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    <title>Transport Research International Documentation (TRID)</title>
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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>Enhancing Commercial Motor Vehicle Safety and Compliance: Evaluating The Aries Pilot and Illegal Bypass Behavior in Oregon</title>
      <link>https://trid.trb.org/View/2726122</link>
      <description><![CDATA[Illegal bypass of weigh stations and roadside inspection facilities poses a measurable safety and compliance risk within Oregon’s commercial motor vehicle (CMV) system. When vehicles evade inspection, potential violations such as overweight operations, equipment deficiencies, and hours-of-service noncompliance may go undetected, increasing crash exposure and infrastructure damage risk. Oregon Department of Transportation's (ODOT’s) Commerce and Compliance Division (CCD) currently lacks a standardized, integrated methodology to quantify illegal bypass behavior or link bypass events to inspection outcomes, crash involvement, and carrier safety history.
OBJECTIVES: This research will deliver to ODOT: (1) A standardized and replicable data integration framework linking ARIES pilot data with CCD inspection, violation, crash, and carrier safety records. (2) Measurable and trackable performance indicators to support ongoing internal monitoring of illegal bypass activity and automated enforcement effectiveness. (3) Quantitative analysis of the magnitude, characteristics, and safety implications of illegal bypass behavior in Oregon. (4) Evaluation of ARIES pilot impacts on compliance rates, inspection targeting efficiency, enforcement productivity, and CMV safety outcomes. (5) Implementation guidance and best-practice recommendations to inform strategic investment decisions, future site deployments, and FMCSA Innovative Technology Deployment (ITD) funding applications.
This research will strengthen ODOT’s ability to detect and deter illegal bypass behavior, directly advancing Oregon’s transportation safety goals. By integrating ARIES data with inspection and crash records, CCD will be able to target high-risk vehicles more effectively, reduce unnecessary inspections of compliant carriers, and improve enforcement productivity. The project supports ODOT priorities related to Safety, Innovative Technologies, Process Improvement, and Stewardship of Public Resources by providing measurable evidence to guide enforcement modernization.]]></description>
      <pubDate>Wed, 08 Jul 2026 17:24:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/2726122</guid>
    </item>
    <item>
      <title>Utilizing Drone Technology for Pavement Surface Condition Evaluation at Truck Weigh Stations: A Case Study from the State of Virginia</title>
      <link>https://trid.trb.org/View/2675891</link>
      <description><![CDATA[Pavement management systems (PMS) are essential for optimizing maintenance budgets and scheduling effective treatments for pavement networks. Traditionally, PMS rely on manual pavement distress data collection, a process that is both costly and time-consuming. This study explores the use of unmanned aircraft systems (UAS), commonly known as drones, as an alternative for collecting pavement surface distress data. The study focused on 13 truck weigh stations managed by the Virginia Department of Transportation and the Virginia Department of Motor Vehicles in the U.S. A drone was utilized to capture detailed images of pavement sections, which were then analyzed using an artificial intelligence model to generate pavement surface evaluation and rating (PASER) scores. These drone-derived PASER scores were compared with those obtained through traditional manual inspections. The results demonstrate that the PASER values from drone imagery and manual surveys align closely, with statistical analyses showing no significant differences overall. However, discrepancies were noted for Portland cement concrete sections, where the drone technology analysis method missed certain distresses such as joint seal damage. This limitation highlights the need for improvements in drone imaging or additional technologies to fully capture and analyze all distress types. Moreover, challenges such as weather dependency, regulatory constraints, and site conditions must be addressed to optimize drone use in pavement management.]]></description>
      <pubDate>Mon, 02 Mar 2026 13:29:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2675891</guid>
    </item>
    <item>
      <title>Assessment of the Impact of the Francis Scott Key Bridge Collapse on Regional Traffic</title>
      <link>https://trid.trb.org/View/2620639</link>
      <description><![CDATA[The collapse of the Francis Scott Key (FSK) Bridge in Baltimore, Maryland, on March 26, 2024, killed six people, severed a major interstate highway, and closed the Port of Baltimore for 78?days. The authors of this paper, in collaboration with the Bureau of Transportation Statistics and the Maryland Department of Transportation State Highway Administration (MDOT-SHA), were tasked with monitoring the impact of the FSK Bridge collapse on the regional road network. To do so, the study leveraged multiple data sources provided by MDOT including commercial motor vehicle (CMV) anonymized trajectory data, traffic volumes from count stations and virtual weigh stations, travel times from vehicle probe data, and incident data extracted from the Center for Advanced Transportation Technology Laboratory’s Regional Integrated Transportation Information System. The study looked at both short-term (2?weeks before and after the bridge collapse) and long-term (3?months after the bridge collapse compared with the same dates in 2023) impacts of the bridge collapse on CMV travel patterns, traffic volumes, travel times, travel time reliability, and incidents. The analysis revealed significant changes across all analysis metrics. Key findings include long-term increases in the average, median, and 95th percentile travel times for all alternative routes, indicating increased congestion and diminished travel time reliability. In addition, the incident count increased, especially outside of peak hours, where an increase of 60% to 172% was observed across different alternative routes.]]></description>
      <pubDate>Tue, 11 Nov 2025 09:21:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2620639</guid>
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    <item>
      <title>Evaluation of Manual Thermal Brake Screening Systems</title>
      <link>https://trid.trb.org/View/2611095</link>
      <description><![CDATA[In 2021, manual thermal brake screening systems were installed at Lyon EB and Rowan County weigh stations. Two additional units were installed at Laurel SB and Scott County weigh stations the following year. Although this system is called a thermal brake screening system, its thermal camera images are used to find both brake and tire-related violations. At the time of this project, Lyon EB, Rowan, and Scott County inspection locations also had tire pressure detection systems in addition to manual thermal brake screening systems. Both systems can be used to identify tire-related violations, but inspectors prefer to use the tire pressure detection system for its ease of use. As a result, the usage rates for the thermal brake screening systems in Rowan and Scott Counties have been low to nonexistent. A quantitative analysis was conducted on the inspections that occurred at Lyon EB and Laurel SB, where the use of the technology was high, to determine the system's effectiveness. A comparison of the level 1 inspection results using the thermal brake screening system to the ones without thermal screening has shown that the system is effective in identifying vehicles with brake and tire-related violations. The use of thermal camera images resulted in a significantly higher number of detected violations and out-of-service placements. It should be noted that inspectors prefer to use tire pressure detection systems for tire-related violations over thermal camera images if an inspection location is already equipped with tire pressure detection systems. Additional training on thermal brake screening systems is recommended so inspectors can use the right tool for brake-violation identification. The training is recommended at weigh stations with both thermal brake screening systems and tire pressure detection systems. In considering expanded use of the thermal brake screening system, we recommend that Kentucky explore the benefits and costs associated with automated systems as an alternative to the manual ones. A quantitative comparison of benefits and costs of an automated system is currently unavailable, so we recommend Kentucky (1) reach out to states with automated systems and collect information on the frequency of breakdowns, the main causes of the breakdowns, the duration of the breakdowns before repair, and the costs related to the repairs; (2) compare them to manual systems in Kentucky; and (3) conduct a cost-benefit analysis to examine if the benefits outweigh the costs. If the analysis determines that the expected benefits outweigh the foreseen costs, we recommend Kentucky install one automated thermal imaging system at a weigh station for an in-depth evaluation of the system's effectiveness before deciding upon further expansion.]]></description>
      <pubDate>Fri, 07 Nov 2025 11:31:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2611095</guid>
    </item>
    <item>
      <title>Sustainability Enhancement of Inclement Weather Dummy Factor Model: A Study of Big Traffic Data in Canada</title>
      <link>https://trid.trb.org/View/2543150</link>
      <description><![CDATA[Transportation agencies in cold regions are tasked with developing traffic models and verifying their accuracy. Few prior studies have examined the spatial transferability of model coefficients across different types of highway segments. This study utilizes traffic data from six weigh-in-motion sites in Alberta, Canada, to develop and test winter traffic models for three vehicle types. The research empirically assesses the spatial transferability of a winter model developed for one site by applying its coefficients to other sites with varying road functionalities within the highway network. The findings indicate that winter traffic models can be transferred to other road segments with differing levels of accuracy. This demonstrates that an appropriate model structure can be selected for each vehicle class based on observed road functionality. Consequently, transportation agencies can use and maintain these developed models without the need for additional traffic monitoring sites.]]></description>
      <pubDate>Thu, 26 Jun 2025 11:42:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2543150</guid>
    </item>
    <item>
      <title>Automated CMV Inspection Demonstrations and Evaluations</title>
      <link>https://trid.trb.org/View/2499201</link>
      <description><![CDATA[This project examined how roadside inspections and other law enforcement interactions could be accomplished on Automated Driving Systems (ADS)-equipped Commercial Motor Vehicles (CMVs). This included research into: (a) how automated CMVs can deliver necessary information to inspectors and (b) how automated CMVs can recognize and respond to inspection locations and directions. These objectives were accomplished by enhancing existing open-source ADS software and demonstrating these enhancements using an ADS-equipped CMV on a test track. This study explored six operational test scenarios designed to represent significant interactions an ADS-equipped CMV may encounter. These scenarios explored data and messaging requirements, preventative maintenance, pre-trip inspection information, interactions with a weigh station, and interactions with law enforcement. Results suggest roadside inspections and interactions with law enforcement can be accomplished on ADS-equipped CMVs. Wireless transmission of a safety data message was demonstrated in real-world testing via cellular communication to a roadside computer and a weigh station bypass provider. Communication of ADS health and safety status data elements within the safety data message was demonstrated as well. Finally, this project demonstrated the maturity of a newly developed law enforcement vehicle light bar detection software plugin as well as compliance with law enforcement commands (pull over, move over).]]></description>
      <pubDate>Tue, 18 Feb 2025 10:45:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2499201</guid>
    </item>
    <item>
      <title>Optimizing network locations of weigh-in-motion stations: A multi-objective approach for enhancing infrastructure management</title>
      <link>https://trid.trb.org/View/2483406</link>
      <description><![CDATA[In the realm of transportation infrastructure, Weigh-in-Motion (WIM) stations are crucial for monitoring impact of overweight trucks and maintaining infrastructure assets such as roadway pavements and bridges. However, current approaches to WIM location problem (WIMLP) on a network of highways and bridges are often region-specific and resource-intensive and lack a multi-objective framework. This study addresses these gaps by proposing a versatile and cost-effective network-based site selection strategy, adaptable to various transportation agency needs. Utilizing an extensive literature review, the framework centers around a comprehensive site-selection framework based on the diverse purposes of WIM data collection. The proposed framework integrates truck traffic composition, infrastructure condition, enforcement needs, and geographical considerations. This approach strategically identifies the optimal sites for WIM installation, maximizing data utility while minimizing resource expenditure. The proposed framework for WIMLP is showcased in New York City, addressing the city’s challenge of managing truck load impacts on its extensive bridge network. Based on the City’s allocation of resources for only ten sites, the research team strategically identified their respective optimal WIM locations across the city’s roadway network and highway bridges. This selection facilitates the assessment of truck load effects, especially from overweight vehicles, on bridge conditions. This approach not only aids in long-term infrastructure monitoring aligned with NYCDOT’s goals but also supports future overweight enforcement efforts. Additionally, the study introduces an analytical framework to enhance the utilization of WIM data in analyzing truck load impacts.]]></description>
      <pubDate>Mon, 27 Jan 2025 15:11:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2483406</guid>
    </item>
    <item>
      <title>Illegal Weigh Station Bypassing</title>
      <link>https://trid.trb.org/View/2408345</link>
      <description><![CDATA[This study was conducted to determine the extent of illegal weigh station bypassing in Kentucky, including the resulting safety and financial implications. Historical data (2017 to 2021) collected by Kentucky State Police–Commercial Vehicle Enforcement, observation data, and a state survey distributed to law enforcement officials across North America were used in tandem to provide evidence that illegal weigh station bypassing is indeed a problem that justifies swift, comprehensive action. Between 2017 and 2021, there were 2,616 charges for illegal weigh station bypassing in Kentucky. Drivers charged with illegal weigh station bypassing were also charged for an average of two additional violations. Site visits to permanent weigh stations along I-75 revealed that illegal weigh station bypassing was a persistent problem, even among preclearance (PrePass and Drivewyze) users. A survey was sent to law enforcement officials across North America to determine whether other jurisdictions were experiencing similar levels of noncompliance, as well as identifying which methods were being used to combat it. With a survey response rate of 56%, and 49% of respondents reporting a recent uptick in illegal weigh station bypasses, a nationwide problem was confirmed. Despite 70% of jurisdictions reporting enforcement efforts to curb illegal weigh station bypassing, it is clear that increased enforcement levels alone will not be sufficient. With safety and financial implications mounting across North America from illegal weigh station bypassing, novel approaches are warranted.]]></description>
      <pubDate>Tue, 30 Jul 2024 09:53:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2408345</guid>
    </item>
    <item>
      <title>Investigation of Illegal Weigh Station Bypassing</title>
      <link>https://trid.trb.org/View/2255699</link>
      <description><![CDATA[This study recommends best practices to curb illegal weigh station bypassing by commercial motor vehicles (CMVs). Analysis of historical data collected by Kentucky State Police – Commercial Vehicle Enforcement (KSP-CVE) for 2017-2021 revealed that CMV drivers were charged with illegally bypassing weigh stations 2,616 times. Drivers were charged with an average of two other violations when cited for illegal bypassing — most often violations related to credentialing, vehicle safety, or driver safety. Site visits to three permanent weigh stations in Kentucky revealed that CMVs regularly bypass weigh stations illegally, including those authorized to use preclearance systems (Drivewyze and PrePass). A survey distributed to law enforcement officials in U.S. and Canadian jurisdictions found that 49% of the responding jurisdictions have seen a recent uptick in illegal bypasses. Most participating jurisdictions (70%) have conducted enforcement details to tamp down illegal bypassing, which indicates it is a widespread problem. Every illegal bypass likely results in jurisdictions missing out on revenues and increases the likelihood of poor safety outcomes. The safety and financial implications of illegal bypasses are substantial enough to warrant swift, comprehensive action to mitigate them.]]></description>
      <pubDate>Fri, 06 Oct 2023 13:40:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2255699</guid>
    </item>
    <item>
      <title>On the Stabilizing Effect of Weigh Stations on Truck Equivalency Factors for Pavement Design</title>
      <link>https://trid.trb.org/View/2187119</link>
      <description><![CDATA[In Costa Rica, weigh stations for trucks and commercial vehicles were reinstated in 2008. Since then, a stabilizing trend in the percentage of heavy vehicles with excess loading was observed. For pavement design purposes, this resulted in reduced variability in truck equivalency factors. These were statistically validated by processing all the weight data collected at different stations located throughout the national road network between 2008 and 2011. Using linear regressions, it was verified that given a constant noncompliance percentage, the truck equivalency factor for C2, C3, and T3-S2 vehicles tended to stabilize at 0.20, 0.66, 1.19, respectively. These results were consistent with additional power regression performed on the data. Higher weight enforcement on the T3-S3 vehicles’ tandem axle would result in a 0.17 decrease in the truck equivalency factor. The findings presented herein should aid countries that have yet to implement weigh stations, considering the benefits of exploring the evolution of truck factors if weigh stations were installed. This weigh station implementation case study exhibits the reality and development of pavement loading over time. Therefore, government authorities should be encouraged to control truck traffic with weigh stations to reduce pavement damage.]]></description>
      <pubDate>Thu, 22 Jun 2023 09:49:08 GMT</pubDate>
      <guid>https://trid.trb.org/View/2187119</guid>
    </item>
    <item>
      <title>Guide for Manual of Instructions for Traffic Surveys 1976</title>
      <link>https://trid.trb.org/View/2122588</link>
      <description><![CDATA[This manual describes in detail the process for inventorying the use of highways. Included in the inventory is the volume, distribution of type, and weight characteristics of the traffic using the highways. This information is needed during the process of planning, designing, and operation of an efficient highway program.]]></description>
      <pubDate>Thu, 23 Mar 2023 16:41:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2122588</guid>
    </item>
    <item>
      <title>Optimizing Commercial Vehicle Enforcement Investments and Activities to Improve Safety and Increase Revenue Collections</title>
      <link>https://trid.trb.org/View/2047370</link>
      <description><![CDATA[The Kentucky Transportation Cabinet (KYTC) owns and maintains 14 fixed weigh stations for commercial vehicle enforcement. The Kentucky State Police (KSP) is responsible for staffing these facilities to conduct enforcement, while KYTC is responsible for constructing and maintaining these facilities. Like many states, Kentucky has experienced a decline of enforcement personnel to operate weigh stations limiting its ability to conduct inspections for safety enforcement and revenue collection. This study analyzes three CMV facilities for their impact on safety enforcement and revenue collection and determines their viability for potential replacement. All three existing weigh stations in Hardin, Fulton, and Henderson counties will be bypassed or removed due to future interstate and interchange construction plans. These weigh stations were assessed for the amount of revenue collected against operating expenses, the ratio of citations issued per violations, and the impact each weigh station had on overall safety. Researchers developed guidelines decision makers and stakeholders can use to determine the outcome for each of the three weigh stations: permanently close, replace with a new facility, or convert to remote monitoring. This guidance can be applied beyond the three facilities in the study, to help make future decisions on weigh stations across Kentucky.]]></description>
      <pubDate>Wed, 30 Nov 2022 10:57:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2047370</guid>
    </item>
    <item>
      <title>Development of a Virtual Weigh Station (VWS) for Monitoring Over-Weight Vehicles on Secondary Routes</title>
      <link>https://trid.trb.org/View/1891278</link>
      <description><![CDATA[The problem of weigh station avoidance by heavy trucks exists throughout the United States. In Arkansas, alternate highways exist near every weigh station and are being used by some trucks to bypass without inspections. Although these trucks can be intercepted by roving Arkansas Highway Police (AHP) units, the ability to detect where this problem may exist is not currently available. Therefore, the interception of heavy truck by-passers is, at best, a random occurrence accomplished by trial and error surveillance of AHP units. Research in both Kentucky and Virginia has confirmed the existence of heavy truck avoidance of weigh stations. The exact reasons for this have not been conclusively determined. It has been determined that a larger proportion of these trucks are more overweight than those encountered with the normal truck traffic at the weigh stations. Consequently, it follows that these trucks, which are avoiding the weigh stations, generate a proportionately larger amount of pavement and bridge wear while carrying illegal loads and avoiding the payment of appropriate highway tax. In order for the AHP to address this problem adequately, cost-effective, non-intrusive methods and techniques are needed to effectively monitor heavy truck traffic on close bypass routes to weigh stations.]]></description>
      <pubDate>Mon, 06 Dec 2021 17:24:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/1891278</guid>
    </item>
    <item>
      <title>Investigation of Illegal Weigh Station Bypassing</title>
      <link>https://trid.trb.org/View/1877380</link>
      <description><![CDATA[Kentucky offers motor carriers the option to bypass weigh stations by using mainline screening services such as PrePass or Drivewyze. Before they are approved to use bypass services, Kentucky screens motor carriers; they are screened again by those services immediately prior to the weigh station. Some motor carriers have been observed illegally bypassing weigh stations by (1) shadowing a PrePass or Drivewyze truck with bypass clearance as it passes the station (i.e., ghosting), (2) bypassing on the mainline despite having no authority to do so, or (3) pulling into the weigh station only to disregard weigh station signage when directed to stop and park for inspection. This problem has been exacerbated by dramatic reductions in the number of Commercial Vehicle Enforcement (CVE) personnel and the need to move officers away from the weigh stations to focus on traffic enforcement and roadside inspections. Inspectors staffing weigh stations lack the authority to chase down vehicles whose drivers do not comply with weigh station signage.]]></description>
      <pubDate>Wed, 08 Sep 2021 11:04:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/1877380</guid>
    </item>
    <item>
      <title>Vision-Based Overload Detection System for Land Transportation</title>
      <link>https://trid.trb.org/View/1756861</link>
      <description><![CDATA[Overloaded trucks pose a threat to highway traffic, increasing the rate and severity of accidents, while damaging road infrastructure. Enabling an efficient overload detection method at existing weighing stations would facilitate regulatory compliance. This paper presents a real-time, accurate truck overload detection system that leverages existing surveillance cameras installed at weighing stations. To achieve this goal, the authors applied computer vision algorithms on video from an indoor camera monitoring a digital display and on another outdoor camera monitoring the station’s weighing bridge. The truck’s actual weight is obtained by reading the numeric digit display on images from the indoor camera, while the truck’s maximum load capacity is estimated by recognizing the its wheel layout using the video from the outdoor camera. Through evaluation using video data from a weighing station, the optical digit recognition algorithm achieves an accuracy of 99.0%, while the load capacity estimation algorithm achieves an accuracy of 93.18%.]]></description>
      <pubDate>Fri, 26 Mar 2021 17:47:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/1756861</guid>
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