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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>Enabling Mobility for Older Adults in the US</title>
      <link>https://rip.trb.org/View/2669552</link>
      <description><![CDATA[Driving is essential for the preservation of functional independence for older adults, yet there is a growing number of older adult drivers with comorbid health conditions that might impair their ability to drive safely. Older adult drivers are overrepresented in motor vehicle crash deaths and injuries, which is a major public health concern. The purpose of this project is to (1) develop a comprehensive understanding of the mobility needs and challenges of older adults in the United States, and (2) develop an innovative tool to extend their safety while they drive.  

Aim 1: Develop a comprehensive understanding of the mobility needs and challenges of older adults  

To develop a comprehensive understanding of the mobility needs of older adults, the research team will analyze data from a nationally representative survey of U.S. adults aged 65 and older. The survey contains a comprehensive set of questions that explore driving behavior, transportation options, mobility limitations, and attitudes toward future transportation technologies and policies among adults aged 65 and older.   

Aim 2: Develop an innovative tool to extend their safety while they drive.  

The goal of this project is to understand older adults’ perceptions of an app (StreetCoach) that provides a driving score based on actual driving behavior. A number of apps exist for older adult drivers but the perceptions of older drivers towards their driving score is poorly understood. This study will use a sequential explanatory research design by asking 10 older adults to download and use the app for 60 days. Following this, the research team will conduct in-depth interviews with the participants to gain an understanding of their perception and interpretation of their telematics score, and what factors might motivate them to change their driving to improve the score.   ]]></description>
      <pubDate>Thu, 12 Feb 2026 15:16:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/2669552</guid>
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    <item>
      <title>ELDER-3: Empowering Lifelong Driving Experiences with SAE Level 3 Automation
</title>
      <link>https://rip.trb.org/View/2628204</link>
      <description><![CDATA[Automated vehicles (AVs) are heralded as the future of transportation. The Society of Automotive Engineers categorizes six levels of AV, with levels 1 and 2 already in operation, and level 3 undergoing mass production testing in North America. Level 3 marks a significant advancement, as drivers can engage in non-driving related tasks (NDRT), but must be prepared to take over control of the vehicle at all times. However, level 3 AVs pose significant cognitive and motor demands during take-over requests (TOR) in older drivers with intact cognition, suggesting that take-over maneuvers may be even more challenging for older adults with cognitive impairment (CI).
This study aims to determine the impact of CI on take-over performance in level 3 AVs. Participants (30 older drivers with intact cognition, and 30 older drivers with CI) will engage in level 3 AV driving using a high-fidelity driving simulator while their eyes are tracked for attention and cognitive workload. During the drive, the TOR will require participants to quickly transition from an NDRT to taking over control of the vehicle. Additionally, participants will complete a clinical battery of cognitive, visual, and motor tests.
We hypothesize that older adults with CI will exhibit: (1) slower response to TOR; (2) reduced attention (glances on screen) and increased drowsiness (eyelid closure) before TOR; and (3) heightened cognitive workload (pupillary response) during and after the TOR. In hypothesis (4), we expect that a combination of clinical tests including reaction time, processing speed, and working will predict take-over performance.
]]></description>
      <pubDate>Fri, 21 Nov 2025 14:20:28 GMT</pubDate>
      <guid>https://rip.trb.org/View/2628204</guid>
    </item>
    <item>
      <title>Statewide augmented information in the driver environment study</title>
      <link>https://rip.trb.org/View/2570738</link>
      <description><![CDATA[The purpose of this project is to increase lifelong independence and safe vehicle operation by improving access to environmental information while driving, particularly among older adults and people with visual impairments. By simulating a new framework for computer-vision assisted augmented reality (CVAR) in the driving environment, the research team intends to study how augmenting roadway elements (e.g., lines on the road, lane markers, and obstructions) improves overall operational performance. It is predicted that the universal design approach used in this work will not only substantially benefit older adult drivers but will also benefit all drivers. This is because the University of Maine (UMaine) CVAR solution can be used to improve access to roadway elements during situations of reduced visibility (e.g., at night or during inclement weather) while also highlighting an eventual suite of potential hazards (e.g., downed limbs, wildlife, and pedestrians).  

The work will expand UMaine's Virtual Environments and Multimodal Interaction Laboratory (VEMI Lab)’s current autonomous vehicle simulator (MOISIN: Multimodal Omnidirectional Immersive Simulator for Inclusive Navigation) to include a manual driving operational mode. Related software will also be developed to simulate new inclusive CVAR approaches that combine multisensory feedback with augmented visual information to expand access to a wide range of potential drivers. The resulting UIs will be tested in a series of user studies examining the impact on driving performance across various driving scenarios.]]></description>
      <pubDate>Wed, 02 Jul 2025 13:53:38 GMT</pubDate>
      <guid>https://rip.trb.org/View/2570738</guid>
    </item>
    <item>
      <title>Enhancing the Safety of Georgia’s Senior Drivers and Pedestrians by Analyzing Crash Characteristics and Behavior</title>
      <link>https://rip.trb.org/View/2508953</link>
      <description><![CDATA[The objectives of this research are to enhance senior driving and pedestrian safety by identifying the types of collisions and contributing factors involving senior drivers and pedestrians. The research will lead to recommendations for the most effective countermeasures for improving senior driver performance and assisting senior pedestrians. ]]></description>
      <pubDate>Wed, 12 Feb 2025 07:20:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/2508953</guid>
    </item>
    <item>
      <title>Driver training for Shared Autonomy Systems using Mixed-reality</title>
      <link>https://rip.trb.org/View/2440018</link>
      <description><![CDATA[This is a continuation of a Year-1 deployment project which engages with different vulnerable driver communities - teens who are learning to drive and seniors who are experiencing loss of cognitive capabilities. 

The research team is developing a virtual reality Driver Training system with augmented reality pass through where a 16 year-olds and patients with compromised cognitive capabilities can sit in a stationary real vehicle and use mixed-reality to learn driving skills and get exposed to increasingly challenging driving scenarios. Sensors are strapped onto the steering and brake/gas pedals of their car and capture driver movements, that are fed back into the simulation. The windshield and windows are overlaid with a VR generated driving simulator scenario. As a result, the driver is sitting in a real vehicle with AR passthrough showing the steering wheel and the driver’s hands hands, but the risky driving scenarios are simulated. The goal of this system is to develop a simulator that can be retrofitted in any car so novice drivers can train at home in a safe way and experience risky scenarios that cannot be demonstrated in real-life. 

Mixed-reality or XR means VR with AR passthrough. So some visual elements are VR and others are camera passthroughs of reality.

The Problem: The high costs of elder care, both to the individual and the government, combined with the demographic shift towards an increasing number of older adults as a percentage of the overall US population is creating a major healthcare crisis. The number of senior citizens in the US in 2030 will be twice that of 2000, leading to a shortage of working-age caregivers and putting increased pressure on labor costs. Equally important is maintaining, or preferably ameliorating, the quality of life of a growing elderly population. Maintaining elders’ autonomy is correlated with increasing quality of life and autonomy enhancement is correlated with improving functionality. Driving is typically a symbol of autonomy. The revocation of driving privileges is often the first step taken by families worried about cognitive decline and emerging dementia of the older adult. Dementia including Alzheimer's disease is a chronic, progressive syndrome that is characterized by a reduction in the ability to perform daily activities, e.g. a cognitive decline with increasing unpredictability and psychological symptoms. Dementia affects about 5 million people in the USA and 35 million worldwide. Coincidentally, Autonomous Vehicles (AVs) are a game-changing AI and robotic solution that can enable older people to maintain independence. For this technology to be effectively deployed, Safety and Trust are however key. Older people, but also caregivers and clinicians need to view the technology as safe and trustworthy. To realize this potential, a robust shared autonomy strategy is needed.  The term shared autonomy is an oxymoron, but it embodies the tension observed as caregivers, clinicians, and patients negotiate the need to trust the autonomous system and the desire to stay in control. This research project aims to address the question on how to mediate autonomy between participating actors to allow the human control of the system up to their level of performance and autotune the degree of intervention by the machine to maintain safety.

Approach: To these ends, the team proposes the development of an interactive imitation learning system for safe human autonomous systems. The system is trained by an expert for multiple levels of performance following a curriculum. When the system is deployed with a human non-expert user (e.g. an older driver), the safe by construction neural network controller ensures safety at any level of performance (see figure on the left). This enables the system to personalize its capabilities to suit the human partner while ensuring safety from any mismatches in the expectations of the controller and that of the human user. The AVs will therefore learn how the user desires to share autonomy and ensure the system does not reach an unsafe state under all operating conditions and inputs from the human.]]></description>
      <pubDate>Sun, 13 Oct 2024 08:32:02 GMT</pubDate>
      <guid>https://rip.trb.org/View/2440018</guid>
    </item>
    <item>
      <title>Evaluating Older Drivers’ Reaction to Forward Collision Warning (FCW) Systems Under Conditions of Distraction Using a Driving Simulator</title>
      <link>https://rip.trb.org/View/2321728</link>
      <description><![CDATA[This research aims to evaluate older drivers’ responses to Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) systems under visual distraction, with the goal of enhancing road safety and supporting broader adoption of driver assistance technologies among aging populations. The primary objective is to assess how these systems affect the driving performance of individuals aged 65 and older when distracted, using a high-fidelity driving simulator. In addition, the study explores older drivers’ perceptions, trust, and attitudes toward FCW and AEB technologies to identify barriers and opportunities for increased user acceptance. The project is divided into two phases. Phase 1, documented in this report, involved a literature review, development of experimental protocols, questionnaire design, Institutional Review Board (IRB) approval, and creation of simulator scenarios. The findings and materials developed in Phase 1 provide the foundation for Phase 2, which will involve participant recruitment, data collection, and behavioral analysis.]]></description>
      <pubDate>Tue, 16 Jan 2024 12:24:50 GMT</pubDate>
      <guid>https://rip.trb.org/View/2321728</guid>
    </item>
    <item>
      <title>Safety through Agility: Using Mixed Reality to tune shared autonomy systems</title>
      <link>https://rip.trb.org/View/2292656</link>
      <description><![CDATA[The research team is developing an virtual reality Driver Training system with augmented reality pass through where a 16 year-olds or patients with compromised cognitive capabilities can sit in a stationary real vehicle and use mixed-reality to learn driving skills and get exposed to increasingly challenging driving scenarios. Sensors are strapped onto the steering and brake/gas pedals of their car and capture driver movements, that are fed back into the simulation. The windshield and windows are overlaid with a VR generated driving simulator scenario. As a result, the driver is sitting in a real vehicle with AR passthrough showing the steering wheel and the driver’s hands hands, but the risky driving scenarios are simulated. The goal of this system is to develop a simulator that can be retrofitted in any car so novice drivers can train at home in a safe way and experience risky scenarios that cannot be demonstrated in real-life.   Mixed-reality or XR means VR with AR passthrough. So some visual elements are VR and others are camera passthroughs of reality.  The Problem: The high costs of elder care, both to the individual and the government, combined with the demographic shift towards an increasing number of older adults as a percentage of the overall US population is creating a major healthcare crisis. The number of senior citizens in the US in 2030 will be twice that of 2000, leading to a shortage of working-age caregivers and putting increased pressure on labor costs. Equally important is maintaining, or preferably ameliorating, the quality of life of a growing elderly population. Maintaining elders’ autonomy is correlated with increasing quality of life and autonomy enhancement is correlated with improving functionality. Driving is typically a symbol of autonomy. The revocation of driving privileges is often the first step taken by families worried about cognitive decline and emerging dementia of the older adult. Dementia including Alzheimer's disease is a chronic, progressive syndrome that is characterized by a reduction in the ability to perform daily activities, e.g. a cognitive decline with increasing unpredictability and psychological symptoms. Dementia affects about 5 million people in the USA and 35 million worldwide. Coincidentally, Autonomous Vehicles (AVs) are a game-changing AI and robotic solution that can enable older people to maintain independence. For this technology to be effectively deployed, Safety and Trust are however key. Older people, but also caregivers and clinicians need to view the technology as safe and trustworthy. To realize this potential, a robust shared autonomy strategy is needed.  The term shared autonomy is an oxymoron, but it embodies the tension observed as caregivers, clinicians, and patients negotiate the need to trust the autonomous system and the desire to stay in control. This research project aims to address the question on how to mediate autonomy between participating actors to allow the human control of the system up to their level of performance and autotune the degree of intervention by the machine to maintain safety.  Approach: To these ends, the team proposes the development of an interactive imitation learning system for safe human autonomous systems. The system is trained by an expert for multiple levels of performance following a curriculum. When the system is deployed with a human non-expert user (e.g. an older driver), the safe by construction neural network controller ensures safety at any level of performance (see figure on the left). This enables the system to personalize its capabilities to suit the human partner while ensuring safety from any mismatches in the expectations of the controller and that of the human user. The AVs will therefore learn how the user desires to share autonomy and ensure the system does not reach an unsafe state under all operating conditions and inputs from the human.]]></description>
      <pubDate>Tue, 21 Nov 2023 20:34:14 GMT</pubDate>
      <guid>https://rip.trb.org/View/2292656</guid>
    </item>
    <item>
      <title>Older Road Users Safety in Louisiana: Understanding the Crash Contributing Factors</title>
      <link>https://rip.trb.org/View/2292745</link>
      <description><![CDATA[The objectives of this study are to investigate the factors contributing to older road users crashes in Louisiana and to recommend effective countermeasures to support the SHSP strategies in reducing traffic fatalities and severe injuries.]]></description>
      <pubDate>Tue, 21 Nov 2023 08:21:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/2292745</guid>
    </item>
    <item>
      <title>Office of Behavioral Safety Research Topic Area Meetings: Older Drivers, Novice Drivers, Distracted Drivers, &amp; Seat Belt Use</title>
      <link>https://rip.trb.org/View/2256372</link>
      <description><![CDATA[The objective of this project is to plan and hold four (4) one-day meetings, one for each of the following topic areas: Older Adults’ Mobility, Novice Driver Safety, Distracted Driving, and Seat Belt Use. Meeting participants will present findings from recently concluded projects, ongoing research activities, and planned projects related to each of the relevant topic areas. The meetings will be held around the time of, and near the site of, the Transportation Research Board (TRB) Annual Meeting to facilitate attendance of those attending TRB. Following the meetings, four (4) Meeting Summary Reports summarizing the presentations and discussions will be developed and distributed.]]></description>
      <pubDate>Thu, 28 Sep 2023 13:30:09 GMT</pubDate>
      <guid>https://rip.trb.org/View/2256372</guid>
    </item>
    <item>
      <title>Rearview Video System Training for Older Drivers</title>
      <link>https://rip.trb.org/View/2042311</link>
      <description><![CDATA[The project will assess the effectiveness of the Rearview Video Systems (RVS) training video developed as a part of a previous project (Older Driver Rearview Video Systems) in improving safe backing performance of older drivers. Participants will include ‘young-old’ (60 participants age 60-69) and ‘old-old’ (60 participants age 70+) drivers, in a controlled field study on a closed course. Participants are to be active drivers with little or no experience using an RVS. Half of the participants from each age group will be assigned to a training group that views the RVS training video. The remainder, assigned to the control group, will view a similar-length traffic safety video unrelated to backing or RVS use. Sex equity will be considered by ensuring similar portions of males and females in all four groups. In addition, the plan will recruit participants from a wide cross-section of the population in the study area to ensure people of various demographics have equal opportunity to volunteer to participate. The study’s key research question is "to what extent does viewing an RVS training video that provides instruction on proper use of RVS that address errors observed in participants in the previous Older Driver Rearview Video Systems study improve older drivers’ backing performance when using an RVS?" The study will compare measures of backing performance (e.g., errors, contacts with obstacles) and of eye glance measures (e.g., the RVS, mirrors, or over their shoulder) during backing of the training and control groups. The results will be distributed to the public in a final report. If promising, the training video also will be distributed to the public. ]]></description>
      <pubDate>Fri, 14 Oct 2022 16:17:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/2042311</guid>
    </item>
    <item>
      <title>Advanced Driver Assistance Systems (ADAS) Education and Outreach</title>
      <link>https://rip.trb.org/View/1996241</link>
      <description><![CDATA[BTSCRP Research Report 18: Evaluating and Delivering Advanced Driver Assistance Systems (ADAS) Education: A Guide provides practical guidance for identifying, creating, and modifying ADAS materials to support specific goals and objectives related to education and training.

Proper use of ADAS —rapidly being introduced into the US vehicle fleet—offers the promise of reducing motor vehicle crashes and fatalities. ADAS features, however, can be confusing to drivers; include a wide variance of terminology; and have many differences in design and functionality. ADAS technology differs from previous vehicle safety enhancements for which a simple message or warning conveys direction to drivers. ADAS requires new models for messaging to help drivers understand and effectively use these complex new technologies. As ADAS technologies continue to advance and permeate the vehicle fleet, it is critical to ensure understanding of how the systems work and how to safely use them. 

Under BTSCRP Project BTS-26, “Advanced Driver Assistance Systems (ADAS) Education and Outreach,” the University of Iowa was asked to (1) assess the current state of ADAS education, training materials, and delivery methods; (2) identify key populations in need of ADAS education and training; (3) pinpoint gaps in existing educational content and instructional methods; and (4) determine effective strategies for delivering ADAS information and training to target audiences. 

In addition to this report, the following deliverables are available on the National Academies Press website (nap.nationalacademies.org) by searching BTSCRP Research Report 18: Evaluating and Delivering Advanced Driver Assistance Systems (ADAS) Education: A Guide: Conduct of research report that documents the entire research effort, published as BTSCRP; Web-Only Document 9: Advanced Driver Assistance Systems (ADAS) Education and Outreach; ADAS Information Source Tracker; Resource Identification Tool; Content Organization Tool; and PowerPoint Presentation.]]></description>
      <pubDate>Thu, 21 Jul 2022 12:56:53 GMT</pubDate>
      <guid>https://rip.trb.org/View/1996241</guid>
    </item>
    <item>
      <title>Older Driver Research Feasibility Study</title>
      <link>https://rip.trb.org/View/1977954</link>
      <description><![CDATA[This project explores the efficacy of smart phone apps as an intervention for older drivers with a particular interest in RoadCoach, a smart phone app originally developed to reduce risky driving in teens, This project will provide a thorough description of the RoadCoach app's functions, specifically how the system detects and alerts drivers to risky behaviors, identify and describe other driver support smart phone apps, conduct a literature review and crash data analysis to identify driving behaviors commonly associated with crashes among young adult, and older adults drivers, and report the findings in a report that discusses the likelihood that each identified system would be effective in reducing risky driving behaviors among these cohorts of drivers. Because the app was initially developed to reduce risk for teen drivers, the study will also include similar research on teen and young adult drivers. A final report will describe the findings from a smart phone app scan and review, a literature review, and a crash data analysis. This report will discuss the extent to which RoadCoach’s and other apps’ designs, including feedback timing and modality, are optimal for each driver age group, and how they could be expected to change drivers’ behavior under conditions associated with elevated crash risk for each age group. This report will explain whether RoadCoach could be expected to reduce crash risk for young adult and older adult drivers and whether any of the other apps could be expected to reduce crash risk for these two groups.]]></description>
      <pubDate>Wed, 08 Jun 2022 19:52:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/1977954</guid>
    </item>
    <item>
      <title>Integrated Tailored Driving Plan for Rural Seniors</title>
      <link>https://rip.trb.org/View/1937029</link>
      <description><![CDATA[Older adult drivers face many challenges as they age – physically, perceptually, and cognitively. These may affect their ability to drive, which is crucial, as well as their general mobility. Those older adults living in rural areas may face even greater impediments to mobility due to the lack of infrastructure or feasible alternative transportation options. Several tools exist to aid drivers or extend their capabilities in an effort to maintain mobility for longer periods of time. To date, these tools have not been applied or integrated in a systematic fashion for rural senior drivers. This effort will utilize available tools to create a customized driving plan for seniors. Once developed, the program will be implemented with 30 seniors and evaluated in a naturalistic data collection study. Participants will drive for one month, demonstrating patterns and concerns. The program will then be tailored and delivered for each. Their driving will then be monitored for two additional months to evaluate program efficacy. Results will highlight the importance of customized solutions that focus on specific needs rather than a blanket approach. The toolbox and technologies utilized will be considered a living document, one that can be altered based on emerging new technologies and learnings.]]></description>
      <pubDate>Sat, 02 Apr 2022 11:12:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/1937029</guid>
    </item>
    <item>
      <title>Identification and Assessment of Preventative Methods to Mitigate Cognitive and Physical Declines Which Influence Driving Performance of Older Drivers</title>
      <link>https://rip.trb.org/View/1917684</link>
      <description><![CDATA[The objectives are to: (1) provide additional guidance on the efficacy of the coaching app to improve older driver performance and safety over a prolonged exposure period; (2) determine the strength of mindfulness meditation training on improving attention and driving performance; and (3) determine how the two treatments combined may result in additional gains in performance over each individual treatment.]]></description>
      <pubDate>Wed, 16 Feb 2022 11:24:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/1917684</guid>
    </item>
    <item>
      <title>Exploring traffic safety problems and challenges of older roads’ users in Louisiana: Causes and countermeasures</title>
      <link>https://rip.trb.org/View/1751132</link>
      <description><![CDATA[Statistics published by the U.S. Department of Transportation, National Highway Traffic Safety administration (NHTSA, 2017) indicated that there were 6,784 people age 65 and older killed in traffic crashes in the United States in 2017, representing 18 percent of all traffic fatalities. Although the population of people 65 and older increased by 31 percent from 2008 to 2017, traffic crash fatalities in that age group increased by 22 percent over this period. These figures can be explained due to several mobility and traffic safety challenges encountered by older adults while using roads as pedestrians or drivers. For example, prior research indicates that older pedestrians exhibit declining walking skills (e.g., decreased walking speed, reduced stability while walking, and less efficient wayfinding strategies), and a greater tendency to engage in unsafe crossing behaviors. Particularly, older adults tend to begin crossing when safe crossing gaps are available in the near lane, but not the far lane (Tournier et al., 2016). Another recent Canadian study (Gargoum et al. 2018) indicated that the design of road infrastructure could have an impact on the risk of traffic collisions for older adults. The findings of this study revealed that available sight distances fell below the stopping sight distance requirements for drivers with limited abilities (e.g., older drivers), particularly in poor driving conditions. Accordingly, it was recommended that changes in the design guidelines for future roadways should reflect the aging driving population. However, little is known about the effect of different types of roadway crossing, geometry and traffic control devices on the safety of older roads’ users. In addition, there is a lack of a solid understanding of older road users’ preferences and needs while crossing different types of pedestrian crossings. As the proportion of older adults continues to increase in USA and elsewhere, it is vital to understand the challenges faced by older roads’ users (drivers and pedestrians), and suggest effective countermeasures to improve their safety and maintain their mobility and independence into later life stages. Therefore, the main objectives of this research are to: (1) Identify the circumstances and precipitating factors contributing to older roads users’ crashes including driver, vehicle and road/environment factors. (2) Identify hotspot locations of crashes involving older road users (drivers/pedestrians). The first two objectives will be addressed through a compressive analysis of traffic collisions database of Louisiana, (3) Examine the effects of changes in the roadways design and traffic control devices on the drivers’ behaviors and safety of aging population. This will be achieved through a driving simulator experiment that will be conducted using LSU driving simulator. (4) Provide a better understanding regarding older pedestrians’ preferences and needs to cross different types of pedestrian crossings safely. This will also include examining older pedestrians’ awareness of their declining abilities and their effects on safety and mobility. To achieve these goals, a questionnaire survey among a representative sample of older pedestrians in Louisiana will be conducted. It is expected that the outcomes of this research will provide better understanding regarding the causes of traffic safety problems of older roads’ users in Louisiana and will accordingly suggest some countermeasures and/or actionable plans to improve the safety of older road users.]]></description>
      <pubDate>Tue, 10 Nov 2020 15:55:33 GMT</pubDate>
      <guid>https://rip.trb.org/View/1751132</guid>
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