based on the ElGamal signature, achieving high efficiency in key generation, signing, and verification algorithms. To conceal the payment information of EV users, we sign the data using our group signature scheme and use it as input for a zero-knowledge proof, ensuring that the information can be verified without being disclosed. To eliminate the dependence on third-party billing entities in traditional centralized schemes, we process system payments on the blockchain, achieving decentralization. Finally, our scheme is tested on Ethereum. The experimental results demonstrate our scheme's efficiency and usability, achieving privacy protection for user payment information in ICV.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2731818</guid>
    </item>
    <item>
      <title>A Transformer-Based Trust Management System for the Internet of Vehicles Using Blockchain Technology</title>
      <link>https://trid.trb.org/View/2731733</link>
      <description><![CDATA[In the Internet of Vehicles (IoV), the vehicular network serves as an open environment for information exchange, which makes it susceptible to internal attacks and leads to security concerns. Trust among vehicles plays a crucial role in addressing these challenges. However, previous approaches to trust management lack precision in evaluating vehicle trust, which limits their effectiveness in countering internal attacks within the vehicular network. To accurately assess the trust among vehicles, mitigate the spread of malicious messages, and prevent interference from malicious nodes within the vehicular network, this paper proposes TrustFormer, a trust management system based on Transformer. TrustFormer employs a transformer-based message detection model (TrMD) to detect each message in real time, converting it into a change in vehicle trust value. In addition, roadside units (RSUs) utilize blockchain technology to store the global trust values of vehicles, thereby ensuring their authenticity. Simulation results demonstrate that the proposed method outperforms existing approaches in terms of Precision, Recall, and F1-score against Bad Mouth Attack (BMA) and Zigzag Attack (ZA). Even with an increased number of malicious nodes in the network, the proposed method exhibits significant advantages, with less degradation in performance metrics compared to existing methods. Furthermore, blockchain performance simulation experiments indicate that the system latency meets the requirements of vehicular network applications, and throughput tests confirm its scalability.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2731733</guid>
    </item>
    <item>
      <title>Bakp: A Blockchain-Assisted Anonymous Authentication and Key Agreement Protocol for Secure Internet of Vehicle</title>
      <link>https://trid.trb.org/View/2731898</link>
      <description><![CDATA[Authentication in the Internet of Vehicles (IoV) is challenged by significant communication delays and risks of attacker intrusion, attributed to the high mobility of vehicles. Current authentication schemes often fail to fully address the reliability of Road Side Units (RSUs) and typically overlook issues related to single points of failure. Additionally, these schemes do not adequately consider secure and efficient handover authentication during vehicle access, leading to increased computational and communication costs. To overcome these limitations, we introduce BAKP, a blockchain-assisted anonymous authentication and key agreement protocol designed specifically for IoV contexts. BAKP enables secure access authentication for vehicles connecting to network services, even in scenarios where RSUs are semi-trusted. When the vehicles re-request network services, the RSUs bypass the authentication center and directly query the blockchain-recorded authentication results, thereby streamlining the handover process. The protocol also supports the revocation of pseudo-identities and enhances the transparency in tracing malicious entities. We performed a provable security analysis of BAKP using the Standard Model, along with formal security evaluations employing Colored Petri Nets (CPN) and the Dolev-Yao attacker model. Our results confirm that BAKP is robust against all relevant attacks and demonstrate its efficiency through comprehensive performance evaluations.]]></description>
      <pubDate>Wed, 12 Aug 2026 15:14:54 GMT</pubDate>
      <guid>https://trid.trb.org/View/2731898</guid>
    </item>
    <item>
      <title>A Blockchain-Based Privacy-Preserving Authentication Scheme for Secure Platoon Communications in VANET</title>
      <link>https://trid.trb.org/View/2685811</link>
      <description><![CDATA[While Vehicular Ad-hoc Networks (VANETs) can potentially improve driver safety and traffic management efficiency (e.g. through timely sharing of traffic status among vehicles), security and privacy are two ongoing issues that need to be addressed. This article proposes a novel blockchain-based authentication scheme leveraging conditional privacy within temporary platoons. The proposed model is an extended model based on Temporary Blockchain Platoons Formation. Our scheme utilizes blockchain technology to ensure data integrity and prevent unauthorized access, while enabling conditional privacy preservation where data sharing is limited based on pre-defined trust levels within the platoon. This significantly reduces reliance on Roadside Units (RSUs), leading to a cost-effective approach. Compared to traditional Public Key Infrastructure (PKI), our scheme offers improved security, enhanced privacy, and reduced infrastructure costs, promoting wider VANET implementation. The augmented model also incorporates an “Accident Prevention Mechanism,” a critical component absent in the preceding Platoon proposed model, thereby enhancing the overall safety and robustness of the system. Apart from the extra proposed features, rest features and mechanisms will be working as in already present Platoon Model.]]></description>
      <pubDate>Mon, 03 Aug 2026 09:10:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2685811</guid>
    </item>
    <item>
      <title>Manage on-Road Services with Chains: A Distributed Vehicular Task Offloading Approach Based on Blockchain Technology</title>
      <link>https://trid.trb.org/View/2730968</link>
      <description><![CDATA[In resource-constrained vehicular environments, offloading tasks to edge servers simultaneously from multiple client vehicles leads to severe resource competition, causing a cycle of increased latency. Designing a task offloading strategy that balances the latency of new offloaded tasks and those already being executed on edge servers is a crucial challenge. Additionally, centralized task offloading strategies based on global information require the design of complex communication mechanisms to collect task and computational workload information in real time, which is not desirable in vehicular environments due to the dynamic changes in the locations of client vehicles and the varying task offloading demands across time and space. To address these issues in multi-client vehicular task offloading environments, we propose Moscato, a blockchain-based distributed task offloading framework. In Moscato, client vehicles function as blockchain consensus nodes, utilizing existing consensus mechanisms for asynchronous, non-real-time global information sharing. To optimize task offloading decisions under diverse task profiles and dynamic traffic conditions, we integrate Federated Learning (FL) with Deep Q-Network (DQN), enabling intelligent, decentralized decision-making. Real-world datasets on edge server workloads and task latencies were collected to conduct simulation-based evaluations. Through comparison with state-of-the-art methods, we demonstrate that Moscato can design a better balance between the execution of newly offloaded tasks and ongoing ones, effectively alleviating resource competition under multi-client scenarios.]]></description>
      <pubDate>Thu, 30 Jul 2026 10:07:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2730968</guid>
    </item>
    <item>
      <title>Edge-Driven Dynamic Two-Tier Blockchain for Energy Trading in Vehicle-to-Grid Networks</title>
      <link>https://trid.trb.org/View/2730942</link>
      <description><![CDATA[Recent developments in vehicle-to-grid (V2G) technology have positioned electric vehicles (EVs) as essential components for increasing the use of renewable energy and managing peak demand. However, while V2G systems utilize blockchain technology for secure energy transactions, they encounter notable inefficiencies due to the high volume of transactions when the number of energy participants increases. The communication overhead associated with processing energy supply and demand is significant. In addition, current energy distribution systems do not fully exploit the potential of EVs. They cannot schedule multiple discharge cycles for a single vehicle over specific periods. Furthermore, existing systems do not provide mechanisms that allow EVs to make smart autonomous decisions about their charging and discharging operations. Instead, they are usually dependent on fixed schedules or manual inputs, which further exacerbates the inefficiency of energy management and market integration. This paper proposes a novel edge-driven two-tier blockchain-based V2G method to optimize the energy management of distributed electric vehicles. The architecture incorporates local dual networks within an electric vehicle blockchain (EVBC) and an energy market blockchain (EMBC), coordinated by a high-level blockchain that manages unfulfilled requests. A dynamic segment-based energy allocation algorithm (DSBEA) is introduced, where the control system allocates energy requests by matching EV offers while continuously updating each EV's remaining energy and available time window after each assignment. The evaluation showed a significant reduction in total time cost compared to baseline methods, with reductions ranging from 42% to 80% in various energy trading scenarios. In addition, the proposed method achieved a 68.6% increase in energy fulfillment compared to the best existing approaches.]]></description>
      <pubDate>Thu, 30 Jul 2026 10:07:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2730942</guid>
    </item>
    <item>
      <title>An Innovative Blockchain-Assisted Multi-Message and Multi-Receiver Heterogeneous Signcryption for Cross-Domain Vehicle Platoon Communication</title>
      <link>https://trid.trb.org/View/2730935</link>
      <description><![CDATA[The operation of autonomous vehicle platooning enhances road efficiency by allowing vehicles to drive in close formation, a process that depends on the platoon leader (PL) communicating essential information to the platoon followers (PFs). In such platoon operations, the efficiency of one-to-many communication and the capability to interact effectively with the PL's heterogeneous domain followers are particularly important for the PL. Tackling the heterogeneity between a sender and multiple receivers, numerous heterogeneous one-to-many signcryption schemes have been proposed. However, these schemes fail to address the issues of heterogeneity between receivers and low efficiency in concurrent one-to-many communication scenarios. To address these challenges, we propose an innovative blockchain-assisted multi-message and multi-receiver heterogeneous signcryption (BMMHSC) scheme, which aims to enhance the efficiency of the PL in concurrently transmitting multiple one-to-many communication messages. Additionally, this scheme leverages blockchain technology as a support system and uses smart contracts to manage the platoon, effectively tackling the heterogeneous communication issues in cross-domain vehicle platoon. A rigorous security proof demonstrates that the BMMHSC scheme is indistinguishable under chosen ciphertext attack (IND-CCA) and existential unforgeability under chosen message attack (EUF-CMA). Experimental results indicate that the scheme incurs low costs in terms of computation, communication, and expenses, making it highly suitable for application in vehicle platooning environments.]]></description>
      <pubDate>Thu, 30 Jul 2026 10:07:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2730935</guid>
    </item>
    <item>
      <title>TMVcrowd: An Authorized and Fine-Grained Encrypted Task Matching Framework on Blockchain for Vehicular Crowdsourcing</title>
      <link>https://trid.trb.org/View/2717762</link>
      <description><![CDATA[Vehicular crowdsourcing has emerged as a promising paradigm that leverages the sensing and computational capabilities of connected vehicles to perform large-scale data collection and task execution. However, existing vehicular crowdsourcing platforms typically rely on centralized servers for task publishing and matching, which introduces risks of single points of failure, privacy leakage, and limited scalability. Blockchain offers decentralization and transparency but poses new challenges, as directly outsourcing sensitive task information onto a public ledger may lead to severe privacy violations. To address these challenges, the authors present TMVcrowd, a blockchain-based framework for authorized and fine-grained encrypted task matching. TMVcrowd enables secure collaboration between task requesters and vehicular workers by integrating attribute-based access control and efficient searchable encryption. Specifically, the authors design a novel constant-length ciphertext attribute-based encryption (CL-ABE) scheme to minimize on-chain storage costs and propose a hybrid encrypted task matching method supporting both keyword and range queries. The authors formally prove the security of the scheme and implement TMVcrowd on Ethereum. Experimental results demonstrate that TMVcrowd achieves strong privacy guarantees, significant storage efficiency, and practical performance, making it suitable for large-scale vehicular crowdsourcing systems.]]></description>
      <pubDate>Wed, 29 Jul 2026 09:13:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2717762</guid>
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