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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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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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      <title>Advanced Integrated Chassis Control for Improved Energy Efficiency and Driving Experience in Electric Vehicle Applications</title>
      <link>https://trid.trb.org/View/2692003</link>
      <description><![CDATA[Complexity of modern ground vehicles grows constantly, since car manufacturers want to provide functionality, while customers are expecting innovation and recent technologies to be integrated into the latest models released to the market. Recent advances in hard- and software opened the gates for new means of vehicle control and operation. Especially the transition to electric propulsion systems and decoupled chassis actuators offer completely new opportunities of dynamics control and manipulation. This paper presents an approach for integrated chassis and vehicle motion control in (battery) electric vehicle applications by using new and innovative controllers as well as mechatronic chassis systems. In several experiments on public roads with a fully instrumented vehicle demonstrator, that features in-wheel based rear-wheel drive and a hybrid brake-by-wire-system, the proposed control is tested under real environmental and traffic conditions with respect to aspects like energy efficiency and driving comfort. The improvements are evaluated by objective performance indicators. In particular, it was found that the controller recovers more kinetic energy during braking maneuvers and lowers driver stress by up to over 90 % fewer mandatory pedal changes compared to already industrialized approaches.]]></description>
      <pubDate>Tue, 14 Apr 2026 15:11:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/2692003</guid>
    </item>
    <item>
      <title>SDVN in Haze: An AI-Driven Solution for Vehicular Networking in Foggy Weather</title>
      <link>https://trid.trb.org/View/2610679</link>
      <description><![CDATA[The winter season worldwide causes serious driving issues due to heavy fog on the roads. In situations like these, having an intelligent transportation system is crucial for safe driving. Therefore, to ensure safe and stable driving in such a natural weather situation, this paper proposes a machine learning-based software-defined vehicular network (SDVN). The SDN main controller (MC) is responsible for selecting the optimal controller (OC) from among several local controllers (LCs). The OC is accountable for sharing the load with the MC and regulating vehicular speed by disseminating alarming messages (AMs) in the form of a speed reduction, lane change, and low visibility alerts. It is also responsible for providing optimal paths from source to destination, thereby ensuring the exchange of data between vehicles in such foggy weather conditions. OC and LCs assist vehicles in calculating link visibility time (LVT) to ensure stable links in the network. To guarantee safety, the paper considers two types of vehicles: normal and stubborn (who do not follow OC’s instructions). The objective is to enable all types of vehicles to travel safely in foggy weather. To achieve this goal and evaluate its validity, the scheme considers different cases following the selection of an OC and the optimal path. Considering different cases in foggy weather, our findings indicate that vehicles can demonstrate safety and stability in low visibility conditions.]]></description>
      <pubDate>Fri, 27 Mar 2026 17:03:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2610679</guid>
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    <item>
      <title>Mitigation of Cybersecurity Vulnerabilities for Traffic Control Infrastructure</title>
      <link>https://trid.trb.org/View/2663282</link>
      <description><![CDATA[As transportation systems incorporate computing technology, cybersecurity risks have grown. This project, in collaboration with the Florida Department of Transportation (FDOT) and the Traffic Engineering Research Laboratory (TERL), aims to enhance the security of traffic controllers and related infrastructure by identifying vulnerabilities, developing cybersecurity specifications, and proposing mitigation strategies. The research team conducted a literature review of cybersecurity standards and best practices in transportation. Based on this review, specifications for authentication, authorization, and encryption were developed, along with a testing procedure. This procedure was demonstrated to TERL staff, who provided feedback for refinement. Applying the procedure to six traffic controller models, the team discovered 20 vulnerabilities, each reported to manufacturers. Several vendors proposed remediation plans, with four software updates scheduled—one already completed. Additionally, a traffic camera assessment focused on its web interface and security scanning, leading to cybersecurity recommendations for agencies and vendors. Future research could expand testing to controller logs, physical security, and advanced cybersecurity threats. If physical access to a traffic camera becomes available, further evaluations can be conducted. This study strengthens transportation cybersecurity by identifying threats and collaborating on solutions to improve system resilience.]]></description>
      <pubDate>Fri, 20 Feb 2026 08:49:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663282</guid>
    </item>
    <item>
      <title>Automotive Ethernet Proxy-Based Security Architecture in Vehicle Computers</title>
      <link>https://trid.trb.org/View/2669809</link>
      <description><![CDATA[Modern vehicles require sophisticated, secure communication systems to handle the growing complexity of automotive technology. As in-vehicle networks become more integrated with external wireless services, they face increasing cybersecurity vulnerabilities. This paper introduces a specialized Proxy based security architecture designed specifically for Internet Protocol (IP) based communication within vehicles. The framework utilizes proxy servers as security gatekeepers that mediate data exchanges between Electronic Control Units (ECUs) and outside networks.At its foundation, this architecture implements comprehensive traffic management capabilities including filtering, validation, and encryption to ensure only legitimate data traverses the vehicle's internal systems. By embedding proxies within the automotive middleware layer, the framework enables advanced protective measures such as intrusion detection systems, granular access controls, and protected over-the-air (OTA) update channels. This strategy enhances both data security and system isolation, creating protective boundaries between critical vehicle operations and potential external attacks.The architecture particularly excels in supporting Vehicle-to-Everything (V2X) connectivity, facilitating seamless information exchange between vehicles, roadside infrastructure, and pedestrians. This capability is essential for enhancing roadway safety, optimizing traffic flow, and supporting autonomous driving technologies. The system incorporates dedicated proxy modules for specialized protocols including Trivial File Transfer Protocol (TFTP), Diagnostic Over Internet Protocol (Doip), and Message Queuing Telemetry Transport (MQTT), each fulfilling specific functions in vehicle diagnostics, software updates, and telemetry data management.Performance evaluations will measure latency and throughput metrics to validate the architecture's efficiency and reliability. The framework's modular design aims to provide scalability and adaptability to accommodate both technological advancements and emerging security challenges.The proxy-based security framework presented offers a holistic and forward-looking approach to safeguarding in-vehicle networks. It provides automotive manufacturers with the tools to develop connected vehicles that combine intelligence and efficiency with robust protection against diverse cybersecurity threats.]]></description>
      <pubDate>Tue, 17 Feb 2026 10:28:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2669809</guid>
    </item>
    <item>
      <title>Enhanced PID for pedal vehicle force control using hybrid spiral sine-cosine optimization and experimental validation</title>
      <link>https://trid.trb.org/View/2591976</link>
      <description><![CDATA[This study develops and validates a force feedback control system for automotive pedals utilizing an optimized PID controller using the hybrid Spiral Sine-Cosine algorithm (SSCA). The primary objective is to enhance system performance by integrating SSCA-tuned PID control and comparing results from simulation and Hardware-in-the-Loop (HIL) testing. Auto Regressive with Exogenous inputs (NARX) models were used as the system identification method for nonlinear dynamic system to accurately represent actuator and pedal force relationships. Results demonstrated that the HIL setup significantly improved performance metrics compared to simulations: overshoot decreased, rise time improved, and settling time reduced for various force parameters. The study confirms that SSCA-tuned PID control can be effectively implemented in real-life applications, particularly in force control pedal vehicles, with potential benefits including reduced driver fatigue due to the repetitive actions of pressing and releasing the vehicle pedal. Future research will aim to enhance this approach by integrating vehicle speed control with advanced actuator and pedal force control systems. This integration will ensure smoother and more precise control over vehicle dynamics, improving overall responsiveness and efficiency. Moreover, a primary focus will be on optimizing low-speed driving scenarios, particularly in traffic congestion, where precise control is critical. By addressing challenges such as stop-and-go movement, vehicle jerks, and energy efficiency, this research seeks to enhance both driver comfort and safety in urban traffic conditions.]]></description>
      <pubDate>Mon, 20 Oct 2025 09:37:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2591976</guid>
    </item>
    <item>
      <title>Leveraging Traffic-in-the-Loop Simulations to Assess the Impact of Traffic on Vehicle Energy Consumption</title>
      <link>https://trid.trb.org/View/2539053</link>
      <description><![CDATA[The advancements in vehicle connectivity and the increased level of driving automation can be leveraged for the development of Advanced Driver Assistance Systems (ADAS) that improve driver safety and comfort while optimizing the energy consumption of the vehicle. In the development phase of energy-efficient ADAS, modeling and simulation are used to assess the potential benefits of these technologies on energy consumption. However, there is a lack of standardized simulation or test frameworks to quantify the benefits. Moreover, the driving scenario and the traffic conditions are often not explicitly modeled when simulating energy-efficient ADAS, even though they have a major impact on the attainable energy benefits. This paper presents the development and implementation of a closed-loop traffic-in-the-loop simulator designed to evaluate the performance of vehicles under realistic traffic conditions. The primary objective is to qualitatively assess how varying traffic conditions influence vehicle energy consumption along a predefined route, highlighting the importance of considering traffic during the development of energy-efficient vehicle controllers. By integrating a dynamic micro-traffic model from the open-source software SUMO with a high-fidelity vehicle model in Simulink, the traffic-in-the-loop simulator provides a comprehensive platform for analyzing the impact of traffic on vehicle efficiency. The micro-traffic model is controlled online through a MATLAB script leveraging TraCI, a TCP based client/server architecture that allows to retrieve values of simulated objects in SUMO and to manipulate their behavior. The findings demonstrate the significant impact of traffic conditions on vehicle energy consumption, highlighting the necessity of simulating traffic environments to properly evaluate the potential benefits of advanced vehicle technologies.]]></description>
      <pubDate>Tue, 29 Apr 2025 17:02:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2539053</guid>
    </item>
    <item>
      <title>Software Architecture for Autonomous Vehicles using MATLAB Simulink</title>
      <link>https://trid.trb.org/View/2511149</link>
      <description><![CDATA[Autonomous vehicles utilise sensors, control systems and machine learning to independently navigate and operate through their surroundings, offering improved road safety, traffic management and enhanced mobility. This paper details the development, software architecture and simulation of control algorithms for key functionalities in a model that approaches Level 2 autonomy, utilising MATLAB Simulink and IPG CarMaker. The focus is on four critical areas: Autonomous Emergency Braking (AEB), Adaptive Cruise Control (ACC), Lane Detection (LD) and Traffic Object Detection. Also, the integration of low-level PID controllers for precise steering, braking and throttle actuation, ensures smooth and responsive vehicle behaviour. The hardware architecture is built around the Nvidia Jetson Nano and multiple Arduino Nano microcontrollers, each responsible for controlling specific actuators within the drive-by-wire system, which includes the steering, brake and throttle actuators. Communication between these components is facilitated through the CAN protocol, which ensures accurate and reliable data transfer essential for real-time decision-making. AEB achieves precise emergency braking and enhances driver comfort through the use of PID controllers, while ACC leverages radar data to maintain a safe distance from the vehicle ahead. LD employs the Hough Transform algorithm for accurate road edge detection. Furthermore, a trained neural network within the system identifies and responds to traffic signals, signage, pedestrians and vehicles. The camera interfaces directly with the Jetson Nano, while radar data is shared with the IMU through a dedicated CAN bus. This integrated approach represents a significant advancement in autonomous vehicle control, thus contributing to enhanced safety, comfort and reliability for both drivers and passengers. This software architecture is designed based on aBaja 2024 competition and according to its rules, regulations, requirements and specifications, the controllers and simulations were designed.]]></description>
      <pubDate>Tue, 18 Feb 2025 14:58:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2511149</guid>
    </item>
    <item>
      <title>Implementing the ATSPM-In-The-Loop Simulation Solution with the TxDOT State-Wide ATSPM System Deployment Plan</title>
      <link>https://trid.trb.org/View/2420080</link>
      <description><![CDATA[This project will introduce automated traffic signal performance measures or ATSPM systems to all stages of traffic signal projects in Texas. The benefits of ATSPM systems have been broadly recognized by agencies. Texas Department of Transportation (TxDOT) is also in the process of state-wide ATSPM deployment. Nonetheless, the ATSPM system is poised to evaluate the traffic signal data generated by controllers. Therefore, access to the real ATSPM systems is limited to a small portion of traffic signal stakeholders, and these stakeholders may not take advantage of ATSPM during traffic signal planning and design due to a lack of data. In a research project sponsored by TxDOT, the research team demonstrated the use of a microscopic traffic simulation engine to generate the needed traffic signal data for real-world ATSPM systems to generate performance measures. With the developed insights and software tools from that project, the research team will assist and facilitate TxDOT to implement the delivered ATSPM-in-the-loop simulation engine toward a regular task for ATSPM-enhanced traffic signal planning and design. This project will also expand the developed ATSPM-in-the-loop simulation platform to meet all the practical needs for TxDOT's ATSPM deployment effort. This project will increase the TRL from 7 to 9 by assisting TxDOT to develop a practical solution to increase stakeholders' access to and acceptance of the ATSPM concept in various types of traffic signal projects.]]></description>
      <pubDate>Thu, 22 Aug 2024 17:19:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2420080</guid>
    </item>
    <item>
      <title>Signal Timing and Coordination — An Art of Engineering</title>
      <link>https://trid.trb.org/View/2281946</link>
      <description><![CDATA[The scientific and engineering aspect of signal timing and coordination is reflected by sophisticated optimization algorithms, computer software, and roadway infrastructure to support servicing traffic flows. On the other hand, implementing a coordinated signal timing plan in the field often involves fine tuning of a plan in order to achieve the best performance. Such a field implementation and fine tune task provides a stage for the traffic engineers to demonstrate their intellectual and artistic skills of manipulating signal timing using the advanced traffic signal controller features. Therefore, traffic engineers often describe signal timing as a form of engineering art. This paper addresses such an artistic aspect of signal timing by illustrating various signal timing tricks applied on different cases. Specifically, the cases to be discussed include: left-turn phasing sequence, pedestrian handling, dealing with long arterials, and strategies for controlling closely-spaced signals. Applying the tricks and tips illustrated in this paper can provide quick fixes to some common operational problems without the need of significant capital investment. Finally, the paper also touches some basic issues related to traffic flow and roadway characteristics in China, and how the signal timing principles may be adapted to China's urban arterials.]]></description>
      <pubDate>Fri, 26 Apr 2024 08:53:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2281946</guid>
    </item>
    <item>
      <title>A Zero Trust Architecture for Automotive Networks</title>
      <link>https://trid.trb.org/View/2367239</link>
      <description><![CDATA[Since the early 1990’s, commercial vehicles have suffered from repeated vulnerability exploitations that resulted in a need for improved automotive cybersecurity. This paper outlines the strategies and challenges of implementing an automotive Zero Trust Architecture (ZTA) to secure intra-vehicle networks. Zero Trust (ZT) originated as an Information Technology (IT) principle of “never trust, always verify”; it is the concept that a network must never assume assets can be trusted regardless of their ownership or network location. This research focused on drastically improving security of the cyber-physical vehicle network, with minimal performance impact measured as timing, bandwidth, and processing power. The automotive ZTA was tested using a software-in-the-loop vehicle simulation paired with resource constrained hardware that closely emulated a production vehicle network. For example, the vehicle’s Advanced Gateway electronic control unit (ECU) is utilized to enforce cyber policy, monitor the network, distribute keys, and implement network segmentation. The technical approach applied other security solutions, including Secure Onboard Communication (SecOC) for authentication and verification of network traffic, and Secure Boot to ensure the system is running authentic software. Implementing these elements and the other security controls was complicated by cost, resource constraints, and the complexity of building and maintaining vehicles.The project team identified four metrics to demonstrate performance success and feasibility of the implementation. They are as follows: 1) Error monitoring system detected 100% of illicit messages, 2) ECUs refused unauthorized firmware 100% of the time, 3) ECUs discarded unauthenticated messages 100% of the time, 4) Latency at first ignition cycle was less than one second. This research successfully met the four requirements and demonstrated that using ZT principles in an on-vehicle network greatly improved the cybersecurity posture with manageable impact to system performance and deployment.]]></description>
      <pubDate>Tue, 16 Apr 2024 09:52:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2367239</guid>
    </item>
    <item>
      <title>PedPal Lite: An ATSC-Independent Safe Intersection Crossing App</title>
      <link>https://trid.trb.org/View/2292660</link>
      <description><![CDATA[PedPal is a smartphone app designed to assist pedestrians with disabilities in safely crossing signalized intersections, developed originally as part of the Federal Highway Administration’s Accessible Transportation Technology Research Initiative (ATTRI) [1,2].   PedPal interacts directly with the surtrac adaptive traffic signal control (ATSC) system operating at the intersection using real-time traveler-to-infrastructure (T2I) communication and standard DSRC messaging to provide crossing support to its user.  Upon arrival at the intersection, PedPal receives and presents information to its user about the intersection’s geometry, crossing options, and current traffic signal state. When the user indicates her crossing intent, the app then communicates this information to the intersection (eliminating the need to locate and push a pedestrian call button), along with how much time is required by the user to safely cross the intersection. In response to receiving this information, the traffic signal system will set the pedestrian crossing time in the desired direction to ensure that upon getting the crossing signal, the user will receive crossing time that has been requested. More advanced PedPal capabilities include the ability to monitor user crossing progress in real-time, to recognize when the user is traveling slower than expected, and to trigger the traffic control system to dynamically extend the crossing time in such circumstances. The PedPal app is integrated with the smartphone's native accessible features and provides visual, auditory and haptic interaction modalities.   This project focuses on producing a cheaper and more broadly deployable version of PedPal. Whereas the ability exploit surtrac’s real-time ATSC capabilities enable advanced capabilities such as dynamic extension of the current phase duration that enhance safety, its deployment cost to municipalities presents a significant barrier to widespread deployment of the PedPal technology. Furthermore, a recent UTC funded project centered on technology support for the 'complete trip' has expanded the scope of PedPal's capabilities in several new safety-related directions, none of which depend on interaction with surtrac.  To foster more widespread deployment of the PedPal technology, this project will develop and pilot test a stand-alone version of PedPal (referred to as ‘PedPal-Lite’) that will interact directly with the hardware controller at the intersection via an ATSC-independent PedPal intersection manager. This manager will take over responsibility from the Surtrac ATSC system both for broadcasting information about the intersection and the current traffic control state to the smartphone app and for interacting with the traffic controller in response to messages received from the app, exploiting the same underlying T2I connectivity. The manager will run on a low-end processor residing in the cabinet at the intersection and will take advantage of the V2I-hub software module developed under sponsorship of FHWA to generate DSRC formatted messages for broadcast to PedPal users. To maximize deployment potential, the research team will focus integrating the PedPal intersection manager with controllers that support standard NTCIP interaction protocols.  The research team will demonstrate and pilot test the developed PedPal-Lite variant on a TBD intersection near the CMU campus that is running a conventional fixed signal timing plan on a hardware controller that supports the NTCIP standard.]]></description>
      <pubDate>Tue, 21 Nov 2023 18:56:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2292660</guid>
    </item>
    <item>
      <title>An Application of Client/Server Architecture in Interfacing Virtual Traffic Signal Controller with CORSIM</title>
      <link>https://trid.trb.org/View/2148875</link>
      <description><![CDATA[Traffic simulation, interfaced with traffic signal controller or traffic control algorithms, can be used to evaluate traffic operations and traffic control in a laboratory environment. This virtual environment can be integrated through client/server computing approaches. The CORSIM (CORridor SIMulation) is microscopic traffic simulation software developed by the Federal Highway Administration. It is distributed as a part of the Traffic Software Integrated System (TSIS). The TSIS suite is a collection of software tools used to support CORSIM. TSIS provides an Application Programming Interface (API) between an external application (e.g., a traffic control application) and CORSIM. This type of interface is known as a run time extension (RTE). To overcome the limitations of CORSIM RTE, a new type of CORSIM client/server API was proposed. The client API was defined and developed to interface CORSIM with a third-party virtual traffic controller server. The new client application needs few source code changes for different servers by different vendors. A railroad preemption case was designed to test the architecture and the client-side software. Sample cases ran successfully in real time on a TCP/IP network with no program execution delays. This paper exemplifies how the client/server application can benefit highway railroad traffic signal preemption studies. The example cases show the dynamics of area traffic (including railroad traffic), traffic control devices and other factors have been systematically and realistically captured in evaluating railroad preemption design.]]></description>
      <pubDate>Wed, 15 Nov 2023 09:19:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2148875</guid>
    </item>
    <item>
      <title>Data Subsystems and Data Management Plans for Traffic Management Systems</title>
      <link>https://trid.trb.org/View/2286626</link>
      <description><![CDATA[Traffic management systems (TMSs) are deployed in the United States to improve the efficiency, safety, and reliability of travel on designated portions of the surface transportation network. TMSs are typically large, complex systems, that consist of a number of subsystems (e.g., ramp metering, traffic signal control, dynamic message sign, data, traveler information, communication, software, hardware), as well as a range of components (e.g., dynamic message signs, detection devices/sensors, closed-circuit television cameras, signal heads, controllers, communication switches, servers, video wall, phones).

TMSs capabilities could support different services, functions, tasks, or actions. For example, some TMSs manage only the vehicular traffic on freeways in each region, while others may manage the entire road network, which may include surface streets and freeways. TMSs may also have different roles and responsibilities (e.g., sharing roadway and traveler information) that involve sharing, coordinating, or making information available to other agencies, systems, or service providers (e.g., emergency services, transit).

TMSs range in size (i.e., coverage area), functionality (e.g., incident management, ramp management), services (e.g., traveler information, managing traffic across institutional boundaries), and capabilities (e.g., whether or not the system includes a traffic management center, which can be used for sharing information).

Significant changes have occurred with cloud options available to agencies to store data. TMSs have traditionally been designed with local servers and limited ability to modify or make changes. Technical options are available to support agencies making changes in the design, configuration, and technologies used to support a data subsystem (see Special Note A). 

Limited technical information and resources exist to help agencies assess the capabilities and evolving needs for TMSs data subsystems. There are limited resources to support agencies integrating the needs and requirements of data subsystems into the decisions made in planning and programming processes throughout the life cycle of a TMS (e.g., how to plan, design, or procure needed data storage and management capabilities). Agencies face challenges with systematically managing data as part of their TMSs operation. There are limited resources for agencies to use or to assist with data management (e.g., archiving, use, configuration, monitoring use), and issues with receiving, sharing or using data with third-party sources or within an agency (e.g., licenses, proprietary, sensitive information). Research is needed to help agencies better manage data in TMSs.  

The objective of this research is to develop two technical reports to support agencies’ decision-making processes and frame the opportunities for agencies to consider when contemplating improvements to data subsystems and data management plans of their TMSs: (1) Report No.1, Data Subsystems for TMSs, and (2) Report No.2, DMP for TMSs.]]></description>
      <pubDate>Tue, 07 Nov 2023 12:01:28 GMT</pubDate>
      <guid>https://trid.trb.org/View/2286626</guid>
    </item>
    <item>
      <title>Strategy Analysis and Evaluation for Emergency Vehicle Preemption and Transit Signal Priority with Connected Vehicles using Software in the Loop Simulation</title>
      <link>https://trid.trb.org/View/2239857</link>
      <description><![CDATA[The overarching objective of this project was to develop and evaluate advanced strategies for Emergency Vehicle Preemption (EVP) and Transit Signal Priority (TSP) implementation that would incorporate and integrate real-time information from connected vehicles, transit vehicles, traffic signal controllers, and other traffic detection technologies to improve overall performance relative to current practice. A microscopic simulation environment was developed in PTV Vissim and calibrated to a real-world corridor for this study. The study demonstrated the benefits of using EVP with dynamic triggering of preemption as compared to no-preemption and traditional preemption using fixed check-in-check-out detectors and developed a novel dynamic preemption logic that minimizes delay for the emergency vehicle while at the same time keeping the preemption period, and hence the disruption to the remaining traffic, to a minimum. The study also developed a machine learning algorithm to generate preemption triggers at lower levels of real-time traffic data availability. The study then created a model to simulate the pull-over behavior of the general traffic, to make the simulation model more realistic and developed code that can be reused by other researchers and practitioners to easily incorporate the advanced model in their simulation. Lastly, the study expanded the effort to TSP and developed some generic guidelines for TSP implementation based on the findings of the study.]]></description>
      <pubDate>Fri, 06 Oct 2023 08:38:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2239857</guid>
    </item>
    <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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