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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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      <title>Technology Selection for IoT-Based Smart Transportation Systems</title>
      <link>https://trid.trb.org/View/1973256</link>
      <description><![CDATA[In this paper, the authors consider the selection of the appropriate technology in Internet of Things (IoT) environments. Specific IoT-based applications, including innovative tracking solutions in automotive or transportation systems, require the mobility of the IoT device under different IoT technologies. Selecting the best technology for connectivity based on several criteria is essential in this context. The authors investigate four LPWAN technologies and they study two well-known multi-attribute decision-making algorithms, TOPSIS and SAW, to select the appropriate IoT technology based on criteria such as bit rate, coverage, power consumption, etc. These two algorithms were implemented to select the best technology depending on the requirements of the application. The obtained results showed that the TOPSIS method gives better results than SAW in the selection and the sorting of the technologies. However, the running time of SAW is smaller.]]></description>
      <pubDate>Tue, 23 May 2023 09:27:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973256</guid>
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    <item>
      <title>Performance Evaluation of Speed Platoon Splitting Algorithm</title>
      <link>https://trid.trb.org/View/1973207</link>
      <description><![CDATA[Platooning of vehicles enhances traffic flow performance in transportation systems. Platoon is defined as a group of vehicles standing one behind another, moving in a line by keeping a very short vehicular gap. Many strategies for platoon formation have been proposed in the literature. These strategies aim to control platoon stability and platoon lifetime. Nevertheless, literature algorithms did not take into account the vehicular congestion problem and platoon velocity. Therefore, the authors propose a new algorithm, called speed platoon splitting (SPS) that targets alleviating congestion by using a ticket pool and classifies platoons according to the velocity using two different lanes. Performance analysis displays that SPS achieves platoon stability and reduces highway congestion.]]></description>
      <pubDate>Tue, 23 May 2023 09:27:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973207</guid>
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      <title>A RINA-Based Security Architecture for Vehicular Networks</title>
      <link>https://trid.trb.org/View/1973188</link>
      <description><![CDATA[In this paper, the authors investigate the use of Recursive InterNetwork Architecture (RINA), a promising network architecture, in a Vehicular Ad hoc Network (VANET) context. The authors especially show that it can address by design the security requirements in order to insure a secure Vehicular Ad hoc Network. Moreover, the authors detail how the ETSI security architecture designed for VANET can be naturally integrated in RINA.]]></description>
      <pubDate>Tue, 23 May 2023 09:27:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973188</guid>
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      <title>Networks of Trusted Execution Environments for Data Protection in Cooperative Vehicular Systems</title>
      <link>https://trid.trb.org/View/1973190</link>
      <description><![CDATA[Networks of autonomous vehicles roaming in smart cities raise new challenges for end-to-end protection of data in terms of integrity, privacy, efficiency, and scalability. This paper provides a survey of Networks of Trusted Execution Environments (NTEE) architectures. NTEE combine the strong, hardware-rooted security guarantees of the TEE deployed locally in the vehicle, with the distributed protection of a decentralized consensus protocol. The authors identify three main families of consensus protocols and analyze their architectures, performance, and security, including improvements brought by the TEE. Overall, voting protocols tend to be more efficient for smaller networks, while lottery-based schemes are not easy to apply in a vehicular context due to higher overheads. Both types of protocols reach an intermediate level of security, with variations in byzantine tolerance and types of threats. Graph-based protocols tend to achieve both efficiency and flexibility in terms of network topology support, but their security still remains to be explored.]]></description>
      <pubDate>Tue, 23 May 2023 09:27:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973190</guid>
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    <item>
      <title>Software-Defined Networking for Emergency Traffic Management in Smart Cities</title>
      <link>https://trid.trb.org/View/1973176</link>
      <description><![CDATA[Vehicle traffic management is becoming more complex due to increased traffic density in cities. Novel solutions are necessary for emergency vehicles, which despite growing congestion must be able to quickly reach their destination. Emergency vehicles are usually equipped with transmitters to control the traffic lights on their path and warn other vehicles with sirens. Transmitters are operated manually and, like sirens, have a limited range. Smart cities can make use of novel network models to facilitate traffic management. In this paper, the authors design a traffic management application leveraging software-defined network controllers for traffic preemption. The proposed application leverages the logical centralization of the SDN control plane to improve traffic management. Results from evaluating the application under five different scenarios indicate that emergency vehicles can reach their destination much faster, with very little effect on the surrounding traffic.]]></description>
      <pubDate>Tue, 23 May 2023 09:27:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973176</guid>
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    <item>
      <title>Vehicular Ad Hoc Networks Security for Smart Cities Based on 2D ZCC/MD Optical CDMA Code</title>
      <link>https://trid.trb.org/View/1973178</link>
      <description><![CDATA[Due to the increasing numbers of vehicles in the world which results in a rise in traffic density, smart city is seeking to minimize transportation problems such as accidents. To solve this issue, VANET has been developed to improve vehicles’ mobility and provide a safe city. VANET is a type of wireless technology which provides vehicle-to-vehicle (V2V) and vehicle-to-infrastructures (V2I) communication system. Despite the advantages of VANET, it faces a lot of challenges; security and privacy, for instance, are the most critical ones. In this paper, the authors implement an approach used in Optical CDMA system given its success in optical domain. This technique is based on the 2D ZCC/MD code which is characterized by zero cross-correlation property. The transmission system is based on the VLC system, in which the information will circulate in optic domain using light in free space. The proposed system can provide the security and the privacy due to the 2D ZCC/MD code which assigns each user by a specific unique code.]]></description>
      <pubDate>Tue, 23 May 2023 09:27:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973178</guid>
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    <item>
      <title>Towards a Reliable Machine Learning-Based Global Misbehavior Detection in C–ITS: Model Evaluation Approach</title>
      <link>https://trid.trb.org/View/1973173</link>
      <description><![CDATA[Global misbehavior detection in Cooperative Intelligent Transport Systems (C–ITS) is carried out by a central entity named Misbehavior Authority (MA). The detection is based on local misbehavior detection information sent by Vehicle’s On–Board Units (OBUs) and by Road–Side Units (RSUs) called Misbehavior Reports (MBRs) to the MA. By analyzing these Misbehavior Reports (MBRs), the MA is able to compute various misbehavior detection information. In this work, the authors propose and evaluate different Machine Learning (ML)-based solutions for the internal detection process of the MA. The authors show through extensive simulation and several detection metrics the ability of solutions to precisely identify different misbehavior types.]]></description>
      <pubDate>Tue, 23 May 2023 09:27:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973173</guid>
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    <item>
      <title>AVEC: A Statistical Framework for Adaptive Vehicular Edge Data Cleaning</title>
      <link>https://trid.trb.org/View/1973175</link>
      <description><![CDATA[In Vehicle-to-Vehicle and Vehicle-to-Infrastructure (V2X) communication, a large amount of data and information is transmitted over the air by the vehicles. If this data is captured, e.g., by a network of roadside units (RSUs) deployed at strategic locations, cleaned and processed, it may generate an interesting value. The process of cleaning the data involves the removal of data duplicates, as two or more RSUs may capture the same information from the same vehicle. Indeed, a vehicle can be located inside the communication range of multiple RSUs at the same time. The data cleaning process can be achieved through a centralized platform in the backend, where all the deployed RSUs connect and upload their collected data. To avoid overloading the backend, the authors propose to involve the RSUs in the cleaning process. Ideally, the RSU should be able to detect if any received information from a passing vehicle has not been also received by another nearby RSU. To achieve that, the authors use an adaptive probability-based splitting of the sensing range. Such a continuous process allows each RSU to adjust the probability distribution of the communication reliability after a sensing time window and to check parameters of neighbor nodes. Simulation results show the efficiency of the solution and demonstrate its ability to adapt with the network dynamicity, by adjusting the algorithm parameters, until reaching a good level of data cleaning compared to static and random approaches.]]></description>
      <pubDate>Tue, 23 May 2023 09:27:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973175</guid>
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      <title>Implementation and Evaluation of Intelligent Roadside Infrastructure for Automated Vehicle with I2V Communication</title>
      <link>https://trid.trb.org/View/1973171</link>
      <description><![CDATA[Automated vehicles (AV) are important elements of smart cities reducing traffic congestions and gas emission. These objectives, however, cannot be achieved without smart infrastructures installed in complex road sections like intersections, roundabouts, blind zones, and uphill. Smart infrastructures equipped with sensors combined with infrastructure-to-vehicle (I2V) communication offer an opportunity to make better decision and to extend perception of AVs. Roadside infrastructure (RSI) is for various services such as green light optimization speed advisory, cooperative awareness, and decentralized event notification supporting AVs to driving safer and in a more efficient manner. Complementary, a collective perception message (CPM) is under specification at European Telecommunications Standardization Institute (ETSI) to transfer information from smart sensors. As CPM carries detailed information on objects detected by the sensors, significant benefits are expected by installing such service on RSI collecting data on blind zones and other complex areas. In this paper, the authors first introduce an intelligent RSI architecture, which is compatible with multiple sensor types and providers, further processes sensor data for CPM creation and transmission. Then, the authors present their  methodology for implementation of their RSI for on-site experimentations. Finally, some key evaluations of CPM transmissions are conducted.]]></description>
      <pubDate>Tue, 23 May 2023 09:27:23 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973171</guid>
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    <item>
      <title>Vehicular Ad-hoc Networks for Smart Cities: Third International Workshop, 2019</title>
      <link>https://trid.trb.org/View/1973174</link>
      <description><![CDATA[This book presents selected papers from the Third International Workshop on Vehicular Ad-hoc Networks for Smart Cities, Paris, 2019. Future smart cities are well placed to profit from extraordinary mobile infrastructures. IWVSC'2019 brings together experts from both academia and industry to discuss recent developments in vehicular networking technologies and their interaction with future smart cities in order to promote further research activities and challenges.]]></description>
      <pubDate>Sun, 31 Jul 2022 15:21:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/1973174</guid>
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