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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=PHNlYXJjaD48cGFyYW1zPjxwYXJhbSBuYW1lPSJkYXRlaW4iIHZhbHVlPSJhbGwiIC8+PHBhcmFtIG5hbWU9InN1YmplY3Rsb2dpYyIgdmFsdWU9Im9yIiAvPjxwYXJhbSBuYW1lPSJ0ZXJtc2xvZ2ljIiB2YWx1ZT0ib3IiIC8+PHBhcmFtIG5hbWU9ImxvY2F0aW9uIiB2YWx1ZT0iMCIgLz48L3BhcmFtcz48ZmlsdGVycz48ZmlsdGVyIGZpZWxkPSJpbmRleHRlcm1zIiB2YWx1ZT0iJnF1b3Q7TW90b3JjeWNsZSBoZWxtZXRzJnF1b3Q7IiBvcmlnaW5hbF92YWx1ZT0iJnF1b3Q7TW90b3JjeWNsZSBoZWxtZXRzJnF1b3Q7IiAvPjwvZmlsdGVycz48cmFuZ2VzIC8+PHNvcnRzPjxzb3J0IGZpZWxkPSJwdWJsaXNoZWQiIG9yZGVyPSJkZXNjIiAvPjwvc29ydHM+PHBlcnNpc3RzPjxwZXJzaXN0IG5hbWU9InJhbmdldHlwZSIgdmFsdWU9InB1Ymxpc2hlZGRhdGUiIC8+PC9wZXJzaXN0cz48L3NlYXJjaD4=" rel="self" type="application/rss+xml" />
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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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>Impact Attenuation Assessment of Several Lightweight Materials Subjected to a Motorcycle Helmet Free-Fall Drop Test</title>
      <link>https://trid.trb.org/View/2581403</link>
      <description><![CDATA[The paper focuses on the analysis of the impact behavior of some light materials used either for shock absorption inside protective helmets or as support materials. Five types of structures were analyzed, subjected to three different impact speeds. A dummy head used in accidentology tests was mounted on the impact head, and in the second stage a motorcycle helmet was fixed on the dummy head. The results revealed that tested materials can lead to an improvement in impact mitigation performance. Thus, it was proven that the use of the protective helmet leads to a decrease in acceleration and impact force by: 48.8% in the case of impact at a speed of 3.13 m/s; 25.1% in the case of the impact at the speed of 4.42 m/s and 31.9% in the case of the impact at the speed of 5.42 m/s.]]></description>
      <pubDate>Mon, 13 Jul 2026 10:46:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2581403</guid>
    </item>
    <item>
      <title>Evaluation of Motorcycle Helmet Test Procedures</title>
      <link>https://trid.trb.org/View/2691562</link>
      <description><![CDATA[FMVSS No. 218, Motorcycle helmets, specifies minimum performance requirements for helmets designed for use  by motorcyclists and other motor vehicle users. FMVSS No. 218 includes three performance test types that have  remained largely unchanged since it was first published in 1973: an impact attenuation test, a penetration test, and  a retention system test. In 2013 NHTSA initiated a helmet testing research program with compliance test labs.  Based upon this testing, adjustments were made to the test procedures and were evaluated in this study. In  continuation of NHTSA’s motorcycle helmet research, the testing described in this report aimed to achieve the  following: (1) assess the feasibility of conducting modified FMVSS No. 218 tests and other performance tests,  and refining test procedures as necessary; and (2) evaluate the repeatability of each of the modified test  procedures assessed.  Six helmet models were tested in six test types. Two test types were based on tests included in FMVSS No. 218,  while four test types were based on tests included in international standards. Four models were used for the  impact attenuation, retention system, and chin bar tests. Five helmets of each helmet model were used for these  test types. The other two helmet models were used for the positional stability, face shield, and rigid projection  tests. Fifteen helmets of each helmet model were used for these test types.  Overall, the results from the six helmet models tested showed that conducting these tests was feasible and the results for all test procedures were generally repeatable. Although the results for a small number of individual  helmet models showed elevated variation, that variation was not substantial enough to prevent the tests from  differentiating the performance of the tested helmets.]]></description>
      <pubDate>Mon, 13 Apr 2026 08:56:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2691562</guid>
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    <item>
      <title>Determinants of Personal Protective Gear Use and Adherence to Safety Standards among Motorcyclists: A Case Study in Qatar</title>
      <link>https://trid.trb.org/View/2646858</link>
      <description><![CDATA[The use of safety gear by motorcyclists is critical in reducing injury severity in the event of a crash. This paper examines the influence of rider characteristics on their selection of safety gear and adherence to safety gear standards. This study employed discrete choice models to investigate factors influencing the use of standard safety gear by motorcyclists. Moreover, variations in risky riding characteristics and non-mandated safety gear usage rates based on rider characteristics have been explored. The data was collected using an online survey questionnaire in Qatar from 439 riders. Results show that only half of the riders used standard safety gear. Despite the relatively high rate of helmet use, the overall uptake of non-mandated protective gear remains low. It is observed that the age group of 23–30 years is the low-risk group compared to other age groups, and the highly educated riders tend to be more risk-taking. Riders’ perceived sense of safety and past crash experience significantly interact; those who reported feeling safe while riding, despite having a history of crashes, were more likely to wear standard safety equipment. The study suggests that interventions based on immersive experiences, such as simulator training and accounts from injured riders, could play a key role in shifting how riders perceive risk and safety. Additionally, locally tailored awareness campaigns are necessary to improve both the understanding and use of standard safety gear among motorcyclists in Qatar.]]></description>
      <pubDate>Mon, 23 Mar 2026 09:45:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2646858</guid>
    </item>
    <item>
      <title>Numerical simulation and experimental validation of human head thermoregulation under motorbike helmet</title>
      <link>https://trid.trb.org/View/2559576</link>
      <description><![CDATA[Headgear including helmets are essential and law-enforced in many countries. However, one of the most main reasons drivers give for not wearing helmets is the discomfort and excessive heat that helmets create. More comfortable helmets can potentially increase helmet use among population, thus play a major role in people safety. In this study, a thermoregulation model of the human helmeted head was created using Finite Element Analysis (FEM) and based on an anatomically correct medical image-based CT-scan model. The model investigated three cases with different wind speeds namely; 1km/h, 20km/h, and 50km/h. In addition, the combined FEM Head-helmet model results is verified by an experimental trail. The compared results shown the ability of the model to predict the head temperature profile and results were in good agreement with experiment. The established model is to predict the thermal distribution of the head parts under helmet conditions. Results reflect the thermoregulatory responses of the rider parts, thus providing grounds for suggestions and recommendations for the helmet design and processing.]]></description>
      <pubDate>Mon, 09 Jun 2025 09:33:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2559576</guid>
    </item>
    <item>
      <title>Motorcycle Helmet Use in 2023 – Overall Results</title>
      <link>https://trid.trb.org/View/2448857</link>
      <description><![CDATA[Use of DOT-compliant motorcycle helmets was 73.8 percent in 2023, not statistically different at the 0.05 level from 66.5 percent in 2022. The 2023 estimate is the highest ever recorded. The 2023 data collection occurred during the usual timeframe of early June, immediately following the Click It or Ticket campaign. There were 945 motorcyclists observed in the 2023 survey, a 1-percent increase from 934 motorcyclists in 2022. Other significant changes in helmet use included: DOT-compliant helmet use among motorcyclists traveling in light traffic increased significantly from 35.5 percent in 2022 to 66.0 percent in 2023; use of noncompliant motorcycle helmets among motorcyclists traveling in slow traffic decreased significantly from 16.9 percent in 2022 to 7.7 percent in 2023; and use of noncompliant motorcycle helmets among motorcyclists traveling in light traffic decreased significantly from 21.1 percent in 2022 to 7.8 percent in 2023.]]></description>
      <pubDate>Thu, 07 Nov 2024 11:30:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2448857</guid>
    </item>
    <item>
      <title>Motorcyle Helmet Use in 2023 – Overall Results</title>
      <link>https://trid.trb.org/View/2437360</link>
      <description><![CDATA[Use of DOT-compliant motorcycle helmets was 73.8 percent in 2023, not statistically different at the 0.05 level from 66.5 percent in 2022. The 2023 estimate is the highest ever recorded. The 2023 data collection occurred during the usual timeframe of early June, immediately following the Click It or Ticket campaign. There were 945 motorcyclists observed in the 2023 survey, a 1-percent increase from 934 motorcyclists in 2022. DOT-compliant helmet use among motorcyclists traveling in light traffic increased significantly from 35.5 percent in 2022 to 66.0 percent in 2023. Use of noncompliant motorcycle helmets among motorcyclists traveling in slow traffic decreased significantly from 16.9 percent in 2022 to 7.7 percent in 2023. Use of noncompliant motorcycle helmets among motorcyclists traveling in light traffic decreased significantly from 21.1 percent in 2022 to 7.8 percent in 2023.]]></description>
      <pubDate>Thu, 10 Oct 2024 09:23:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2437360</guid>
    </item>
    <item>
      <title>Role of ABS and EPS foams in determining the performance of motorcyclist helmet during impact loading</title>
      <link>https://trid.trb.org/View/2404288</link>
      <description><![CDATA[This study develops a Finite Element Method (FEM) model to evaluate motorcyclist helmet performance, with a focus on stress distribution in the temporal bone region and its impact on brain protection. The model includes an ISI 4151 rated helmet coupled with equivalent head foam mass. Results show that Acrylonitrile Butadiene Styrene (ABS) shells reduce cortical bone impact by 97% through lateral load distribution, while Expanded Polystyrene (EPS) foam absorbs and protects the head. The study also incorporates lateral falls on flat and hemispherical anvils to assess helmet performance in real-life scenarios. These findings contribute to improved helmet design and safety for motorcyclists, enhancing overall rider protection. The analysis highlights the importance of ABS shells in minimising impact on cortical bones and the role of EPS foam in absorbing and mitigating head injury risks. The study’s insights inform the development of advanced helmet materials and designs for enhanced safety in motorcycle riding.]]></description>
      <pubDate>Tue, 06 Aug 2024 10:35:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2404288</guid>
    </item>
    <item>
      <title>Lightweight helmet target detection algorithm combined with Effici-Bi-Level Routing Attention</title>
      <link>https://trid.trb.org/View/2387422</link>
      <description><![CDATA[Wearing helmets is essential in two-wheeler traffic to reduce the incidence of injuries caused by accidents. The authors present FB-YOLOv7, an improved detection network based on the YOLOv7-tiny model. The objective of this network is to tackle the problems of both missed detection and false detection that result from the difficulties in identifying small targets and the constraints in equipment performance during helmet detection. By applying an enhanced Bi-Level Routing Attention, the network can improve its capacity to extract global characteristics and reduce information distortion. Furthermore, the authors deploy the AFPN framework and effectively resolve information conflict using asymptotic adaptive feature fusion technology. Incorporating the EfficiCIoU loss significantly improves the prediction box's accuracy. Experimental trials done on specific datasets reveal that FB-YOLOv7 attains an accuracy of 87.2% and 94.6% on the mean average precision (mAP@.5). Additionally, it maintains a high level of efficiency with frame rates of 129 and 126 frames per second (FPS). FB-YOLOv7 surpasses the other six widely-used detection networks in terms of detection accuracy, network implementation requirements, sensitivity in detecting small targets, and potential for practical applications.]]></description>
      <pubDate>Wed, 12 Jun 2024 16:04:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/2387422</guid>
    </item>
    <item>
      <title>Development of Discrete Size Measurement Methodologies for Motorcycle Helmets</title>
      <link>https://trid.trb.org/View/2288335</link>
      <description><![CDATA[FMVSS No. 218 defines the discrete size of a motorcycle helmet and requires the discrete size to be listed on the label. However, it does not specify where this measurement is taken within the helmet, and it does not provide a standard procedure for measuring this discrete size nor a tool to measure the size. In addition to the discrete size, there is no standard procedure for determining the helmet positioning index (HPI) used to align the helmet on the headform for measurements and testing. Thus, the objective of this research was to develop procedures to determine HPI and to measure discrete size of motorcycle helmets. NHTSA identified a few areas to focus efforts on while developing an objective, repeatable, and non-destructive method for measuring the discrete size of a motorcycle helmet. These areas were defining a location where the discrete size is to be taken, developing a tool to take the measurements, and incorporating use of alternative headforms (ASTM International F2220 headforms). Four methods for measuring discrete size and one method for determining the HPI were developed and evaluated in this study. NHTSA’s Vehicle Research and Test Center (VRTC) evaluated a procedure for determining the HPI and compared results to the HPIs provided by the helmet manufacturer. The four methods to measure discrete size were to measure internal circumference with a handheld scissor tool, measure internal circumference with a modified scissor tool, and measure internal lateral and longitudinal distances with and without compression of the comfort liner. The internal lateral and longitudinal measurement methods did not give clear or consistent results and therefore were not continued with as part of the full study. Measurement differences were small between modified and handheld scissor tool methods; the largest difference was 1.5 cm between the two methods. A repeatability analysis for both tools used to measure discrete size was completed; the maximum percentage of coefficient of variation for the handheld scissor tool was 0.9 percent and for the modified scissor tool was 1.4 percent.]]></description>
      <pubDate>Mon, 13 Nov 2023 16:56:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2288335</guid>
    </item>
    <item>
      <title>Strategies for Reducing Motorcyclist Injuries: Engaging Stakeholders to Apply Evidence-Based Countermeasures that Work</title>
      <link>https://trid.trb.org/View/2270237</link>
      <description><![CDATA[One of the recent issues in transportation safety is the rise in fatalities and severe injuries among motorcyclists. Since motorcyclists are far more vulnerable than enclosed vehicle users on the road, they are substantially more likely to get injured in a crash. While evidence-based countermeasures are available, this research aims to shorten the implementation cycle in the translation of research into practice at the state level. Especially with insights and information from Collaborative Sciences Center for Road Safety (CSCRS)-sponsored analysis of Motorcycle Crash Causation (MCCS) study data, this project aims to accelerate the research to deployment cycle. For this, statewide motorcycle safety plans provide a critical intervention opportunity. Such safety plans often identify risk factors and consider countermeasures. To identify risk factors, recent motorcycle crash data in Tennessee was analyzed. Then motorcycle safety practices across the United States and other countries were reviewed. Promising and new countermeasures such as enhancing rider conspicuity and motorist awareness, new personal protective gear, avoiding impaired driving, and rider education were matched with risk factors. Based on recent motorcycle crash data (N=14,677) in Tennessee, 73.4% resulted in rider injuries, with 5.1% causing a fatality. Statistical analysis reveals that improper use of a Department of Transportation (DOT)-compliant helmet is associated with severer injuries, compared with properly wearing a DOT-compliant helmet. Other injury risk factors were identified along with high-frequency motorcycle crash hotspots including the Great Smoky Mountains National Park, with tight curves and elevation changes. To further support planning efforts, a comprehensive review of motorcycle safety practices suggests that Tennessee can invest in efforts to carry out more robust media campaigns on motorcycle safety and increase communication with motorcyclists via online and printed materials. The findings from this project are a valuable reference for expeditious and timely translation of research into practice with the newest evidence-based countermeasures delivering innovative solutions. Based on input from practitioners, developing a Motorcycle Safety Clearinghouse can improve technology transfer, increase two-way information sharing between researchers and practitioners, and serve as a means to get research into practice much more quickly.]]></description>
      <pubDate>Mon, 06 Nov 2023 08:39:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2270237</guid>
    </item>
    <item>
      <title>Assessing the Fit and Comfort of Motorcycle Safety Gear</title>
      <link>https://trid.trb.org/View/2256362</link>
      <description><![CDATA[This project will examine the fit and comfort of motorcycle safety gear from the perspective of the motorcyclist. We will seek the participation of motorcyclists to learn about the gear they use, assess how well the gear fits, and ask about the comfort and usability of gear (e.g., does a jacket constrain the ability to turn). Additionally, we will look at the differences in fit and comfort by gear type and rider characteristics (age, sex, race, ethnicity). The project will also ask riders about their reasons for not using gear and their beliefs about the protective benefit of gear.]]></description>
      <pubDate>Thu, 28 Sep 2023 11:38:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/2256362</guid>
    </item>
    <item>
      <title>Motorcycle Helmet Use in 2022—Overall Results</title>
      <link>https://trid.trb.org/View/2239743</link>
      <description><![CDATA[Use of DOT-compliant motorcycle helmets was 66.5 percent in 2022, not statistically different at the 0.05 level from 64.9 percent in 2021. This result is from the National Occupant Protection Use Survey (NOPUS), the only survey that provides nationwide, probability-based, observed data on motorcycle helmet use in the United States. The 2022 data collection occurred during the usual time-frame of early June, immediately following the Click It or Ticket campaign. There were 934 motorcyclists observed in the 2022 survey, a 7-percent increase from 871 motorcyclists in 2021. Helmet use among motorcyclists traveling in light traffic decreased significantly from 59 percent in 2021 to 35.5 percent in 2022. Use of noncompliant motorcycle helmets among motorcyclists traveling on surface streets increased significantly from 6.1 percent in 2021 to 10.9 percent in 2022. Use of noncompliant motorcycle helmets among motorcyclists traveling in slow traffic increased significantly from 5.9 percent in 2021 to 16.9 percent in 2022. Use of noncompliant motorcycle helmets among motorcyclists traveling in light traffic increased significantly from 5.3 percent in 2021 to 21.1 percent in 2022. Use of noncompliant motorcycle helmets among motorcyclists traveling in the northeast increased significantly from 6.5 percent in 2021 to 15.8 percent in 2022, while use of noncompliant motorcycle helmets among motorcyclists traveling in the west decreased significantly from 3.6 percent in 2021 to 2.4 percent in 2022. Use of noncompliant motorcycle helmets among motorcyclists traveling in objectively characterized urban areas increased significantly from 5.2 percent in 2021 to 11.5 percent in 2022.]]></description>
      <pubDate>Mon, 11 Sep 2023 11:42:29 GMT</pubDate>
      <guid>https://trid.trb.org/View/2239743</guid>
    </item>
    <item>
      <title>Analysis head injuries of Vietnamese motorcyclist without a helmet in car to motorbike frontal impact using a computer model</title>
      <link>https://trid.trb.org/View/2189303</link>
      <description><![CDATA[Nowadays, with the increasing demand for travel, the number of people using motorbikes is increasing, especially in Vietnam. People tend to face more injury risks when they are in traffic, such as vulnerable road users (VRU) – pedestrians, cyclists, and motorcyclists. Therefore, the objective of this study is to assess how car crashes influence Vietnamese motorcyclists' bodies, in particular their heads, because they are the most vulnerable parts of their bodies. The result of this study is to let people know what they’re facing in case they are hit by a car. In addition, this research analyzes the injury to the motorcyclist's head when being hit by different configurations of the car. Due to the lack of facilities, car-to-motorcyclist frontal impact simulation has become the best way to resolve this problem. The impact conditions, which were obtained from real motorcyclist accidents in Vietnam, including the speed of vehicle and motorcycle, and impact angle, were defined as initial loading conditions in a simulation of the head striking the windscreen by using a finite element Vietnamese dummy model. Logistic regression models were developed to study brain injury risk with respect to injury-related variables: the head linear acceleration and head injury criterion (HIC) value. In this paper, the deformation of the motorbike structure model was neglected, so the material has been selected as a rigid form. The knowledge from this research could be a prerequisite for developing guidelines to improve motorcyclist safety in Vietnam.]]></description>
      <pubDate>Mon, 12 Jun 2023 09:13:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2189303</guid>
    </item>
    <item>
      <title>The impact of perceived safety, weather condition and convenience on motorcycle helmet use: The mediating role of traffic law enforcement and road safety education</title>
      <link>https://trid.trb.org/View/2142154</link>
      <description><![CDATA[Despite numerous studies on motorcycle safety, especially the compliance of helmet use laws in both developed and developing countries across the globe, little is known about the mediating role of traffic law enforcement and road safety education specifically on the relationship between helmet use influencing factors and helmet usage in general. The aim of this study was to examine the mediating role of traffic law enforcement and road safety education on the relationship between helmet usage influencing factors and motorcycle helmet usage. A total of 358 respondents from a university community that uses a motorcycle on daily bases to and from the community and for other important trip purposes completed a self-reported questionnaire in the Upper West Region of Ghana where motorcycles are predominantly used as a transportation mode. To test for the various hypotheses of this study, the authors developed a hypothesized single multiple mediated structural equation model and several sub-mediated models using AMOS 26.0. The results showed that the perceived safety of the helmet, weather conditions, and convenience of helmet use have positive significant impacts on helmet use. The study also found a full mediation role of the combined effect of traffic law enforcement and road safety education on the relationship of helmet use influencing factors investigated and helmet use. The study concludes that new traffic law enforcement and road safety education strategies need to be adopted to help improve upon the low prevalence of helmet use within the study area.]]></description>
      <pubDate>Thu, 18 May 2023 17:08:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2142154</guid>
    </item>
    <item>
      <title>Full-face motorcycle helmets to reduce injury and death: A systematic review, meta-analysis, and practice management guideline from the Eastern Association for the Surgery of Trauma</title>
      <link>https://trid.trb.org/View/2071546</link>
      <description><![CDATA[While motorcycle helmets reduce mortality and morbidity, no guidelines specify which is safest. The authors sought to determine if full-face helmets reduce injury and death. The authors searched for studies without exclusion based on: age, language, date, or randomization. Case reports, professional riders, and studies without original data were excluded. Pooled results were reported as OR (95% CI). Risk of bias and certainty was assessed. (PROSPERO #CRD42021226929). Of 4431 studies identified, 3074 were duplicates, leaving 1357 that were screened. Eighty-one full texts were assessed for eligibility, with 37 studies (n = 37,233) eventually included. Full-face helmets reduced traumatic brain injury (OR 0.40 [0.23-0.70]); injury severity for the head and neck (Abbreviated Injury Scale [AIS] mean difference -0.64 [-1.10 to -0.18]) and face (AIS mean difference -0.49 [-0.71 to -0.27]); and facial fracture (OR 0.26 [0.15-0.46]). Full-face motorcycle helmets are conditionally recommended to reduce traumatic brain injury, facial fractures, and injury severity.]]></description>
      <pubDate>Tue, 20 Dec 2022 09:10:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2071546</guid>
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