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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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      <title>Intelligent Vehicle Highway Safety: A Smart Choice for the Future [Video]</title>
      <link>https://trid.trb.org/View/2732191</link>
      <description><![CDATA[An animated "glimpse of the future" that shows how the four components of IVHS (Advanced Traffic Management Systems, Advanced Traveler Information systems, Commercial Vehicle Operations and Advanced Vehicle Control Systems) will contribute to increase driver safety and mobility.]]></description>
      <pubDate>Sat, 08 Aug 2026 18:07:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2732191</guid>
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      <title>Traffic information impact on the optimisation of fuel consumption and emissions in an urban driving scenario</title>
      <link>https://trid.trb.org/View/2696110</link>
      <description><![CDATA[Traffic jams are one of the main causes of city pollution and significantly impact the economic cost of transportation. Context awareness by the traffic players may be key to improving the current control strategies and optimising traffic flow. This study investigates the effect of information availability through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity in an urban real-driving route. An optimal control problem (OCP) is formulated to create speed advisory profiles, and it is solved using dynamic programming (DP) to provide the global optimal solution. Experimental engine tests have been used to characterise the fuel consumption and emissions of the engine, while traffic sensors around the city of Valencia have been used to reproduce realistic urban mobility using the traffic simulation software SUMO. The paper quantifies the impact of traffic information on vehicle fuel consumption and emissions. Under normal traffic conditions and assuming total access to the traffic information, the DP algorithm can reduce almost 60% on average the fuel consumption compared to normal driving behaviour provided by the default car-following model of SUMO.]]></description>
      <pubDate>Fri, 31 Jul 2026 09:23:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2696110</guid>
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      <title>Traveler Information Technologies in the National Park System</title>
      <link>https://trid.trb.org/View/2731916</link>
      <description><![CDATA[This report details completed and ongoing traveler information-focused Intelligent Transportation System (ITS) deployments on National Park Service (NPS) lands. It reviews six ITS technologies areas – data feeds, mobility data, vehicle-to-everything (V2X) technology, machine learning and artificial intelligence, geofenced alerts, and physical infrastructure and equipment – which can address common NPS transportation challenges, such as congestion, safety, and operational efficiency. Technology reviews include the status of NPS usage and key takeaways for implementation. The report also provides recommendations to increase the adoption of these technologies and thus improve planning, operational efficiency, and visitor experience across the park service’s transportation system.]]></description>
      <pubDate>Thu, 23 Jul 2026 09:16:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2731916</guid>
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      <title>Rampcast Phase II: Connected Vehicles Traffic Management Application on Indiana Highways</title>
      <link>https://trid.trb.org/View/2727584</link>
      <description><![CDATA[This project advances connected vehicle applications by developing and testing an enhanced RampCast system, a comprehensive traffic management system using Cellular Vehicle-to-Everything (C-V2X) technology for Indiana highways. The system features a dual-mode architecture integrating both short-range (PC5) and long-range cellular (Uu) C-V2X communication pathways, utilizing commercial-grade Cohda MK6 hardware and adhering to SAE J2735 standards to ensure interoperability. A key innovation is the integration of an Artificial Intelligence (AI)-based prioritization framework, which leverages a large language model to enhance the contextual relevance of traffic messages. This AI system introduces two intelligent agents: one to dynamically estimate the appropriate display distance for an event based on its severity, and another to prioritize the order of messages based on urgency and potential driver impact. Field tests conducted on I-65 and I-70 in Indianapolis validated the system's hybrid design. Results confirmed that the PC5 link provides very low latency (around 25 ms), ideal for time-critical alerts, while the Uu link ensures highly reliable coverage in complex environments, albeit with higher latency (around 45 ms). The AI framework was successfully shown to reorder and present messages based on real-time context, improving the clarity and usefulness of information provided to the driver. These findings support a hybrid C-V2X architecture as a robust model for future smart highway deployments.]]></description>
      <pubDate>Tue, 21 Jul 2026 09:48:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727584</guid>
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    <item>
      <title>Standardized Framework for Winter Weather Road Condition Indices</title>
      <link>https://trid.trb.org/View/2693715</link>
      <description><![CDATA[State and local agencies across the United States have developed winter weather road condition indices (WWRCIs) to support decisions related to roadway operations, public information, road closures, and winter maintenance responses based on prevailing conditions. However, the absence of a standardized national framework for WWRCIs has resulted in substantial variation in how road conditions are defined, assessed, and communicated. These inconsistencies can create confusion for travelers and limit the ability of transportation agencies to compare performance, share best practices, and benchmark winter operations effectively. The objective of this project was to develop a standardized national framework for WWRCIs that reflects both operational realities and safety impacts across diverse climatic and geographic contexts in the United States. The framework is informed by a comprehensive assessment of existing practices, stakeholder input, and advances in data availability, including traditional weather and roadway sensors as well as emerging connected and autonomous vehicle (CAV) data sources. By promoting consistent definitions, indicators, and measurement principles, the proposed framework aims to advance the accuracy, reliability, and usefulness of winter road condition information provided to transportation agencies, policymakers, and the traveling public. Ultimately, this effort supports improved driver safety, reduced crashes and congestion, and more effective and coordinated winter weather response strategies nationwide.]]></description>
      <pubDate>Fri, 17 Apr 2026 08:55:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2693715</guid>
    </item>
    <item>
      <title>Environmental Sensors for Safe Traffic Operations</title>
      <link>https://trid.trb.org/View/2683249</link>
      <description><![CDATA[The meteorological parameters that have the greatest impact on drivers and their safety are rainfall, snow, ice, fog, and wind. To minimize the impact of these conditions, information can be provided to travelers en route or prior to departing, as well as to highway maintenance crews. The rapid response of appropriate measures can potentially save lives, as well as retain mobility. This demand has led to the development of sensor systems to collect data on pavement temperatures and chemical composition, air temperature and humidity, wind velocity and direction, visibility, and precipitation. This research was initiated to review the state of the art of environmental sensors and to determine where improvements might be made.]]></description>
      <pubDate>Mon, 13 Apr 2026 16:27:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2683249</guid>
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    <item>
      <title>AZ TripUSA™</title>
      <link>https://trid.trb.org/View/2683248</link>
      <description><![CDATA[Northern Arizona has more than 6 million visitors per year. More than 2 million of these visitors will explore the World Wide Web to learn more about their destination prior to their trip. For this reason, the Federal Highway Administration, in partnership with the Arizona Department of Transportation (DOT), sponsored the development of the AZ TripUSA™ Rural Model Deployment Initiative (MDl)/Field Operation Test (FOT) in Northern Arizona along I-40. The result was TripUSA™ (developed by Castle Rock Consultants). This program is a public/private partnership created to improve traveler mobility, enhance economic development for the area, and enrich the overall experience of travelers. AZ TripUSA™ was successfully deployed during the first 6 months of 1998. TripUSA™ allows travelers who use the Internet to discover a wealth of information about their destination for use in trip and travel planning. Upon arriving at their destination, travelers can use interactive touch-screen kiosks to check road and weather conditions, find lodging and restaurants, and obtain directions to attractions.]]></description>
      <pubDate>Mon, 13 Apr 2026 16:27:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2683248</guid>
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    <item>
      <title>Branson Travel and Recreational Information Program (TRIP)</title>
      <link>https://trid.trb.org/View/2683247</link>
      <description><![CDATA[The city of Branson, Missouri, has a permanent population of around 4,400 and measures approximately 7 mi (11.3 km) along its main thoroughfare, State Highway 76. Branson attracts more than 6 million visitors per year. The congestion on State Highway 76 is severe (Level of Service F) during peak and some off-peak periods. The lack of right-of-way makes it impossible for the city to "build" out of its congestion problems. With this in mind, the Branson Travel and Recreational Information Program (TRIP) project was created. The Branson TRIP project was one of five Advanced Rural Transportation System Operational Tests selected in August 1997 by the Federal Highway Administration for deployment. The Branson area provided an excellent opportunity to test Advanced Traveler Information System (ATIS) technologies in a rural tourist destination.]]></description>
      <pubDate>Mon, 13 Apr 2026 16:27:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2683247</guid>
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    <item>
      <title>General Transit Feed Specification (GTFS) Phase II Report</title>
      <link>https://trid.trb.org/View/2663125</link>
      <description><![CDATA[This report provides an overview of the National Park Service (NPS) General Transit Feed Specification (GTFS) Phase II Project. To better connect visitors to parks and improve trip planning capabilities, the NPS is interested in improving and seamlessly sharing transit information on third-party applications, such as Google Maps and Apple Maps, and NPS digital products, such as the NPS app and website. With parks turning to transit service to help manage congestion and expand visitor access, creating and sharing GTFS feeds is a cost-effective way to enhance operational efficiency by reducing staff time devoted to sharing transit information with visitors and directing traffic. This project aligns with the 2025 NPS National Transportation Strategy objective of improving and expanding trip planning tools. GTFS is the standardized and widely accepted method for transmitting transit information to third-party navigation applications. GTFS feeds can either be “static,” displaying a pre-determined, fixed schedule, or “realtime,” displaying live updates of transit vehicle positions and expected arrival times. Establishing GTFS feeds can help visitors make more informed travel decisions and further integrate NPS systems into the larger transit network. This project aimed to build upon the Phase I work by creating static GTFS feeds for high boarding transit systems, compiling GTFS realtime feeds, and providing recommendations for continuing and improving GTFS feed creation and maintenance.]]></description>
      <pubDate>Thu, 12 Feb 2026 08:52:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663125</guid>
    </item>
    <item>
      <title>Unlocking the potential of cooperative staggered shifts in urban networks</title>
      <link>https://trid.trb.org/View/2604660</link>
      <description><![CDATA[Staggered shifts strategies effectively alleviate traffic pressure and promote the rational allocation of traffic resources by dispersing peak-hour traffic demands. The development of advanced traveler information systems (ATIS) platforms has facilitated the rapid transmission and precise delivery of traffic information. Current studies have combined ATIS platforms with staggered shifts strategies to propose cooperative staggered shifts (CSS) strategies, which can enhance the sophistication of staggered shifts strategies and, consequently, improve their effectiveness. However, current studies on CSS inadequately consider the heterogeneity in the willingness of travelers with different travel behaviors to adjust their departure times. Additionally, existing studies have used traffic state optimization as the sole objective function, without considering system costs. To fill this gap, this study integrates multi-source spatiotemporal big data and survey data to analyze the willingness of travelers with different travel behaviors to adjust their departure times. Based on this analysis, a modeling framework for CSS that considers system costs is constructed. The framework is designed with the dual objectives of optimizing traffic conditions and minimizing system costs. Using the fast-solving algorithm proposed in this study for large-scale scenarios, the Pareto front of the CSS framework is analyzed. Taking Hangzhou city, China as an example, the results indicates that an 11.1% optimization effect on the traffic state can be achieved with only 2.4% of the maximum system cost; As the system cost increases, the marginal benefits of CSS diminish. The research findings can provide effective support for the modeling and policy formulation of CSS strategies.]]></description>
      <pubDate>Mon, 22 Dec 2025 16:07:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2604660</guid>
    </item>
    <item>
      <title>Real-time Bus Arrival Information Service: Optimal Dissemination Value Considering Non-travel Activities</title>
      <link>https://trid.trb.org/View/2625761</link>
      <description><![CDATA[When real-time bus arrival information is provided, passengers adapt their en route behaviour, demonstrating a strong propensity to engage in short-term non-travel activities to enhance travel time utility. However, accurately predicting bus arrivals remains challenging due to various operational uncertainties, necessitating an effective information dissemination strategy for Advanced Traveler Information Systems (ATIS). This study focuses on passengers’ time interval from receiving arrival information to boarding, defined as the “catching process”. To minimize the time cost during this process, we develop a cost-minimization model that treats the disseminated bus arrival time as the decision variable and incorporates passengers’ behaviour feedback, namely, their choice of non-travel activity duration. The theoretical framework determines the optimal dissemination value within the prediction confidence interval. Numerical experiments under a typical scenario show that the optimal dissemination value reduces the expected catching time cost per passenger by an amount equivalent to 5.82 min of in-vehicle time (an 11.5% saving), compared to the benchmark strategy of disseminating the estimated time of arrival. Furthermore, sensitivity analyses reveal that prediction accuracy and travel purpose are critical determinants of the optimal dissemination strategy. In contrast, factors such as bus arrival time distribution, service headway, estimated time of arrival, and passenger access time exhibit negligible influence. These findings indicate that the proposed optimal dissemination strategy is particularly beneficial for ATIS with low prediction accuracy and for passengers with high punctuality requirements.]]></description>
      <pubDate>Wed, 17 Dec 2025 08:49:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2625761</guid>
    </item>
    <item>
      <title>Navigating the truck parking challenge: A comprehensive review of strategies, emerging technologies, and future directions</title>
      <link>https://trid.trb.org/View/2626057</link>
      <description><![CDATA[Freight transportation systems play a vital role in the economy of the United States, making adequate truck parking essential for safe and efficient operation. However, a significant gap between truck parking demand and supply has led to challenges, including road safety risks, regulatory non-compliance, operational inefficiencies, and environmental impacts. Despite their importance, comprehensive reviews of potential solutions to truck parking are limited. This study fills this knowledge gap by reviewing current truck parking management approaches with a focus on intelligent truck parking information systems, data prediction models, and parking behavior analysis. The analysis encompasses various technological solutions, including sensing infrastructure, GPS technology, and information dissemination methods. This review also examines emerging solutions in smart parking systems and the potential adoption of these solutions to address truck parking challenges. Furthermore, the current challenges, possible solutions, and future research directions are presented.]]></description>
      <pubDate>Tue, 02 Dec 2025 09:57:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2626057</guid>
    </item>
    <item>
      <title>The value of partial and full pre-trip information under stochastic demand and bottleneck capacity in the morning commute</title>
      <link>https://trid.trb.org/View/2596771</link>
      <description><![CDATA[This paper studies the welfare effects of providing pre-trip information to morning commuters in a single-bottleneck model, where both bottleneck capacity and travel demand are exogenously stochastic and assumed to follow an arbitrary joint distribution. We first derive the equilibrium travel costs under varying levels of information completeness, and then examine how information completeness influences travel costs and the key factors driving the welfare outcomes of information provision. We find that the welfare effects of providing pre-trip information are associated with the information completeness, the degree of correlation between bottleneck capacity and demand, and the frequency and amplitude of bottleneck capacity and demand changes. Although providing full information is never welfare-reducing, providing partial information can increase travel costs compared to no information (i.e., information paradox) when demand and bottleneck capacity are moderately correlated. Nevertheless, transitioning from partial to full information consistently leads to a reduction in travel costs. Our numerical examples further confirm the theoretical results and highlight the necessity of accounting for uncertainties in both supply and demand when developing traveler information systems.]]></description>
      <pubDate>Mon, 24 Nov 2025 10:22:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2596771</guid>
    </item>
    <item>
      <title>Real-time driver alerts to improve CMV safety in California work zones: A naturalistic study</title>
      <link>https://trid.trb.org/View/2617087</link>
      <description><![CDATA[Commercial motor vehicles (CMVs) are disproportionately involved in crashes around work zones. We seek to reduce these crashes via location-based in-cab alerts ahead of work zone activity. It was hypothesized that alerted drivers would reduce their speed, and that they would remain alert for traffic hazards as they passed through work zones. This would in turn reduce CMV-involved crashes and associated injuries and fatalities. Participants comprised existing users of a mobile application that provides free safety alerts exclusively to commercial drivers. Experimental group vehicles received a pop-up notification and audible chime 500 m before work zones, control group vehicles received no such alert. Location data was collected for all CMVs 30 s before alert through 5 min after the alert geofence, which was used to determine vehicle speed. An anonymous driver survey was also deployed in November - December 2024 via email to assess driver perceptions of the alerting experience and the safety impact of these alerts. Analyses from April 1 - December 23, 2024 for 228,713 vehicle visits at 4,080 unique work zones across nine counties in California indicate that, within the first 10 s post-alert, alerted drivers traveling above 55 mph reduce their speed by up to 0.5 mph more than the control group (p = .02), with a 30% greater magnitude of speed reduction. Lane-specific alerts may also be more effective than generic alerts, with slopes of deceleration up to 1.5 times steeper (p < .001). A survey of drivers participating in the present study (N = 422) found that 82% of drivers reported slowing down when receiving these alerts and 83% reported paying increased attention to their surroundings. In-cab notifications of active work zones in California appear to promote safer driving behaviors among commercial drivers exceeding the CMV speed limit. More informative alerting may have a more pronounced impact. Drivers appear to perceive these alerts as helpful in promoting safer driving behaviors.]]></description>
      <pubDate>Wed, 19 Nov 2025 17:09:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/2617087</guid>
    </item>
    <item>
      <title>A Walk across Europe: Development of a high-resolution walkability index</title>
      <link>https://trid.trb.org/View/2601906</link>
      <description><![CDATA[Physical inactivity significantly contributes to obesity and other non-communicable diseases, yet efforts to increase population-wide physical activity levels have met with limited success. The built environment plays a pivotal role in encouraging active behaviors like walking. Walkability indices, which aggregate various environmental features, provide a valuable tool for promoting healthy, walkable environments. However, a standardized, high-resolution walkability index for Europe has been lacking. This study addresses that gap by developing a standardized, high-resolution walkability index for the entire European region. Seven core components were selected to define walkability: walkable street length, intersection density, green spaces, slope, public transport access, land use mix, and 15 min walking isochrones. These were derived from harmonized, high-resolution datasets such as Sentinel-2, NASA’s elevation models, OpenStreetMap, and CORINE Land Cover. A 100 m × 100 m hierarchical grid system and advanced geospatial methods, like network buffers and distance decay, were used at scale to efficiently model real-world density and proximity effects. The resulting index was weighted by population and analyzed at different spatial levels using visual mapping, spatial clustering, and correlation analysis. Findings revealed a distinct urban-to-rural gradient, with high walkability scores concentrated in compact urban centers rich in street connectivity and land use diversity. The index highlighted cities like Barcelona, Berlin, Munich, Paris, and Warsaw as walkability leaders. This standardized, high-resolution walkability index serves as a practical tool for researchers, planners, and policymakers aiming to support active living and public health across diverse European contexts.]]></description>
      <pubDate>Tue, 18 Nov 2025 09:30:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2601906</guid>
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