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    <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" />
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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>Evaluating the Safety Performance of Delineator-Based Temporary Restricted Crossing U-Turns as a Cost-Effective Treatment</title>
      <link>https://trid.trb.org/View/2720199</link>
      <description><![CDATA[Restricted Crossing U-turn (RCUT) intersections have proven highly effective at reducing crashes on rural high-speed highways. As a cost-effective interim solution, transportation agencies may implement delineator-based temporary RCUTs before constructing permanent concrete-median installations. However, the safety performance of temporary RCUTs remains underexamined in the current literature. This study evaluates the safety performance of six unsignalized temporary RCUTs in Mississippi: three on urban six-lane divided highways and three on rural four-lane roadways installed between 2015 and 2022. This study considered two before–after safety evaluations: naïve annual crash frequency analysis and a rigorous Empirical Bayes (EB) method. The crash modification factor (CMF) estimation was facilitated by developing new local safety performance functions (SPFs), and the results were compared with those derived from Highway Safety Manual (HSM) SPFs and state-specific SPFs. Results showed that at urban locations, there was a 28% reduction in total crashes and 18% in fatal and injury (FI) crashes. Rural locations showed even more promising results, with a 74% reduction in total crashes and 71% reduction in FI crashes at the intersection-level analysis. These results demonstrate that temporary RCUTs can achieve safety benefits comparable to conventional intersections, particularly in rural, moderate-volume contexts. Given their significantly lower construction cost ($111,000 versus $3.8 million), temporary RCUTs represent one of the most cost-effective solutions for agencies seeking immediate crash reduction at high-risk locations.]]></description>
      <pubDate>Wed, 23 Sep 2026 15:56:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2720199</guid>
    </item>
    <item>
      <title>Enhanced Crash Risk Estimation in Urban Environments: Integrating Multi-Source Data and Advanced Modeling Approaches for the City of Pittsburgh</title>
      <link>https://trid.trb.org/View/2778230</link>
      <description><![CDATA[Crash risk estimation is a critical aspect of transportation safety study, aimed at identifying high-risk locations and mitigating potential hazards/risks for road users. Limited resources can be allocated to those high-risk areas for effectively improving safety for the entire network. As travel demand grow, new mobility options emerges and traffic volumes increase, the complexity of factors influencing crash risk has also grown. Historically, crash risk estimation has been approached using statistical models, such as Safety Performance Functions (SPFs), which predict the expected crash frequency or risk on road segments based on exposure and other factors. However, the dynamic nature of urban environments and the growing availability of diverse data streams, such as video analytics, near-miss reports, real-time traffic data, and social media, present opportunities to enhance traditional methods. In particular, data directly measuring near-misses in addition to observed and rare accidents enable a more holistic and accurate measure of crash risks. These sensing and methodological advancements can improve model accuracy, reduce biases, and provide more granular insights into high-risk locations for both motorized and non-motorized traffic.

By leveraging long-term multi-source data related to crash risks, diverse sources such as police reports, traffic stops, and near-miss incidents from the city of Pittsburgh, and applying both statistical and machine learning approaches, this project aims to enhance the precision of crash risk estimations. It addresses key challenges related to data aggregation, modeling performance, and bias mitigation to provide more reliable safety insights that can inform future interventions.

Methodology and steps

The approach is to estimate SPFs for both motorized and non-motorized crash risks in the city of Pittsburgh with multiple data sources, including historical crash data, UPMC urgent care data, police traffic stop reports, 311 near miss report, 911 Dispatch data, Waze reports (social media), Velo.ai video analytics data, and so on. Specifically, the research team processes the video, medical, police and Waze data among all locations and in the past few years to either improve or validate the SPFs (namely current risk maps). The team applies both statistical and machine learning models and select the best model based on model performance. The team develops a new crash map and compare it with the the current risk map network. The team explores the potential biases and how to improve the accuracy of crash risk estimation in general. This work will be conduct particularly for the City of Pittsburgh, but can be replicated in any other communities in general. The detail for each step is listed below.
Step 1: Conduct a comprehensive literature review on risk factors and video analytics algorithm for near-miss detection
The team plans to carry out a comprehensive literature review on types of risk factors that make significant contributions to the crash risk (particularly near-misses related to vulnerable road users). This literature review helps collecting necessary datasets for building robust SPFs to estimate crash risk for streets in the following task. In addition, the team will review the approaches of detecting incidents from the video data, which could help improve the algorithm in detecting near-miss cases from the camera videos.

Step 2: Data collection and video processing for near-miss incidents
In this step, the team will collect the related datasets which could benefit the safety performance function estimation from multiple data sources. Table 1 lists potential datasets that could be applied in this research project. Furthermore, the team plans to carry out video processing with advanced deep learning techniques to detect the near-miss incidents from the camera videos from selected intersections. The result of the number of near-miss incidents and driving factors could be either used to improve the SPFs or validate the estimated SPFs.

Table 1. Source and year of the datasets
Dataset	Data source	Year
High injury network	City of Pittsburgh	-
Crash data	PennDOT	2017-2023
UPMC urgent care	UPMC	In request
Police traffic stop report	City of Pittsburgh	2018-2022
311 near miss report	City of Pittsburgh	2019-2023
911 Dispatch data	WPRDC	2015-2022
Network of bike facilities	City of Pittsburgh	-
Built environment data	EPA	-
Socio-demographic data	NHGIS	-
Waze data	Waze for Cities	2018-2024
Cyclists’ waypoints and distances to vehicles	Velo.ai	2022-2024
Camera video from selected intersections	City of Pittsburgh	In request
Strava pedestrian and bicyclist count data	Strava Metro	2023-2024

Step 3: Estimate SPFs with both statistical and machine learning modeling approaches.
The team will estimate two sets of SPFs for motorized crash risk and non-motorized crash risk, respectively, with the data collected and processed in Step 2. The team plans to apply both statistical (e.g., linear regression, Poisson regression, and Negative Binomial regression) models and machine learning models (e.g., random forest, gradient boosting decision tree, and neural network). The team will compare the model performance and select the best one as the final model.

Step 4: Develop a crash map for all street segments in Pittsburgh, compare it with the original high injury network, and prioritize high-risk locations. 
The team plans to use the estimated SPFs to predict the expected crash risk (both motorized and non-motorized) for all streets in the city of Pittsburgh and develop a crash map dashboard. The team will compare the crash risk with those estimated in the high injury network and find the differences. The team will explore the sources of bias and study how to improve crash risk estimation. Finally, the team will rank the locations and prioritize high-risk ones for further examination.]]></description>
      <pubDate>Thu, 17 Sep 2026 16:28:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/2778230</guid>
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    <item>
      <title>Assessment of Safety and Operation Performances of CFIs and DDIs in Utah</title>
      <link>https://trid.trb.org/View/2744901</link>
      <description><![CDATA[The diverging diamond interchange (DDI) and the continuous flow intersection (CFI) represent significant innovations in roadway design, offering superior operational performance and enhanced safety compared with conventional signalized ramp terminals and intersections. This study conducts a comprehensive evaluation of these two designs, focusing on both traffic flow and safety outcomes. The research begins by establishing a safety-integrated calibration and validation framework for microscopic traffic simulation models using PTV VISSIM, a leading microscopic traffic flow simulation software developed by the PTV Group Unlike traditional approaches, this framework incorporates surrogate safety analysis by embedding bivariate peak over threshold (POT) modeling from extreme value theory (EVT) to jointly capture conflict severity using time to collision (TTC) and maximum deceleration (MaxD). This dual-purpose modeling approach allows for the estimation of crash frequency directly from simulated conflicts while maintaining operational fidelity. The calibration achieved high accuracy, with GEH values below 5 for all movements and minimal speed errors, and simulation-based crash estimates for CFIs differing from observed frequencies by only 0.07 crashes per year. Validation using 2019 data further confirmed the predictive capability and generalizability of the models. Complementing the simulation framework, the study utilizes an empirical Bayes (EB) methodology with crash and traffic data from 2006 to 2021 to evaluate six DDI and eight CFI sites in Utah against matched conventional signalized locations. The research developed statespecific crash modification factors (CMFs) and locally calibrated safety performance functions (SPFs), revealing substantial safety benefits for both designs. DDIs demonstrated a 47.8% reduction in fatal and injury (FI) crashes (CMF = 0.522) and a 28.07% reduction in property damage only (PDO) crashes (CMF = 0.719). Similarly, CFI sites showed an 8.54% decrease in FI crashes (CMF = 0.91), a 1.72% decrease in PDO crashes (CMF = 0.98), and a 3.98% decrease in total crashes (CMF = 0.96), preventing an estimated 77 FI, 37 PDO and 127 total crashes over the analysis period. Collectively, these findings validate that when properly designed and operated, both DDIs and CFIs deliver meaningful improvements in safety performance and offer a robust, transferable framework for evaluating both the operational efficiency and safety of innovative intersection designs at regional and national levels.]]></description>
      <pubDate>Mon, 24 Aug 2026 08:44:55 GMT</pubDate>
      <guid>https://trid.trb.org/View/2744901</guid>
    </item>
    <item>
      <title>Development of Safety Performance Functions for Urban and Suburban Multilane Highways in Georgia</title>
      <link>https://trid.trb.org/View/2712062</link>
      <description><![CDATA[This report presents the findings of the Georgia Department of Transportation (GDOT) Research Project 25-04 which concludes Research Project 22-27, which aimed to develop Georgia-specific safety performance functions (SPFs) and estimate crash modification factors (CMFs) to evaluate the safety effectiveness of different median treatments on urban and suburban multilane highways. Leveraging six years (2016–2021) of crash, roadway, and traffic data—with a focus on 2018–2021 data—the research developed segment-level and corridor-level SPFs and estimated CMFs to quantify the impacts of three median types on crash frequency and severity: undivided/no median, flush medians (two-way left-turn lanes [TWLTLs]), and raised medians. SPFs were developed separately by median type and crash severity (all crashes [KABCO] and fatal and injury crashes [KAB]), incorporating key variables such as traffic volume (annual average daily traffic [AADT]), truck percentage, access point density, intersection density (corridor-level), land use, and area type (urban versus suburban). Findings indicate that raised medians consistently provide the greatest safety benefits in high-volume and high-conflict settings (e.g., AADT > 25,000, dense intersections), and TWLTLs are effective under moderate traffic conditions (AADT 15,000–25,000) with low truck percentages. Undivided/no-median highways are generally suitable only in low-volume, low-conflict environments (AADT < 20,000). CMF-informed policy recommendations were developed to support GDOT in making context-sensitive, data-driven decisions about median design for urban and suburban multilane highways across Georgia, aligning with the department’s design guidelines.]]></description>
      <pubDate>Tue, 23 Jun 2026 13:53:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712062</guid>
    </item>
    <item>
      <title>Highway Safety Manual Crash Prediction Models of Arterial Weaving Segments</title>
      <link>https://trid.trb.org/View/2712176</link>
      <description><![CDATA[More than half of the roadway deaths and nearly two-thirds of pedestrian fatalities in the United States occur on non-freeway arterials. Arterial sections with weaving maneuvers are complex for all road users to navigate and traverse without incidents or collisions.

The Code of Federal Regulations requires determination of whether the location, configuration, geometric design, and signing related to a proposed change in access may be reasonably expected to serve the anticipated traffic of the Interstate system in a manner that is conducive to safety, durability, and economy of maintenance. For many existing and proposed alternative designs, the safety of the weave is not quantified between ramps. Examples include cloverleaf designs with adjacent intersections and crossing weaves from ramps to downstream left turns. A better understanding of crash outcomes is needed for a variety of rural and urban speeds and contexts.

As part of NCHRP Project 15-66, “Operational Performance and Safety Effects of Arterial Weaving Sections,” crash data and conflict data obtained in the field and a driving simulator were analyzed to assess the safety performance of several types of arterial weaving sections. The results of the safety analysis did not provide a definitive relationship between the length and vehicle maneuvers of arterial weaving sections and crashes or conflicts; however, sufficient information was found to suggest additional research in this area would yield promising results toward developing a methodology for predicting the safety performance of arterial weaving sections suitable for inclusion in the AASHTO Highway Safety Manual (HSM).

OBJECTIVE: The objective of this research is to develop a crash prediction methodology, safety performance functions (SPFs), to assess different types of arterial weaving sections, suitable for inclusion in the HSM.]]></description>
      <pubDate>Tue, 09 Jun 2026 14:53:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2712176</guid>
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    <item>
      <title>The Calibrator—An SPF Calibration and Assessment Tool Updated User Guide</title>
      <link>https://trid.trb.org/View/2711610</link>
      <description><![CDATA[This user guide provides background information on safety performance functions (SPFs) and the need for calibration. It also serves as a companion “how-to” manual for The Calibrator software tool. This is an updated user guide based on enhancements to The Calibrator, including the ability to calibrate SPFs based on calibration functions and dispersion functions.]]></description>
      <pubDate>Sat, 06 Jun 2026 17:47:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/2711610</guid>
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    <item>
      <title>Safety Risks of Out-of-Context Curves: Three Decades of Rural Curve Research in New Zealand</title>
      <link>https://trid.trb.org/View/2706340</link>
      <description><![CDATA[The rural road network of New Zealand contains many horizontal curves that are inconsistent with their surrounding environment. These “out of context” curves—where the safe negotiation speed is significantly lower than the prevailing approach speed—are associated with higher crash risk than in-context curves of otherwise similar geometry. Over the past three decades, New Zealand researchers and transport agencies have developed a robust body of work to understand and address this issue, although it remains underexplored internationally. This paper reviews the evolution of rural curve safety research in New Zealand, including the development of high-resolution road geometry datasets, operating speed models, and crash prediction models. It also highlights how these insights have informed national project evaluation guidance and safety prioritization frameworks, and a recent adaptation of this research to international contexts, including the United States. In particular, it was found that traditional crash prediction models such as those in the Interactive Highway Safety Design Model and the Highway Safety Manual can underestimate the observed number of crashes around out-of-context curves by at least 30%, and potentially up to 60%. The recent application of New Zealand curve context modeling to U.S. rural roads through the SafeCurves software tool addresses this limitation. This review aims to demonstrate the value of incorporating curve context into safety analysis and prioritization, highlight New Zealand research in this area, and encourage broader application of these methods to reduce crash risk on rural roads worldwide.]]></description>
      <pubDate>Thu, 28 May 2026 10:47:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2706340</guid>
    </item>
    <item>
      <title>Development of a Pavement Friction Management Program</title>
      <link>https://trid.trb.org/View/2703676</link>
      <description><![CDATA[This project aims to develop a comprehensive framework for statewide pavement friction management and safety-oriented decision-making for IDOT. The project was structured into several key tasks. First, a literature review was conducted to synthesize existing research on pavement friction measurement, friction-crash relationships, investigatory levels, and friction-based treatment strategies. Second, a survey and an assessment of current agency practices were carried out to understand how friction data are collected, processed, and incorporated into project selection and maintenance decisions across peer states. Third, statewide friction data were compiled, cleaned, and spatially integrated into databases for roadway and intersection peer groups to evaluate friction coverage, measurement density, and variation across facility types. Fourth, safety performance functions were developed with explicit consideration of pavement friction and other roadway and intersection characteristics to support risk-based safety evaluation. In parallel, a new life cycle cost analysis (LCCA) framework was established to integrate friction and other pavement surface condition measures (such as the IDOT Condition Rating Survey) into a unified treatment selection model, explicitly accounting for pavement deterioration, treatment effectiveness, and traffic loading. This LCCA framework was further extended to network-level site screening and prioritization through a decision-tree-based approach. In addition, IDOT-specific aggregate policy was assessed with an emphasis on incorporating friction performance into mixture design considerations. Digital image processing techniques, including the Aggregate Imaging Measurement System, have been previously applied to characterize the angularity and surface texture of Illinois aggregates and their degradation under simulated polishing. Morphological indices derived from these prior investigations were compiled and used as inputs for friction prediction modeling, supporting a more proactive, material-level approach to pavement safety performance. The tasks’ outcomes were synthesized into a schematic design of the Illinois friction management system. Finally, educational materials were developed to support statewide training on fundamental pavement friction management concepts. Overall, the project establishes a practical, data-driven foundation for integrating friction performance into safety analysis, material selection, and maintenance planning.]]></description>
      <pubDate>Mon, 18 May 2026 10:59:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703676</guid>
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    <item>
      <title>Revisiting the Estimation of the Highway Safety Manual Calibration Factor and the Evaluation of Crash Frequency Models</title>
      <link>https://trid.trb.org/View/2684240</link>
      <description><![CDATA[Safety performance functions (SPFs) form the analytical backbone of various roadway safety analyses. SPF are either developed as jurisdiction-specific models or adopted from the Highway Safety Manual (HSM) and calibrated to reflect local conditions. This paper first outlines data needs and availability, data processing methods, and approaches to gathering the required data for the calibration and development of SPFs. Rural two-lane two-way segments and intersections in New Jersey are used as a case study. The paper then presents a maximum likelihood–based calibration factor estimation method, an alternative to the one given in the HSM, allowing for the estimation of its standard deviation and the evaluation of sample size adequacy. The results reveal notable differences in calibration factors derived from these two methods. The paper also develops New Jersey–specific SPFs and presents a statistically rigorous evaluation of both the calibrated and developed SPF. A comparative analysis of the calibrated and developed SPF is performed using log-likelihood ratio tests, Rootogram plots, and chi-square tests. The findings caution against relying on mean absolute deviation alone for model comparison, as it fails to account for the intrinsic variability of crash data. The study also highlights that data preparation is often the most resource-intensive aspect of SPF development and calibration, requiring substantial programming and manual effort. Accordingly, the paper emphasizes the need for automated data extraction techniques to reduce costs and improve accuracy, and it underscores the critical role of crash location accuracy in model outcomes.]]></description>
      <pubDate>Thu, 26 Mar 2026 09:05:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2684240</guid>
    </item>
    <item>
      <title>Characterising safety effects of highway rest areas using continuous driving time variable</title>
      <link>https://trid.trb.org/View/2672726</link>
      <description><![CDATA[Previous studies on highway rest area safety assumed driver fatigue based on distance, without directly measuring it. This study used continuous driving time (CDT) from digital tachograph (DTG) data to more accurately represent fatigue and developed a safety performance function (SPF) within an empirical Bayes (EB) framework. Using detailed individual-level data, the analysis divided sites into four reference groups to assess the impact of rest areas on accident reduction. Results showed varying SPF outcomes, with accident reduction effects ranging from 1.8% to 40.1%. The greatest reduction occurred when CDT neared 2 hours, highlighting the importance of strategically installing rest areas where continuous driving is expected to reach that threshold.]]></description>
      <pubDate>Tue, 10 Mar 2026 09:54:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/2672726</guid>
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    <item>
      <title>Intersection Safety Performance Function Calibration for Project Planning and Design</title>
      <link>https://trid.trb.org/View/2678099</link>
      <description><![CDATA[This study calibrated the predictive models for conventional intersections in the Highway Safety Manual (HSM) second edition draft to account for local conditions in Virginia. The calibration ensures that predictions made with the HSM safety performance functions accurately reflect the crash experience, driver population, and environmental characteristics of the state. Crash, traffic, and geometric data were collected for 1,326 intersections across Virginia, representing minor road stop-controlled, all-way stop-controlled, and signal-controlled configurations on rural two-lane, rural multilane, and urban or suburban arterial highways. The study followed HSM-recommended procedures to estimate calibration factors and dispersion parameters for the conventional intersection site-type safety performance functions in the HSM second edition draft. Constant calibration factors provided a good fit for total crashes, with 20 of 21 site types meeting HSM acceptance criteria, but they did not perform as well for fatal and injury crashes. Calibration functions offered a superior fit for those crash types, with 14 of 19 site types achieving percent cumulative residual deviations within 5%. It is recommended that the Virginia Department of Transportation Traffic Operations Division use the constant calibration factors in Table 11 for total crashes and the calibration functions in Table 12 for fatal and injury crashes and incorporate these results into the Traffic Operations and Safety Analysis Manual to ensure consistent statewide application.]]></description>
      <pubDate>Sat, 07 Mar 2026 16:04:41 GMT</pubDate>
      <guid>https://trid.trb.org/View/2678099</guid>
    </item>
    <item>
      <title>Developing a Pedestrian Safety Performance Function for Oregon</title>
      <link>https://trid.trb.org/View/2673030</link>
      <description><![CDATA[This report details the development of a pedestrian safety performance function (SPF) for intersections in urban areas in the state of Oregon. The report documents the process to develop SPFs for pedestrian crashes including the process to develop the data for analysis. A key innovation of this work is the use of pedestrian traffic volume estimates from traffic signals push button actuations. These data and other pedestrian traffic volume data collected through traditional methods are utilized in a machine learning data fusion model to estimate pedestrian volumes for all intersections in Oregon urban areas. SPFs are constructed for various intersection types with different traffic control. Crash prediction models using estimates of pedestrian volumes and also proxies for pedestrian volume are compared to give agencies a sense of how models perform with better pedestrian volume data.]]></description>
      <pubDate>Wed, 25 Feb 2026 09:12:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2673030</guid>
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    <item>
      <title>Development of Colorado Specific Safety Performance Functions (SPF’s) and Diagnostic Norms for Roundabouts</title>
      <link>https://trid.trb.org/View/2666801</link>
      <description><![CDATA[Roundabouts commonly replace intersections to reduce the number of conflict points, with the objective of crash reduction and better operations. They are becoming ever more popular in the United States. Many U.S. based research studies on the topic of roundabouts have focused on evaluating the effectiveness of converting existing intersections to roundabouts. This study was concerned with the development of Safety Performance Functions (SPFs) for Colorado roundabouts as well as diagnostics norms. Implementation: SPF models and diagnostic norms to evaluate safety performance using Colorado-specific crash prediction models for three roundabout facility types have been developed: Urban 3-leg 1-lane, 4-leg 1-lane, and 4-leg 2-lane. The models are ready for immediate use on safety projects by CDOT engineers. The products of this research will allow CDOT to more accurately quantify and evaluate the safety performance of Colorado roundabouts in a timely manner, assess design alternatives as part of future projects and overall make better investments of limited funding where maximizing safety is concerned.]]></description>
      <pubDate>Fri, 20 Feb 2026 08:49:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/2666801</guid>
    </item>
    <item>
      <title>Develop a Real-Time Decision Support Tool for Urban Roadway Safety Improvements</title>
      <link>https://trid.trb.org/View/2663223</link>
      <description><![CDATA[Speed-related crashes remain a critical concern for Texas, identified as one of the seven key emphasis areas in the Texas Strategic Highway Safety Plan (SHSP) for 2018–2022. Traditional crash risk models often overlook essential real-time factors such as operating speed, traffic variability, and weather, limiting their effectiveness. To address this, TxDOT Project 0-7144 integrated data from diverse sources, including NPMRDS and INRIX XD (real-time speeds), TMAS (traffic volumes), CRIS (crashes), RHiNO (roadway inventory), and NOAA (weather), to develop both annual and short-duration Safety Performance Functions (SPFs) for a wide range of urban facility types. Annual SPFs were developed for urban facilities, including freeways, multi-lane divided and undivided highways, continuous left-turn lane roads, and two-lane highways, incorporating geometric and operational features such as lane and shoulder width, truck proportion, driveway density, average speed, and precipitation. This project also employed a Negative Binomial-Lindley (NBL) modeling framework to produce monthly SPFs from 2019 to 2022. These shortduration models captured the dynamic influence of seasonal factors, monthly average daily traffic (MADT), speed and travel time variability, and weather patterns on crash frequency across facility types. A key outcome of the project is the development of an interactive, GIS-based decision support tool using the Shiny platform. This tool enables users to visualize, filter, and download crash prediction outputs at both annual and short-duration levels. It offers dynamic data uploading capabilities, allowing local engineers to input updated roadway and traffic data for customized analyses. The project concludes with recommendations to update Texas SPFs for urban roadways by integrating operating speed and weather data, emphasizing speed consistency in guidelines, and expanding the tool's capacity for daily-level modeling and facility-specific diagnostics.]]></description>
      <pubDate>Thu, 05 Feb 2026 09:18:37 GMT</pubDate>
      <guid>https://trid.trb.org/View/2663223</guid>
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    <item>
      <title>Analysis of Traffic Crash Data in Kentucky 2019-2023</title>
      <link>https://trid.trb.org/View/2642336</link>
      <description><![CDATA[This report documents analysis of traffic crash data in Kentucky. A primary objective of this study was to determine average crash statistics for Kentucky highways. Where used, rates were calculated for various highway types and for counties and cities. Difference criteria were used for exposure. Average and critical numbers, SPFs, and crash rates were calculated for various highway types in rural and urban areas. These metrics rely on crashes identified on highways where Annual Average Daily Traffic (AADT) volumes were available. Data in this report may be used to help identify problem areas. The other primary objective of this study was to provide benchmark data that can be used to prepare the problem identification portion of Kentucky’s Annual Highway Safety Plan (HSP). Crash statistics were analyzed and a summary of results and recommendations in several problem identification areas is presented. These general areas include alcohol involvement, occupant protection, speed, teenage drivers, pedestrians, bicycles, motorcycles, trucks, and vehicle defects. Other areas covered in the analysis for which specific recommendations were not made include school bus crashes and train crashes. Crash data are stored in the Collision Report Analysis for Safer Highways (CRASH) database. This database is updated daily, so the number of crashes in a given calendar year continues to change for a substantial time after the end of that year. KTC captures an extract annually for analysis. Since 1978, annual reports have been prepared to document statewide crash rates. Traffic crash data for a five-year period were used to prepare this report. Kentucky has a systematic procedure to identify locations that have had abnormal rates or numbers of traffic crashes. However, before that procedure may be utilized, average crash rates and numbers must be determined for appropriate highway categories and for rural and urban areas. Those statistics may then be used in the high-crash location identification program to identify locations that should be investigated to determine whether changes should be made. A highway safety program is prepared each year for Kentucky in order to comply with 23 U.S. Code § 402. This program includes identifying, programming, budgeting, and evaluating safety projects with the objective of reducing the number and severity of traffic crashes.]]></description>
      <pubDate>Mon, 26 Jan 2026 14:44:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2642336</guid>
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