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    <title>Research in Progress (RIP)</title>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Research in Progress (RIP)</title>
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      <link>https://rip.trb.org/</link>
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    <item>
      <title>Hotspot Stability of Freight Vehicle Crashes Involving Vulnerable Road Users: A Spatio-Temporal Perspective</title>
      <link>https://rip.trb.org/View/2625586</link>
      <description><![CDATA[This research will analyze the interaction between two of the most different transportation road users that interact on roads—freight vehicles and vulnerable road users (VRU), i.e., pedestrians and bicyclists. The research objective of this project is to identify the temporal stability of hotspots in (1) non-fatal crashes, (2) fatal crashes, and (3) all crashes (non-fatal and fatal) between freight vehicles and VRU in two U.S. States. This research proposes a novel spatiotemporal analysis to answer whether crash hotspots intensify over time (i.e., the number of crashes increases over time at the same location) or if it stays the same over time.  In terms of processes, the first one is collecting the data on fatal, non-fatal, and all crashes of both States into a single file, cleaning it, and ensuring its validity/accuracy/consistency. Once the data collection is ready, the second process focuses on merging the panel data into a space-time cube. This arrangement will host on a single data array geographical and temporal data of the total number of (1) non-fatal crashes, (2) fatal crashes, and (3) all crashes between freight vehicles and VRU for each State. The third process is calculating a Local Indicator of Spatial Association Statistic (the Gettis Ord*) to identify crash hotspot locations for each year of analysis for each State, and estimate emerging hotspot patterns based on the panel data results. The fourth process will use crash hotspot locations (identified in process three) and data from the County Business Pattern data, the Census Tract Data, and the American Community Survey to compare urban economic and built environment characteristics between different types of hotspots (e.g., recent versus consecutive hotspots), and identify common factors and differences. Specifically, the research team will compute an ANOVA and a post hoc test to identify statistical differences between crash hotspot locations. The last process focuses on visualizing the results on a geographic information system (GIS) software or tables for statistical analysis.  The results of the spatiotemporal analysis will be correlated with urban economic and built environment features to identify common factors in hotspot locations that could have influenced road crashes in both States. These factors include built environment attributes and the number of establishments by industry sector, among others.]]></description>
      <pubDate>Tue, 18 Nov 2025 14:19:08 GMT</pubDate>
      <guid>https://rip.trb.org/View/2625586</guid>
    </item>
    <item>
      <title>Understanding Factors Influencing Truck Crashes with Vulnerable Road Users: A Panel Data Approach</title>
      <link>https://rip.trb.org/View/2625592</link>
      <description><![CDATA[The purpose of this project is to define the spatial, temporal, and socioeconomic factors that most significantly contribute to truck-related accidents involving vulnerable road users (VRU) and to determine how variations in these factors alter the frequency of crashes. VRUs, such as pedestrians and bicyclists, are at the greatest risk when interacting on roadways, and accidents involving trucks and VRUs very frequently result in severe injuries or fatalities. This research will be conducted in New Mexico and Tennessee, both served by major interstate highways and characterized by unique economic patterns. To achieve this, the research will employ panel data regression analysis using crash records from both states, combined with socioeconomic and economic activity indicators at the Zip Code level. The dependent variable will be the frequency of truck-related accidents involving VRUs, while independent variables will include demographic, economic, and contextual factors, with controls such as weather conditions. The models will be tested for robustness, and results from the two states will be compared to identify context-specific patterns and to develop policy recommendations that enhance roadway safety for VRUs.]]></description>
      <pubDate>Mon, 17 Nov 2025 16:15:57 GMT</pubDate>
      <guid>https://rip.trb.org/View/2625592</guid>
    </item>
    <item>
      <title>Integrating Large Commercial Motor Vehicle Safety into State Freight and Safety Planning




</title>
      <link>https://rip.trb.org/View/2558373</link>
      <description><![CDATA[According to the Federal Motor Carrier Safety Administration (FMCSA), Large Truck and Bus Crash Facts 2022, crash rates in the United States involving large trucks increased 25 percent from 2009 to 2021. Given their size and weight, large-truck crashes can result in closure of one or more lanes of a highway, particularly for rollovers or cargo spills. Large-truck crashes also have the potential to damage pavements, bridges, and other infrastructures. 

Large commercial motor vehicles include heavy-duty tractor-trailers and heavy equipment such as dump trucks. Data collection and reporting related to large commercial truck crashes and safety are the responsibility of federal and state agencies, diffusing the “ownership” of commercial truck safety among largely unrelated agencies. However, state department of transportation (DOT) officials often do not reach out to agencies with these responsibilities, such as the FMCSA or the state’s highway patrol agency, in their freight and highway safety planning processes. Plans developed from these planning processes are not informed by the data collected and managed by these agencies. The lack of agency coordination means that the infrastructure needed to support large commercial trucks are not fully considered in state highway and freight planning processes. Thus, infrastructure such as truck parking and emergency escape ramps may not be prioritized in highway safety and freight plans and funding programs. 

Research is needed to identify integrated approaches that consider large commercial motor vehicle safety in highway freight and safety planning processes and plans. 

The objective of this research is to develop a guide for the integration of commercial motor vehicle safety into state freight and safety planning processes. ]]></description>
      <pubDate>Thu, 29 May 2025 12:59:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/2558373</guid>
    </item>
    <item>
      <title>Enhancing Rural Roadway Safety through Geospatial Analysis and
2SFCA-Driven Rest Area Serviceability Optimization for Trucks</title>
      <link>https://rip.trb.org/View/2265842</link>
      <description><![CDATA[Truck-involved crashes within the rural network pose a distinctive and multifaceted challenge that necessitates a specialized approach for comprehensive analysis and effective mitigation. Data from the Insurance Institute for Highway Safety (IIHS) indicates that fatal truck crashes frequently occur between 12:00 p.m. and 3:00 p.m., deviating from patterns observed in other vehicle crashes. This peculiarity arises from the distinct routines of truck drivers, often commencing journeys early, which amplifies the risk of driver fatigue and contributes to crashes during the early hours. These observations underscore the imperative to address driver fatigue and enhance rest area serviceability and functionality in rural contexts. Recognizing the unique characteristics of rural areas necessitates acknowledging that truck-involved crashes within these regions can have varied effects on groups such as older adults. These disparities emphasize the crucial need for an all-encompassing approach to enhance safety. Leveraging the context of Florida, this project endeavors to formulate a robust methodology that incorporates geospatial, optimization, and machine learning techniques. By incorporating these multifaceted techniques, the methodology aims to holistically evaluate the resilience of these communities, thereby contributing to a comprehensive comprehension of the repercussions of truck-involved accidents in rural areas.
The objective of this proposal is to improve rural roadway safety by enhancing the accessibility and facilities of rest areas for trucks along rural highways in Florida. By applying the specialized Two-Step Floating Catchment Area (2SFCA) method, this proposal aims to bridge the gap between rest area provisions, truck driver behavior, and rural truck-involved crashes. The data-driven insights generated through this project have the potential to significantly elevate rural roadway safety in Florida. This initiative intends to establish a clear correlation between the availability of rest areas, particularly truck parking lots, and the frequency of truck-involved crashes on rural roadways. The objective is to offer data-driven insights that guide strategic rest area development, thereby contributing to the reduction of truck-related accidents and fostering safer rural highways across Florida.
To meet this research demand, Signal4Analytics (S4A) and the Fatality Analysis Reporting System (FARS) serve as optimal platforms for collecting truck-involved crash data. Furthermore, the 2SFCA analysis acknowledges the distinctive features of trucking operations. It encompasses the delineation of catchment areas surrounding each rest area, adapting to rural travel conditions and operational constraints. Calculating accessibility scores for each rural catchment area factors in elements such as the availability of truck parking lots and the population density within each region. These scores provide insights into the potential utilization of rest areas by truck drivers in rural environments. The integration and analysis of truck-involved accident data from Florida’s rural roadways hold pivotal importance. This process uncovers patterns and hotspot locations, linking these incidents with computed accessibility scores to unveil potential associations between rest area accessibility and rates of truck-involved accidents in rural settings.
]]></description>
      <pubDate>Thu, 19 Oct 2023 16:40:51 GMT</pubDate>
      <guid>https://rip.trb.org/View/2265842</guid>
    </item>
    <item>
      <title>Completing the Picture of Crashes: Understanding Data Needs and Opportunities for Road Safety</title>
      <link>https://rip.trb.org/View/2067969</link>
      <description><![CDATA[Since 2009, fatal crashes involving large trucks have steadily increased to 4,237 fatal crashes in 2017, a 46.5 percent increase when compared to 2009. Over that same time period, non-fatal crashes involving large trucks have increased by 57.6 percent to an estimated 446,000 such crashes. This study will leverage existing data sources external to the agency, to gain more insight into crashes involving large trucks and buses, including, but not limited to: Federal Highway Administration (FHWA) roadway inventory data; National Highway Traffic Safety Administration (NHTSA) Fatality Analysis Reporting System (FARS), CRSS and EDT; economic data (e.g. truck sales, employment trends, etc.). Once identified, the various data sets will be integrated and analyzed. The analysis will allow 
the Federal Motor Carrier Safety Administration (FMCSA) to identify areas of concern and develop countermeasures to drive new initiatives to reduce large truck and bus crashes on our nations roadways.]]></description>
      <pubDate>Mon, 21 Nov 2022 16:26:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/2067969</guid>
    </item>
    <item>
      <title>Impact of Truck Drivers and Transportation Infrastructure Characteristics on Large Truck Crashes</title>
      <link>https://rip.trb.org/View/1904957</link>
      <description><![CDATA[For the past three decades, Texas has had the highest number of fatal crashes involving
large trucks in the United States. Other states in Regions 6 also have high rates of large truck
crashes. Due to the size and weight of large trucks, their crashes usually are very destructive.
Although large trucks have a significant impact on traffic safety in Region 6, very little analysis
has been conducted on the risk factors associated with crashes involving large trucks, especially
the roadway-related risk factors. The purpose of this research is to perform a comprehensive
evaluation of crash and operational data to identify the root causes of crashes involving large
trucks in Texas. This includes developments of a database of large truck crash reports in the
target area, calculation of crash counts and rates, and identifying road segments and intersections
with highly concentrated large truck crashes and the unsafe actions that are contributing to such
crashes. The crash data analysis will include detailed review of the crash narratives and diagrams
as part of the crash database building process to help elucidate the true causes of the crashes.
The evaluation will include operational and physical characteristics of the crash locations, severity
of injuries, environmental conditions, characteristics of truck drivers, and road users behaviors as
well as the common characteristics of the built environment that contribute to unsafe actions and
conditions. The above evaluation shall allow the research team to identify on-system and off-system
segments and intersections with highly concentrated large truck crashes and the unsafe
actions that are contributing to these crashes and provide safety countermeasures and
recommendations for further study. The changes in crashes in 2020 could primarily be attributed
to changes in travel due to COVID-19. The COVID-10 impact could also be highly variable based
on location, and it might be difficult to determine if these changes were due to COVID-19, other
factors, or just simple randomness associated with highly random and independently distributed
events such as large truck crashes. However, the team carefully examines the 2020 crash data to
see if there would be any consistent identifiable impacts of COVID-19. This research will also
include an in-depth analysis aiming at pinpointing variables that may have affected road safety
associated with large trucks during the pandemic. In order to provide an efficient and quick
solution to the problem, the team aims to carry out the tasks outlined below:
(1) The team will first undertake a thorough review of the available literature.
Available past research and reports of a related nature, from Texas, Region 6, across
the nation, and internationally, will be reviewed. Some of these resources will be listed
and individually described elsewhere in this proposal. A major focus of the research
team will be identification and prioritizing of risk factors associated with crashes
involving large trucks and the effectiveness of engineering/educational
countermeasures to improve safety. (2) The team will download operational and safety data from sources such as
Crash Records Information System (CRIS), the Fatality Analysis and Reporting
System (FARS), which has far more specialized detail on large truck crashes, Texas
Department of State Health Services records, and crash narratives as well as site
visits. (3) The team will use data mining to examine spatio-temporal indicators that
may reveal information about the correlation between crash numbers and traffic
volumes, common characteristics of the built environment that contribute to unsafe
actions and conditions, and other factors. (4) The team will use different data collection techniques to understand road
user’s behavior and review crash narratives and diagrams. These observations will
not only be helpful in the analysis of risk factors, but also provide a framework that
guides decision-making throughout the entire process, from identifying a problem to
implementing a countermeasure.]]></description>
      <pubDate>Thu, 20 Jan 2022 14:48:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/1904957</guid>
    </item>
    <item>
      <title>Phase 2: Computationally Informed Methodologies for Capturing the Effect of Intervening Structures during Truck Impact Events</title>
      <link>https://rip.trb.org/View/1757972</link>
      <description><![CDATA[The continued, multi-step approach involving detailed computational modeling and the development of simplified design approaches for estimating the effect of vehicle-column will be extended. In the second phase, the yield line theoretical analysis will be extended to various angles of truck attack crashing into the barrier, as this was established in the current phase for perpendicular loading to the barrier only, supported by numerical simulations using Abaqus. This way, design graphs or tables will be produced to help Kansas Department of Transportation (KDOT) engineers account for various scenarios to select cases that are safe, relatively conservative and accurate. An expanded set of vehicle velocities, vehicle orientations, barrier types, and pier configurations will be explored with detailed computational simulations. Preliminary development of a “Riera Function” for the studied truck will conducted. 
Since the hypothetically impacting vehicle must first pass through a vehicle barrier, it can be assumed that the vehicle barrier is failed.  Yield line theory describes the behavior of under reinforced concrete elements where energy is dissipated primarily by plastic deformation in the reinforcement. Yield line analysis of the vehicle barrier will likely also help to estimate the energy dissipated and reduce the demand on the column.
The singular objective of the proposed research is the further development of a design methodology for the accidental bridge pier impact by trucks that have departed the roadway.]]></description>
      <pubDate>Tue, 15 Dec 2020 14:56:27 GMT</pubDate>
      <guid>https://rip.trb.org/View/1757972</guid>
    </item>
    <item>
      <title>Evaluation of Traffic Crash Characteristics on Elevated Sections of Interstates in Louisiana </title>
      <link>https://rip.trb.org/View/1745432</link>
      <description><![CDATA[The primary objective of this project is two-fold: first, to fully develop a video analytical
software to classify and count vehicle stream and have the capability of calculating vehicle speeds and/or headways; and secondly, to undertake crash analysis on selected elevated segments to look for characteristics of crashes, common issues, and similarities/differences in car and truck crashes. ]]></description>
      <pubDate>Thu, 15 Oct 2020 15:36:43 GMT</pubDate>
      <guid>https://rip.trb.org/View/1745432</guid>
    </item>
    <item>
      <title>Assessment and Repair of Prestressed Bridge Girders Subjected to Over-Height Truck Impacts (OHTI)</title>
      <link>https://rip.trb.org/View/1738102</link>
      <description><![CDATA[Having adequate reliable infrastructures, including bridges, has been crucial to the process of economic and social development of any country. Bridges are exposed to man-made and natural hazards such as earthquakes, floods, and impact loads. Vehicles and vessels may impact bridge columns, piers, and girders causing severe damage and yielding losses of human lives and economy. Based on bridge failure incidents occurred between 1967 and 2006, vessel and vehicles impacts are the second highest cause of bridge failure in the U.S. Failure occurred due to damage to bridge girders and columns. This project focuses on the behavior and repair of bridge girders subjected to over-height truck impacts.

OBJECTIVES: Vehicle impact is one of the major causes for bridge collapse in the U.S. The overarching goal of this project is to assess the damage to and repair of bridge girders due to the over-height truck impact using comprehensive experimental testing and analytical models. In particular, this project aims to determine: • The remaining carrying capacity of bridge girders damaged due to over-height truck impact which will allow stakeholders (e.g., state department of transportation engineers) to prioritize girders needing repairs. • Determine the carrying capacity of the damaged girders after being repaired using different repair measures. The repaired beams will be investigated under static and fatigue loads to determine their capacities.

]]></description>
      <pubDate>Thu, 10 Sep 2020 10:54:48 GMT</pubDate>
      <guid>https://rip.trb.org/View/1738102</guid>
    </item>
    <item>
      <title>Evaluate Ohio Department of Transportation's Ability to Decrease Dump Truck Backing Accidents</title>
      <link>https://rip.trb.org/View/1644893</link>
      <description><![CDATA[There are 305 backing accidents involving dump trucks, an average of 100 per year, which have been experienced by the Ohio Department of Transportation (ODOT) from 1/1/2015 to 2/21/2018. To maneuver large trucks and equipment, ODOT Highway Technicians (HTs) utilize side-view and rear-view mirrors coupled with ground guides, but these views are limited. This weakness may cause ground guides to be invisible in the mirrors to the driver in the direct zone of impact throughout the maneuvering. To solve this problem, it is imperative to investigate innovative technologies providing advanced views to the driver throughout various types of operations. It is also critically important to find out the way of utilizing technological advancements to help maximize worker safety, and productivity while decreasing the number of backing accidents involving ODOT dump trucks.
The overall goal of this research is to decrease ODOT's backing accidents through introducing the new technologies that better equip ODOT garage persons, particularly the driver with the ability to perform daily operations in a safer and more efficient manner. To fulfill the goal, the scope of work will be divided into two phases.  The objectives of the Phase 1 research work are to: (1) Evaluate the best practices nationwide for decreasing backing accidents with dump trucks. (2) Identify the pros and limits, as well as specifications of the advanced vision technologies that have been utilized by other states, districts, or counties. (3) Identify the practical experiences in applying the advanced vision technologies together with innovative sensing technologies including vehicle radars and ultrasound sensors in state and local transportation governments, and construction (public and private) work environments for reducing the backing accidents. (4) Analyze and develop the integrated approach to assemble or package the key components of the state-of-the-art/practice technology to make the new option(s) of utilizing the technologies perform effectively throughout day and night operations in all types of severe weather conditions. (5) Develop the draft standard operations procedure (SOP) documenting the improved procedure to ODOT's current process, including the activities involving both day and night operations, as well as in all types of severe weather conditions.
                         ]]></description>
      <pubDate>Thu, 08 Aug 2019 07:55:56 GMT</pubDate>
      <guid>https://rip.trb.org/View/1644893</guid>
    </item>
    <item>
      <title>Investigation and Development of a MASH Test Level 6, Cost-Effective, Barrier System for Containing Heavy Tractor Tank-Trailer Vehicles and Mitigating Catastrophic Crash Event – Phase II</title>
      <link>https://rip.trb.org/View/1582125</link>
      <description><![CDATA[For this study, a new, cost-effective, Test Level 6 vehicle containment system will be developed to prevent and/or mitigate the consequences of errant heavy tanker-truck vehicles striking opposing traffic on heavily-congested urban freeways and interstates as well as crashes into high-risk facilities or highly-populated areas, such as schools, malls, sports venues, concert arenas, military bases, international airports, or critical government buildings. The new optimized barrier system will provide adequate structural strength, investigate reduced heights, consider visual appeal for communities, implement height transitions for barrier ends, incorporate options for expansion/contraction joints, and remain safe for errant motorists operating light to heavy passenger vehicles.]]></description>
      <pubDate>Tue, 05 Feb 2019 16:14:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/1582125</guid>
    </item>
    <item>
      <title>Large Truck Crash Causation Study</title>
      <link>https://rip.trb.org/View/1458078</link>
      <description><![CDATA[A nationally representative sample of large-truck fatal and injury crashes was investigated during 2001 to 2003 at 24 sites in 17 States. Each crash involved at least one large truck and resulted in at least one fatality or injury. Data were collected on up to 1,000 elements in each crash. The total sample involved 967 crashes, which included 1,127 large trucks, 959 non-truck motor vehicles, 251 fatalities, and 1,408 injuries.]]></description>
      <pubDate>Tue, 28 Feb 2017 10:03:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/1458078</guid>
    </item>
    <item>
      <title>Working Group to Consider New Post-Accident Crash Data Elements for Tow-Away Crashes (FAST Act - § 5306)</title>
      <link>https://rip.trb.org/View/1456999</link>
      <description><![CDATA[The working group considered requiring additional data elements in post-accident reports for reportable tow-away crashes involving CMVs, including: 
(1)	The primary cause of the accident, if the primary cause can be determined; and 
(2)	The physical characteristics of the CMV and any other vehicle involved in the accident, including: 
a)	The vehicle configuration; 
b)	The gross vehicle weight, if the weight can be readily determined;
c)	The number of axles; and 
d)	The distance between axles, if the distance can be readily determined.]]></description>
      <pubDate>Wed, 22 Feb 2017 11:47:22 GMT</pubDate>
      <guid>https://rip.trb.org/View/1456999</guid>
    </item>
    <item>
      <title>Truck and Bus Maintenance Requirements and Their Impact on Safety</title>
      <link>https://rip.trb.org/View/1456962</link>
      <description><![CDATA[The current study is analyzing the impact of preventative vehicle maintenance of large trucks and buses on safety, to include not only violations that are serious enough to be listed as out-of-service (OOS) criteria, but also other vehicle maintenance issues which have been found to cause or contribute to crashes. The study seeks to understand the effect of current regulations on maintenance and consider whether new or revised OOS criteria are needed. New or revised OOS criteria may include combinations of vehicle maintenance issues. This study is also assessing the prevalence and nature of State inspection programs and the maintenance standards of the safest carriers.]]></description>
      <pubDate>Wed, 22 Feb 2017 10:17:58 GMT</pubDate>
      <guid>https://rip.trb.org/View/1456962</guid>
    </item>
    <item>
      <title>Assessing the Safety Issues Associated with Isolated Rural Intersections</title>
      <link>https://rip.trb.org/View/1455578</link>
      <description><![CDATA[Due to the relatively low traffic volumes on many rural high-speed roadways roads, it is often not cost-effective to upgrade the roads and not warranted to implement active traffic control devices such as traffic lights to improve safety at intersections and sometimes it may be even counterproductive. However, vehicles traveling on these roadways generally have high speeds and, thus, tend to have relatively more severe injuries when vehicle crashes do occur. In addition, many rural roadways also have high truck volumes and suffer from truck-related safety issues. Although local communities with problematic isolated intersections request traffic signals be installed, often these intersections do not meet the Texas Manual on Uniform Traffic Control Devices (TMUTCD) traffic signal warrants. Furthermore, the placement of a traffic signal at an isolated signal can also create a driver expectancy issue for the traveling public. The purpose of this research is to compile crash and operational data and perform a comprehensive assessment of the risk factors and root causes of crashes involving rural intersections, prioritize the risk factors, identify and evaluate safety countermeasures, and recommend the most effective, low-cost countermeasures for safety promotion.]]></description>
      <pubDate>Fri, 17 Feb 2017 14:45:32 GMT</pubDate>
      <guid>https://rip.trb.org/View/1455578</guid>
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