<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
    <description></description>
    <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>
    </image>
    <item>
      <title>Interaction of road, traffic and environment in the operational design domain of lane support systems: Hybrid factorial–observational design and causal analysis</title>
      <link>https://trid.trb.org/View/2736848</link>
      <description><![CDATA[The Operational Design Domain (ODD) defines the conditions under which automated driving and driver-assistance systems are expected to operate. This study evaluates the ODD of a camera-based Lane Support System (LSS) using direct Mobileye 6.0 lane-detection quality outputs. A large-scale hybrid factorial–observational field design covered 6 different Light × Weather combinations across 9,351 road sections on two-lane rural roads with wide variability in lane-marking retroreflectivity (RL) and road horizontal alignment and cross section characteristics. Statistical and machine-learning classification models were calibrated and compared to analyze the relationships between lane-marking quality and environmental, road, and traffic features. An AutoML-LightGBM pipeline with SMOTE-based class-imbalance treatment achieved the best accuracy of 0.81. SHAP analysis identified low RL, rain, night conditions, narrow lanes, and high curvature as contributors to critical detection conditions. Because standard ML is optimized for prediction rather than causal inference, Double Machine Learning was added to estimate adjusted effects from observational data. Higher RL, higher speed, and wider lanes were associated with better expected Mobileye quality scores, whereas rain, night conditions, and higher curvature were associated with lower detection quality. SHAP dependence and conditional SHAP analyses supported the identification of maintenance-mitigable infrastructure constraints and harder environmental/geometric ODD limits. One practical result is that RL transitions from low-quality detection mainly occur within 120–150 mcd/(m2·lx) across the majority of environmental and physical conditions, although this transition is less evident under sharp curvature or rain.]]></description>
      <pubDate>Thu, 13 Aug 2026 17:03:26 GMT</pubDate>
      <guid>https://trid.trb.org/View/2736848</guid>
    </item>
    <item>
      <title>Safety Evaluation of Sinusoidal Centerline Rumble Strips</title>
      <link>https://trid.trb.org/View/2742164</link>
      <description><![CDATA[The Montana Department of Transportation installed nearly 600 miles of sinusoidal centerline rumble strips (SCLRS) in 2021. These were mostly installed on high-speed, two-lane rural highways, in the Kalispell Division and Missoula area. The sinusoidal pattern produces lower exterior noise levels than conventional centerline rumble strips, but the safety effects of the pattern have not been quantified. This study performed an observational before-after analysis of the SCLRS installation on two-lane rural highways using the Empirical Bayes (EB) methodology. Crash modification factors (CMFs) for a variety of crash types were less than 1.0, indicating that SCLRS were associated with a reduction in crash frequency. The CMF associated with total target crashes—defined as opposite direction collisions—was 0.711 while the CMF associated with fatal plus injury target crashes was 0.624. The only CMF that exceeded 1.0 was for the single-vehicle run-off-the-road crash type; however, this result was not statistically significant. This study also compared the safety performance of the SCLRS to that of conventional centerline rumble strips in Montana. Because the installation dates of the conventional pattern were unknown, a causal inference framework was used for evaluation. The results indicate that the CMFs for the conventional and sinusoidal patterns have confidence intervals that overlap, suggesting similar safety performance associated with the two patterns. An economic evaluation found that both centerline rumble strips patterns have a benefit-cost ratio exceeding 1.0.]]></description>
      <pubDate>Tue, 04 Aug 2026 09:18:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/2742164</guid>
    </item>
    <item>
      <title>A Bayesian approach to planning support on two-lane rural roads for automated vehicles: The role of geometric design in disengagement events</title>
      <link>https://trid.trb.org/View/2704106</link>
      <description><![CDATA[This paper presents an on-road study examining the interaction between Level 2 automated vehicles (AVs) and the geometric features of two-lane rural roads. These roads constitute the largest percentage of the road network in most countries. Their complex geometric features and lack of design consistency present a significant challenge for the operation of automated vehicles (AVs). Although AV systems aim to reduce driver workload and improve road safety, their performance remains limited on these roads, often resulting in automated system disengagements that require driver intervention. Such disengagements highlight emerging challenges for road administrations regarding road readiness and the safe integration of AVs into existing infrastructure.Based on an on-road study using two instrumented AVs, this study investigates how geometric features of Homogeneous Road Segments (HRS), including Curvature Change Rate (CCRHRS), average radius, tangent length, and average parameter of vertical curves, affect driving system engagement rates. A Bayesian approach was used to quantify the relationship between road geometry indices and AV disengagements. The findings reveal that the primary factor affecting engagement status is CCRHRS, showing that higher values of CCRHRS (>400 gon/km) are associated with AV engagement dropping below 25%, highlighting a direct impact of geometric complexity on AV reliability. The other geometric indices have a moderate positive effect. The findings underscore that road geometry significantly affects AV reliability.These findings have significant implications for infrastructure planning and policy. By identifying geometric thresholds that compromise AV functionality, this research supports the definition of Operational Road Sections (ORS) aligned with Operational Design Domains (ODD). The proposed model offers a practical tool for road administrations to assess road suitability for AV deployment, inform upgrading priorities, and establish design guidelines that facilitate the safe integration of AV technologies into existing rural networks. As automation advances, aligning infrastructure design with AV capabilities becomes essential for equitable and effective transport policy.]]></description>
      <pubDate>Mon, 03 Aug 2026 09:10:14 GMT</pubDate>
      <guid>https://trid.trb.org/View/2704106</guid>
    </item>
    <item>
      <title>Operating Speed Prediction Model for Horizontal Curves of Two-Lane Rural Highways</title>
      <link>https://trid.trb.org/View/2671509</link>
      <description><![CDATA[The research presents a study of operating speed prediction model designed to increase the efficiency and safety of transportation systems. Operating speed is defined as “85th percentile of the distribution of observed speeds used to measure the operating speed associated with a particular location or geometric feature.” Operating speed is an important parameter influencing traffic flow and overall system performance. An operating speed prediction (OSP) model is a tool used in road safety and transportation engineering. The model uses real-time data from various sources and road infrastructure, to find dynamic factors affecting operating speed. Variables, such as spot speed and spatial coordinates, of the vehicles were analyzed. Models were developed to predict the operating speed using spot speed data. R software and Microsoft excel are employed to analyze the complex relationships among multiple variables and predict future operating speeds. The speed data is collected using Laser camera, and geometrics of the road is obtained using Google Earth pro and civil 3D. Data of the model is conducted over a stretch of 10 km on Padubidri to Karkala (SH-01) in Dakshina Kannada district of Karnataka state for 10 curves at these locations. Integrating prediction model into transportation management systems has the capacity to enhance traffic control, and ultimately increase the overall efficiency of transportation networks. The results shows the model's accuracy and robustness in predicting operating speeds for two wheeler and car. This research is helpful for the ongoing efforts to develop transportation systems. This offers a practical tool for planners and engineers to make informed decisions that promote smoother traffic flow, reduce congestion, and enhance road safety. The proposed operating speed prediction model serves as a valuable asset in the quest for sustainable urban mobility solutions.]]></description>
      <pubDate>Mon, 27 Jul 2026 11:16:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/2671509</guid>
    </item>
    <item>
      <title>Presenting Spatial Data Mining Based on a Stage-Interpretable Multilayer Deep Learning Approach to Analyze the Factors Affecting the Crash Frequency of Light Vehicles in Rural Freeways</title>
      <link>https://trid.trb.org/View/2727485</link>
      <description><![CDATA[Some studies show that most light vehicle crashes occur on rural freeways. Crash frequency analysis presents significant challenges due to the complexity of large-scale datasets, hidden intervariable relationships, limited interpretability, and the influence of segmentation methods used. The present study aims to provide an innovative stage-interpretable multilayer perceptron (SI-MLP) method based on deep learning for quantitative and spatial analysis of the effect of geometric factors, weather conditions, and traffic parameters on the crash frequency by presenting a combined dynamic–static segmentation approach in rural freeways. The stage-interpretable method makes the interpretability of deep learning algorithm results possible by stepwise feature omission and assessing its impact on model accuracy. To this aim, significant variables were selected using a decision tree algorithm in conjunction with the Pearson correlation test. The Poisson regression model was utilized to compare the results with those of the proposed SI-MLP method due to the discrete nature of the data and the ability of such an algorithm to model the crash frequency. TabNet was also considered as a benchmark to assess the proposed SI-MLP, since it supports both crash frequency classification (enabling direct accuracy comparison with the MLP-based formulation) and regression-based crash frequency estimation as a numerical outcome. The results revealed that the proposed SI-MLP outperforms the Poisson regression model and the TabNet benchmark in identifying influential crash factors, owing to its ability to capture complex patterns and relationships and to extract high-level features from crash data enriched with geometric and weather information. In the three-class setting (low, medium, and high crash frequency levels), the SI-MLP achieved an overall accuracy of 0.81 and a Macro-F1 of 0.81. Based on the results, the vehicle type and color, license type, temperature, driver’s age, lighting conditions, and front collision with a fixed object were identified as variables affecting the crash frequency. In the next step, the effective variables identified by the proposed method were analyzed using thematic kernel density maps to model the clustering patterns and spatial autocorrelation of the crash frequency, with an emphasis on the most effective factors. Identifying key contributing factors within high-crash segments using the proposed approach allows for the formulation of targeted safety priorities and supports the deployment of proactive countermeasures in segments with the highest risk.]]></description>
      <pubDate>Mon, 27 Jul 2026 09:46:49 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727485</guid>
    </item>
    <item>
      <title>Stage Passing Framework under First Tier Quality Monitoring in PMGSY</title>
      <link>https://trid.trb.org/View/2727682</link>
      <description><![CDATA[The Stage Passing Framework has been introduced under the Pradhan Mantri Gram Sadak Yojana (PMGSY) to strengthen first-tier quality assurance in rural roads construction by linking inspection and certification with predefined stages of execution. The framework replaces earlier ad-hoc and paper-based inspection practices with a digitised, progress-aligned system, wherein stage-wise inspections are recorded through Online Management, Monitoring, and Accounting System (OMMAS) and the Quality First App and certified by the Project Implementation Unit (PIU) Head based on geotagged evidence and e-test reports. By embedding quality checks within the construction workflow, the framework seeks to restore accountability at the field-execution level, enhance transparency and traceability of inspection records, and reduce excessive reliance on 2nd and 3rd monitoring tiers. This paper outlines the rationale, institutional design, and operational role of the Stage Passing Framework and highlights its relevance in promoting preventive, concurrent, and evidence-based quality assurance in PMGSY works.]]></description>
      <pubDate>Tue, 21 Jul 2026 09:49:16 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727682</guid>
    </item>
    <item>
      <title>SPR-5132: Implementation of Proven CV Applications on the Local System LRS</title>
      <link>https://trid.trb.org/View/2727695</link>
      <description><![CDATA[Adapting Indiana Department of Transportation (INDOT) connected vehicle safety and mobility metrics onto the local road network will provide a more uniform mechanism for identifying and assessing the anticipated benefits of projects on the local road system.
]]></description>
      <pubDate>Wed, 15 Jul 2026 11:40:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2727695</guid>
    </item>
    <item>
      <title>Assessing the impact of road lighting on reducing severe nighttime crashes: A case-control study on rural roads in Khorasan Razavi Province, Iran</title>
      <link>https://trid.trb.org/View/2721783</link>
      <description><![CDATA[The disproportionate share of nighttime road crashes, despite lower traffic volumes, highlights the need for effective safety measures. Road lighting is a proven countermeasure, yet its high cost and long implementation timelines require rigorous evaluation. This study applies the case–control method, an epidemiological approach suited to rare events, to estimate the impact of road lighting on severe nighttime crashes on rural roads in Iran. Three case-control approaches—simple, stratified, and matched—produce Crash Modification Factors (CMFs) of 0.39, 0.40, and 0.53, respectively, indicating substantial crash reductions. The reliability of the estimates is assessed using the star quality rating approach, achieving a 4-star rating out of 5 and indicating relatively high confidence. By providing multiple, reliable CMF estimates, the study supports evidence-based decision making, helping transportation agencies prioritize investments, optimize resource allocation, and strengthen the empirical literature on nighttime road safety.]]></description>
      <pubDate>Thu, 09 Jul 2026 13:29:25 GMT</pubDate>
      <guid>https://trid.trb.org/View/2721783</guid>
    </item>
    <item>
      <title>Developing Guidance on the Safety Performance of Edge Line Pavement Markers and Guardrail Delineations on Rural Oregon Roads</title>
      <link>https://trid.trb.org/View/2724855</link>
      <description><![CDATA[Despite Oregon's efforts to reduce fatalities and serious injuries, crashes along curves (statewide) continue to be high-risk locations, particularly those involving roadway departures.  Contributing factors such as speed, visibility, pavement quality, limited delineation, and adverse weather conditions exacerbate these risks.  While Oregon incorporates edge line pavement markers and guardrail delineations, there is limited research on their safety performance on Oregon specific rural roads. It will also investigate whether combining edge line pavement markers with guardrail and barrier delineations as part of a systemic safety countermeasure strategy provides greater safety benefits than applying treatments individually.

This research will produce a guidance document outlining recommendations for the use of edge line pavement markers and guardrail delineations on rural curves.  The document will provide: (1) criteria for identifying high-risk curves where these treatments will be most effective, considering factors such as crash history, speed, curve geometry, and environmental conditions; (2) guidance on combining edge line pavement markers with guardrail and barrier delineations as a systemic safety countermeasure strategy to achieve greater safety benefits; (3) scalable solutions tailored to rural curves that address Oregon’s unique roadway environments and crash patterns; and (4) performance evaluation framework for ongoing assessment and monitoring of these countermeasures.]]></description>
      <pubDate>Wed, 08 Jul 2026 15:06:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2724855</guid>
    </item>
    <item>
      <title>Factors Influencing Rural Freight Transport in Bangladesh: Insights from Generalized Linear and Additive Models</title>
      <link>https://trid.trb.org/View/2719390</link>
      <description><![CDATA[Freight transportation is an important research topic in the transportation domain of high-income countries, but middle-income and low-income countries lack quality research on this, especially for heterogeneous roadway freight movement on narrower rural roads. This study addresses this issue in northern Bangladesh, analyzing the volume of five dedicated freight vehicle types across 1,162 roadway segments. A negative binomial generalized linear model (NB-GLM), along with a supporting negative binomial generalized additive model (NB-GAM), was found suitable to better explain the interrelation between freight volume and different predictors like area, population, household size, solvency rate, crest width, embankment height, and international roughness index. Freight movement was notably higher on market days. The NB-GLM highlighted significant linear effects of socioeconomic attributes, whereas the NB-GAM revealed strong nonlinear influences of roadway and spatial characteristics. Distinct variations were observed for predictor significance in statistical terms across different vehicle classes. These findings serve as a decision-support tool for policy makers wanting to implement targeted interventions, including temporal zoning, last-mile surface funds, and village freight consolidation hubs. The results provide a robust framework for predicting freight movements in regions with similar economic conditions, aiding in sustainable road network development and maintenance planning.]]></description>
      <pubDate>Fri, 26 Jun 2026 08:40:59 GMT</pubDate>
      <guid>https://trid.trb.org/View/2719390</guid>
    </item>
    <item>
      <title>A full Bayesian random parameters Negative Binomial-Lindley model for fatal pedestrian crash frequency on rural highways</title>
      <link>https://trid.trb.org/View/2706957</link>
      <description><![CDATA[Pedestrian safety on rural highways remains a pressing concern in low- and middle-income countries (LMIC), where highways frequently pass through settlements with substantial pedestrian activity but limited dedicated pedestrian infrastructures and prevalence of high-speed motorized traffic. This study investigates fatal pedestrian crash frequency on such roads using a fine-resolution segment-level approach. Five-year fatal pedestrian crash data (2017–2022, excluding 2020), comprising 337 pedestrian-involved crashes across six rural highway corridors, were analyzed by dividing the entire road network into 2,881 equal-length segments. Crash data were integrated with detailed segment-level information on traffic exposure, vehicular speeds, roadway geometry, roadside environment, land use, and population exposure. Four count data models were estimated within a Full Bayesian framework to account for overdispersion, excess zeros, and unobserved heterogeneity, and the best-fitting model was identified for pedestrian crash frequency. Model performance was evaluated using the Deviance Information Criterion, predictive accuracies, and cumulative residual plots, which support the superiority of the Random Parameter Negative Binomial-Lindley (RPNB-L) model over its counterparts. Results indicate that the presence of junctions, settlements, land use, flyover transition zones, canals/bridges/culverts, median gaps, service roads, minor accesses, and pedestrian activity generators such as bus stops, schools, fuel stations, and roadside eateries primarily drives pedestrian crash risk on rural highways. Population exposure emerges as a robust predictor of risk, while observed pedestrian volumes exhibit a safety-in-numbers effect. The findings emphasize the need for segment-level pedestrian safety strategies on high-speed rural highways and provide empirical evidence to support targeted infrastructure design, access management, and roadside environment interventions in LMICs.]]></description>
      <pubDate>Thu, 18 Jun 2026 16:34:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706957</guid>
    </item>
    <item>
      <title>Performance of Glass-Based Geosynthetic Reinforced RAP Bases for Unpaved Road Applications</title>
      <link>https://trid.trb.org/View/2678556</link>
      <description><![CDATA[The United States classifies over 1.3 million miles of its roadway network as unpaved and low-volume roads, which constitutes nearly 35% of the transportation infrastructure of the country. A significant portion of it consists of local and rural roads, which play a crucial role in connecting remote communities. Construction of these low-volume roads (LVRs) with Reclaimed Asphalt Pavement (RAP) base could potentially be a sustainable and cost-effective alternative to virgin aggregate base. However, the usage of RAP in pavement layers comes with several challenges such as reduced strength and stiffness, moisture susceptibility, and variable material properties. These drawbacks directly affect the pavement performance under repeated traffic loading, resulting in higher settlement and long-term deformations. In order to overcome the shortcomings and improve the performance of the pavements, the use of geosynthetics is a promising solution. The performance of conventional geosynthetics, such as geogrids and geotextiles is well-studied and proven to show significant improvement as reinforcing material. However, non-traditional geosynthetics, such as glass-based geosynthetics for base layer reinforcement, have been investigated minimally. Hence, this study explores using two different glass-based geosynthetics, GlasPave (GP) and GlasGrid (GG), as base layer reinforcement for RAP to improve the pavement performance. An experimental study was performed on unreinforced and reinforced sections with a 100% RAP base using large-scale cyclic plate load tests. From the test results, it was observed that the unreinforced section exhibited low stiffness and failed with a surface deformation of over 3 in. under 3,000 load cycles. Whereas the reinforced sections that were constructed with GP and GG installed at the mid-depth of RAP base layer showed significantly high stiffness and resulted in 50% to 75% less surface deformation when compared to the unreinforced RAP base section.]]></description>
      <pubDate>Fri, 12 Jun 2026 15:59:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2678556</guid>
    </item>
    <item>
      <title>Evaluation of Expanded Uses of Residential Driveway Temporary Signals (RDTS): Turn Lane Volumes and Storage</title>
      <link>https://trid.trb.org/View/2712243</link>
      <description><![CDATA[Traffic management for work zones in rural two-lane two-way highways can be challenging as these segments often intersect with low volume side streets and access points. Residential Driveway Temporary Signal devices (RDTS) (formerly Driveway Assistance Device (DAD)) have provided a solution to improve mobility for traffic entering a one-lane, two-way work zone. These devices have been implemented for several years under experimental evaluations by numerous state and local agencies across the United States. In January 2025, the optional use of RDTS was approved by the Federal Highway Administration (FHWA) under Interim Approval (IA) 23. However, whereas prior experimental use of the DAD allowed the device to be deployed at minor cross-streets and commercial driveways, IA-23 only allows for the RDTS to be used at residential driveways. To that end, this proposed research project will assess the operational effects of RDTS when used at non-residential access points to develop guidance that will inform future policy-making related to the device. The proposed project objectives build upon the work already performed with RDTS/DAD and other temporary work zone signal systems by considering their use at uncontrolled rural low-volume side streets and access points. Of particular interest is the ability of RDTSs to handle traffic on low volume side streets and access points with a focus on turning volumes related specifically to the designed turn lane storage capacity (i.e., the amount of left and right turn storage). The results will include implementation guidance that will delineate appropriate usage cases of the RDTS, including appropriate mainline and access point exiting volumes based on storage capacity of the turn lane(s) departing the access point. Guidance related to future Manual on Uniform Traffic Control Devices (MUTCD) language will also be provided where applicable and appropriate.]]></description>
      <pubDate>Tue, 09 Jun 2026 12:32:57 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712243</guid>
    </item>
    <item>
      <title>Safety Performance of Centerline Raised Pavement Markers</title>
      <link>https://trid.trb.org/View/2707952</link>
      <description><![CDATA[Centerline raised pavement markers (RPM) have emerged as a justifiable rural road safety countermeasure for preventing run-off-road (ROR) and opposite-direction crashes. These devices supplement lane markings, enhance positional guidance, alert drivers to changes in roadway geometry, and reduce encroachment. This research evaluated the safety effect of centerline raised pavement markers (RPM) installed on rural roads in Indiana and proposed a practical and systemic approach for identifying road segments that require more attention. To support the Indiana Department of Transportation (INDOT) in this task, the study develops a set of Crash Modification Factors (CMFs) that reflect the safety effects of installing raised pavement markers on the target crashes. The analysis is based on crash data collected from Indiana rural two-lane roads during the 2015-2023 period, which comprised more than 20,000 crashes across over 8,000 roadway segments. In addition to the effect of RPMs, the study also investigated the joint safety effects of RPMs and other countermeasures, including rumble strips (RS) and shoulders and lane widths. The results help determine the joint effect of any combination of these road cross-section features on reducing the crash occurrence and severity. A panel analysis (cross-sectional combined with before-and-after analyses) through a negative binomial model with random effects was implemented to safety-related data from two-lane rural roads during the studied nine-year period. The safety effects across sites with and without raised pavement markers were estimated while controlling local factors such as traffic volume and road geometry. This study confirmed a statistically significant reduction in ROR crashes associated with the implementation of raised pavement markers (RPMs) equal to 15% at daytime and 11% at nighttime on average across the treated Indiana roads. The opposite-direction collisions, including head-on and opposite-direction sideswipe crashes, were significantly reduced at nighttime by nearly 22%. The daytime opposite-direction crashes showed no significant change after RPMs implementation.]]></description>
      <pubDate>Fri, 05 Jun 2026 16:38:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2707952</guid>
    </item>
    <item>
      <title>Effective Shoulder Width on Rural Highway System Related to Roadway Departure Crashes</title>
      <link>https://trid.trb.org/View/2705398</link>
      <description><![CDATA[Roadway design plays a crucial role in traffic safety, particularly on rural roads. This research investigates the safety effectiveness of shoulder width on Indiana’s rural two-lane highways, and to use this understanding to provide a basis for more effective shoulder improvement programs. Although previous studies have established the benefits of shoulder widening in other states, limited research has been conducted in Indiana conditions. This research aims to evaluate the safety effectiveness of shoulders on rural roads in Indiana and to propose a practical and systemic approach to identifying road segments that require additional attention and possible need for shoulder improvements. A negative binomial model with random effects was implemented to evaluate run off road crash frequency on two lane rural roads in relation to shoulder width. Nine years of crash data from 2015 to 2023 from over 5,000 miles of Indiana rural highways was used. This model incorporates geometric factors including shoulder width, traffic exposure, and the presence of rumble strips to quantify the impact of shoulder width on crash frequency. Crash Modification Factors (CMFs) were developed based on the existing combinations of shoulder and lane width, and proposed design alternatives. This allows for a comparison among different configurations. Findings indicated that increasing shoulder width generally reduces crash frequency. Installing a 5- or 6-foot shoulder in a location that previously did not have a shoulder resulted in the highest reduction in crashes according to CMFs. Shoulders equal to or exceeding 7 feet showed diminishing safety benefits when compared to shoulders of 5–6 feet. This is potentially due to the additional risk-taking by drivers under seemingly safer conditions. The presence of roadside rumble strips was found to reduce run-off-road (ROR) crashes by 9.1%.]]></description>
      <pubDate>Tue, 02 Jun 2026 11:02:33 GMT</pubDate>
      <guid>https://trid.trb.org/View/2705398</guid>
    </item>
  </channel>
</rss>