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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>Implicit Safety Benefits for Vulnerable Road Users</title>
      <link>https://rip.trb.org/View/2151379</link>
      <description><![CDATA[Research Project Includes the following tasks: literature Review, data collection, data linkage and visual analysis, DOT safety benefit tool development, TAC meetings, technology transfer for workshop/training to HSIP staff only. Includes quarterly, interim, and final reports with recommendations to the Department.]]></description>
      <pubDate>Wed, 12 Apr 2023 19:35:08 GMT</pubDate>
      <guid>https://rip.trb.org/View/2151379</guid>
    </item>
    <item>
      <title>Investigate Age Impacts on Controlled Flight into Terrain (CFIT) Crashes in General Aviation</title>
      <link>https://rip.trb.org/View/1881804</link>
      <description><![CDATA[Controlled Flight into Terrain (CFIT) crash is defined as an unintentional collision with terrain (the ground, a mountain, a body of water, or an obstacle) while an aircraft is under positive control. It is one of three high-risk accident occurrence categories identified by the International Civil Aviation Organization. Although advanced technologies have dramatically reduced the number of General Aviation CFIT crashes over the past 20 years, CFIT crashes continue to occur and at least half of them are fatal. Therefore, it is quite momentous to identify the contributing factors and recommend countermeasures to prevent or mitigate CFIT crashes. This research will utilize the General Aviation CFIT crash data collected from National Transportation Safety Board (NTSB) and pilots’ information from Federal Aviation Administration (FAA), to perform statistical analysis to reveal the impacts of pilots’ age and other pilot related contributing factors on the occurrence of CFIT crashes in General Aviation. Based on the analysis, technology-based and policy-level countermeasures will be proposed to reduce the CFIT crashes. The research findings will help policymakers to better understand the underline reasons for General Aviation CFIT crashes and update their current practices and regulations.
The research is developed based on the CAMMSE theme of addressing the FAST Act research priority area of “Improving Mobility of People and Goods” for multimodal transportation. As discussed earlier, General Aviation plays an important role in moving people and goods, such as business travel or overnight delivery. Improving the safety of General Aviation is the foundation of improving the mobility of people and goods transported by General Aviation. The research is relevant to the CAMMSE research thrust “Innovations to improve multi-modal connections, system integration and security”. Specific project objectives include:
(1)	Review current practices and regulations on the safety operations in General Aviation,
(2)	Identify pilot related factors contributing to CFIT crashes in General Aviation,
(3)	Investigate the impacts of pilots’ age on the occurrence of CFIT crashes in General Aviation, and
(4)	Recommend technology-based and policy-level countermeasures to mitigate General Aviation CFIT crashes.
]]></description>
      <pubDate>Mon, 04 Oct 2021 13:27:28 GMT</pubDate>
      <guid>https://rip.trb.org/View/1881804</guid>
    </item>
    <item>
      <title>Partial Automation for Truck Platooning</title>
      <link>https://rip.trb.org/View/1441804</link>
      <description><![CDATA[The safety, mobility and environmental impacts which are side affects of the current transportation system will continue to worsen as the population and vehicle miles traveled (VMT) continue to increase.  For many reasons, conventional solutions can only partially address the numerous challenges associated with transportation.  Technologies combining information technology, sensing systems, and communications can be used to automate the driver-vehicle-highway system and have the potential for transformational changes.  Commercial vehicles because they are highly regulated.   For example, human error is a major factor in around 90 percent of crashes.  Humans are very good at complex tasks but are not as good at paying attention (distracted driving).  Machines on the other hand are not as good at complex tasks in an uncontrolled environment such as highway driving but do not get distracted and are therefore very good at staying alert.  Congestion relief is another area where technology development can have huge impact.  Vehicle to vehicle or infrastructure to vehicle communications when added to automating truck speed and spacing can as much as double throughput capacity.    Automation can safely maintain or increase the mobility of the elderly and physically challenged populations by supplementing or taking over portions of the driving task.]]></description>
      <pubDate>Wed, 04 Jan 2017 10:52:59 GMT</pubDate>
      <guid>https://rip.trb.org/View/1441804</guid>
    </item>
    <item>
      <title>Spatial-Context Intersections Safety Analysis for the Aging Population: An Integrated 3-Dimensional Visualization and Human Factors Simulation Approach</title>
      <link>https://rip.trb.org/View/1414809</link>
      <description><![CDATA[As the number of elderly drivers continues to increase, there is a need to identify parameters that can negatively influence their driving
performance. Since major parts of fatalities and injuries to elderly drivers occur at intersections, it is evident that improving safety at
intersections will decrease the number of dangerous crashes for this age group. This research aims to determine significant parameters
associated with drivers’ gap acceptance behavior while they perform a turning maneuver at a four-legged, permissive signalized
intersection. For this purpose, drivers of different age group were asked to perform left-turn and right-turn maneuvers at four-legged,
permitted signalized intersections developed using driving simulation. Human characteristics of drivers (age, gender, and driving
experience), presence of pedestrian in or nearby of the crosswalk, number of lanes, different crosswalk configurations (ladder or
standard) and contextual conditions (heavy fog, and night conditions) were considered for generating driving scenarios. The distance
between a turning driver (participant’s vehicle) and the nearest on-coming entity (vehicle or pedestrian) was considered as a
measurement for how conservative a driver is. A standard linear regression model, Artificial Neural Network (ANN), and the M5’ tree
model were employed to identify a correlation between the explanatory variables and the distance to the nearest on-coming entity (as
dependent variable). The results illustrated that the age of driver, accepted gap size, and number of lanes; are significantly correlated
with the distance to the entity in both left- and right- turn models. Moreover, the results of left-turn models illustrated the importance
of other two variables of driver’s gender and presence of pedestrian(s) on the distance to the entity. The results also showed that ANN
model outperforms the other two models in producing accurate results; however, this model performs like a black-box and lacks
coefficients that are interpretable. This issue of ANN method was addressed by M5’ model. The produced M5’ model not only benefits
from the advantages of data mining methods, but it also presents some interpretable formulae to make the model applicable for other
data sets.]]></description>
      <pubDate>Fri, 01 Jul 2016 13:07:37 GMT</pubDate>
      <guid>https://rip.trb.org/View/1414809</guid>
    </item>
    <item>
      <title>Understanding Contributing Factors to Wrong-way Crashes and Evaluating the Effectiveness of Countermeasures in Reducing Wrong-way Crash Risk of Older Drivers</title>
      <link>https://rip.trb.org/View/1414801</link>
      <description><![CDATA[Although relatively infrequent, when Wrong Way Crashes (WWCs) occur they are much more likely to be fatal, and to involve multiple fatalities, compared to other types of highway crashes. Impairment as a result of drug and/or alcohol consumption is a major contributing factor to WWCs. However, older drivers are also at greater risk of being involved in WWCs. The focus of the current project was assess the effectiveness of different countermeasures in preventing Wrong Way Entries (WWEs), a frequent precursor to WWCs, and reducing confusion regarding highway entry points. A driving simulator study asked older drivers (65+) to enter a highway using an entrance ramp on the left while passing an exit ramp on the left that featured various levels of wrong way countermeasures (minimum required signs and pavement markings defined by the MUTCD, minimum plus the addition of a No Left Turn (R3-2) sign before the lip of the exit ramp, and an enhanced countermeasure condition that included additional signs, larger signs, and enhanced pavement markers. The number of WWEs did not statistically differ as a function of countermeasure level, nor did pre-planned analyses of behavioral driving data reveal differences in uncertainty regarding which ramp (entrance or exit) to enter. Exploratory analyses found that a measure of confusion/uncertainty (speed before the exit ramp) did differ significantly between the minimum and enhanced countermeasure conditions, in line with previous simulator findings that enhanced countermeasures can reduce confusion (Boot, Charness, Mitchum, Roque, Stothart, & Barajas, 2015). While providing some support for the benefit of enhanced countermeasures, results also suggest that WWEs are particularly difficult to prevent. Even in the minimum plus and enhanced conditions featuring multiple redundant cues, some older drivers (2) still entered the exit ramp. This research highlights the need to understand not only the best set of cues to prevent WWEs, but the most effective cues to provide further down the exit ramp (e.g., flashing Wrong Way signs, flashing in pavement LED markers) to encourage retreat once a WWE has occurred.]]></description>
      <pubDate>Fri, 01 Jul 2016 11:54:10 GMT</pubDate>
      <guid>https://rip.trb.org/View/1414801</guid>
    </item>
    <item>
      <title>Vision-Based Traffic Conflict Detection of Signalized Intersections</title>
      <link>https://rip.trb.org/View/1371693</link>
      <description><![CDATA[A key to the development of effective crash countermeasures is an understanding of pre-crash causal and contributing factors. Accurately determining the cause or behaviors leading to traffic crashes is a very challenging process. Traditionally, traffic conflict observations by manual or automated means have been used to determine pre-crash causal factors. In recent years, naturalistic driving studies have been used to provide detailed and more accurate pre-crash causal information.

Naturalistic driving databases contain large datasets of low-resolution video streams (due to compression) of highly variable intersections, multiple flows, and turning movements of vehicles under very complex lighting conditions (e.g., constantly varying shadows). This makes automated traffic conflict detection and analysis very challenging. Also, existing vision-based traffic conflict detection systems are not designed to work in naturalistic real world settings; as a result, they fail to extract relevant information from these databases.

To maximize the use of this valuable safety dataset, vision systems with a high-level of understanding of scene dynamics around the naturalistic driver must be developed. The project aims at developing a vision system for understanding pre-crash causal factors through the detection and analysis of traffic conflicts in a naturalistic real world setting.
]]></description>
      <pubDate>Wed, 14 Oct 2015 11:54:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/1371693</guid>
    </item>
    <item>
      <title>Suborbital Pilot Training Assessment
</title>
      <link>https://rip.trb.org/View/1367928</link>
      <description><![CDATA[There exists a great deal of information about pilot performance under high +Gz forces from extensive military high performance fighter jet aircraft and centrifuge studies. There are little data, however, on pilot performance in a high +Gx environment, particularly repetitive exposures. Although astronauts and cosmonauts experience increased +Gx forces during launch, they are not actively piloting the spacecraft during this time. Similarly, the +Gx acceleration in carrier launch operations is experienced in a “hands off” pilot control window. The situation will be quite different in commercial suborbital flights for companies such as XCOR and Virgin Galactic. In these vehicles the pilots will experience sustained high +Gx acceleration (often in combination with high +Gz acceleration) during the vertical portion of the flight and will need to actively pilot the vehicle during this phase of the launch into space. This is similar to X-15 operations where pilot control issues were thought to be associated with one fatal accident, lending credibility to the concern over pilot performance in such scenarios. Further, the addition of a microgravity period between high acceleration exposures adds the risk of a potentially significant “push-pull” effect, complicating the physiological response profile. Research is needed to evaluate pilot performance and physiological response, including their hemodynamic tolerance, their ability to manually reach and operate the controls, maintain visual focus on the instruments, and avoid sensory perception illusions that could cause disorientation, in order to better understand the impacts on performance during sustained +Gx and combined +Gx/Gz acceleration and to
make sound recommendations regarding physiological and medical standards for pilot screening prior to suborbital spaceflight crew selection.
]]></description>
      <pubDate>Thu, 03 Sep 2015 11:14:09 GMT</pubDate>
      <guid>https://rip.trb.org/View/1367928</guid>
    </item>
    <item>
      <title>Research to Support the Development of Human Factors Guidance for Ameliorating the Negative Effects of Surprise, Startle, and Distraction</title>
      <link>https://rip.trb.org/View/1361236</link>
      <description><![CDATA[No summary provided.]]></description>
      <pubDate>Fri, 17 Jul 2015 01:00:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/1361236</guid>
    </item>
    <item>
      <title>Situation Management</title>
      <link>https://rip.trb.org/View/1360977</link>
      <description><![CDATA[This research focuses on the cognitive and behavioral components involved in managing dynamic situations, and uses air traffic scenarios as a vehicle for studying those processes.]]></description>
      <pubDate>Wed, 15 Jul 2015 01:01:11 GMT</pubDate>
      <guid>https://rip.trb.org/View/1360977</guid>
    </item>
    <item>
      <title>Quantifying Vermont Transportation Safety Factors</title>
      <link>https://rip.trb.org/View/1359743</link>
      <description><![CDATA[Researchers at the Transportation Research Center (TRC) are teaming up with state officials to address key issues in the Agency of Transportation's "Strategic Highway Safety Plan." This project focuses on the following emphasis areas: 1)  keeping vehicles from running off the roadway; 2)  safety of young drivers (under age 21); and 3)  lack of alertness due to fatigue, in-vehicle distractions and other driver errors. The TRC will take the lead in utilizing the Vermont crash database to provide in-depth analysis for policy-makers attempting cost-effective solutions for reducing crashes in the state.]]></description>
      <pubDate>Thu, 02 Jul 2015 01:00:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/1359743</guid>
    </item>
    <item>
      <title>Pre-crash Multi-vehicle Experimental Analysis Using a Networked Multiple Driving Simulator Facility</title>
      <link>https://rip.trb.org/View/1285236</link>
      <description><![CDATA[To evaluate human performance and resulting crash safety, the University Transportation Center (UTC) will develop a robust simulation facility in which multiple vehicles interact; some of these vehicles will be driven by people, some will be autonomous, and some will be autonomous to varying levels, with people in the driver's seat but disengaged to various levels from the actual driving of the vehicle. Although a single simulator can be used to create scenarios that involve other programmed autonomous, semi-autonomous, and non-autonomous vehicles, it provides only an approximation of the level of unpredictability and uncertainty encountered when multiple human drivers are operating in the same environment--as is the case in real-world driving. The ability to create a virtual driving environment simultaneously accessed by three or more human drivers allows a much closer approximation of reality, with its attendant risks. Therefore, a key enabling first step will be to develop a network of driving simulators that can interoperate to conduct multi-driver tests. The project will leverage three existing simulator facilities at Ohio State University (OSU), University of Wisconsin, Madison (UW), and University of Massachusetts (UMass), all of which are from the same vendor, Realtime Technologies, to design and execute common scenes and scenarios. In addition, the project will purchase desktop simulator units from Realtime Technologies for Indiana University-Purdue University in Indianapolis (IUPUI) and North Carolina A&amp;T State University (NCA&amp;T), so that all five institutions are able to contribute to the experiment designs and access experiment data. The initial selection of safety applications to be evaluated is based on results from the National Highway Traffic Safety Administration's (NHTSA's) Crash Imminent Test Scenarios and Safety Pilot Model Deployment. The safety applications will include Forward Collision Warning (FCW), Lane Change/Blind Spot Warning (LCW/BSW), Emergency Electric Brake Light Warning (EEBL), and Intersection Movement Assist (IMA). This project will enable testing of drivers with autonomous vehicle systems with an unprecedented capability in multi-driver and multi-vehicle interaction studies. In addition, this project will generate "standard" scenarios that can be shared with the transportation research and education community.]]></description>
      <pubDate>Sat, 04 Jan 2014 01:00:27 GMT</pubDate>
      <guid>https://rip.trb.org/View/1285236</guid>
    </item>
    <item>
      <title>Bioinjury Implications of Pre-crash Safety Modeling and Intervention</title>
      <link>https://rip.trb.org/View/1285233</link>
      <description><![CDATA[This project will directly address the University Transportation Center's (UTC's) human physiology strategy. The goal will be to include bioinjury expertise in scenario generation, data collection, and human behavioral models so that research outcome metrics are closely aligned with the goal of improving safety. In particular, the project will investigate whether bioinjury data from a particular crash scenario can suggest particular evasive actions by the driver or the autonomous vehicle to minimize injury. The project hypothesizes that bioinjury data from a particular crash scenario can suggest situations in which the driver should not re-engage and assume control of the vehicle but rather leave the autonomous system in control, because human motor skill or reaction time would be insufficient to mitigate injury. Coupled with human behavioral models developed in Projects 2 and 3, this project will be able to extrapolate situations beyond those for which data currently exist, and to test these extrapolated situations under Project 1. The project will also investigate how bioinjury data can inform the user community--both vehicle designers and vehicle safety policy makers--about the optimum position of the driver and the timing of passive restraints for given crash scenarios. As an example, recent data from airbag injury studies have suggested that the position of the driver's hands on the wheel should be modified to avert arm and wrist fractures when airbags are deployed. This information is expected to inform policy and safety procedures as well. As a second example, increasing vehicle autonomy for crash prevention increases the likelihood that the vehicle is braking hard at the time of impact, placing the driver and passengers in very different positions than those currently being employed in crash testing. The research on both driver behavior and autonomous vehicle behavior is expected to suggest alternative--and more relevant--safety testing procedures. A primary resource for this research will be the crash data available from two national sources. The National Automotive Sampling System (NASS) Crashworthiness Data System (CDS) provides a broad range of data from crashes that occur in the United States. These data, largely based on police reports, focus on passenger vehicle crashes and are used to investigate injury mechanisms. The database may be queried across several relevant variables, including primary direction of impact, object impacted, age and sex of occupants, safety restraints, and resulting injuries. The Crash Injury Research Engineering Network (CIREN) consists of detailed analyses of motor vehicle crashes, including both accident reconstruction and medical injury profiles. CIREN is University Transportation Centers Program more focused on specific crashes in which the occupant received a serious injury. The CIREN network brings together the first responders to the crash, the treating physicians, and a panel of bioinjury experts to examine each injury in detail and to document corresponding injury mechanisms. Similar to NASS CDS, CIREN cases may be searched across several relevant variables. The CIREN database is ideal for comparing bioinjury data across variations in a given crash scenario, such as different passive restraints or different occupant positions. The project will use the NASS CDS to define the most critical injury mechanisms related to each scenario to be considered in the UTC. The project will also examine CIREN to document specific injury outcomes based on variations related to the automobile safety systems and to the driver's position and reaction. These analyses will be used to understand which variations lead to fewer or less severe injuries, providing valuable input to both human behavior influencing strategies and autonomous vehicle control strategies considered in other projects, with the goal of improving pre-crash safety. Information leading to improvements in passive restraint systems and more effective crash test protocols are also expected.]]></description>
      <pubDate>Sat, 04 Jan 2014 01:00:20 GMT</pubDate>
      <guid>https://rip.trb.org/View/1285233</guid>
    </item>
    <item>
      <title>Application Specific Scenario Evaluation Using Driving Simulator</title>
      <link>https://rip.trb.org/View/1236233</link>
      <description><![CDATA[The project utilizes an in-house 3-axis driving simulator and has been divided into three major components examining various driver related issues. The first examines the change in driving behaviors, capabilities, and reaction time of people who are under the influence of alcohol. Multiple driving scenarios have been created and programmed for the simulator allowing the test subjects to drive through traffic situations they may face in the Las Vegas valley. This provides an opportunity to observe how the chances of crashes and other incidents increase while intoxicated. This function will also be used for conducting local workshops at alcohol serving establishments to increase awareness of issues related to driving while intoxicated. The second component of the project involves developing an elderly driver training and re-training program. The aim of this program is to provide elderly drivers a simulated traffic environment to sharpen their skills and become more aware of their driving abilities. This program will both evaluate their skills and facilitate training for those drivers. The third component of the project involves conducting surveys to gather public opinion about new proposed traffic changes ranging from new laws to new transportation related construction. The test subjects would be able to drive through the city with the new changes included in the simulated scenarios and provide feedback for local and state officials to consider.]]></description>
      <pubDate>Thu, 03 Jan 2013 15:43:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/1236233</guid>
    </item>
    <item>
      <title>Evaluation of High Potential Areas for Truck Overweights and Accidents</title>
      <link>https://rip.trb.org/View/1234321</link>
      <description><![CDATA[There are several areas in California that have high incident and accident weights involving overweight trucks. These areas need to be investigated and recommendations made for possible use of Weigh in Motion equipment to assist Law Enforcement in removing these overweight vehicles from the roadway. Areas where overweight trucks may find alternate routes to bypass fixed/static weight stations will be evaluated. Also, potential placement of virtual weight in motion equipment on these routes will be evaluated.]]></description>
      <pubDate>Thu, 03 Jan 2013 15:10:27 GMT</pubDate>
      <guid>https://rip.trb.org/View/1234321</guid>
    </item>
    <item>
      <title>Evaluation of Dynamic Speed Signs</title>
      <link>https://rip.trb.org/View/1232122</link>
      <description><![CDATA[Speeding is a major increasing contributing factor in all traffic crashes including local and collector highways. This factor, in addition to restrictive law enforcement agencies' budgets and staff, poses an ever present need for effective, low-cost, speed mitigation measures. Studies have determined that Dynamic Speed Signs (DSS), when used in relation to roadway work zones, can reduce the traveled speed of vehicles. DSS display the approaching vehicle's speed to the driver in addition to the posted speed limit. This study will evaluate the effectiveness, both short-term and long-term, of DSS as a speed reduction measure for local and collector roadways. Different configurations and messages will be examined to determine the most effective DSS. The study will be conducted through the use of a driving simulator obtained through a National Science Foundation grant by the Principal Investigator. The results of this study will provide concepts that can be utilized in the development of Variable Speed Signs for interstates and highways during recurring or nonrecurring congestion in order to limit queuing and poor levels of service.]]></description>
      <pubDate>Thu, 03 Jan 2013 14:32:21 GMT</pubDate>
      <guid>https://rip.trb.org/View/1232122</guid>
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