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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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      <title>Investigating the Contributing Factors to Willingness to Share Automated Vehicles with Gender Focus</title>
      <link>https://rip.trb.org/View/2142128</link>
      <description><![CDATA[This study uses a survey collected in four metropolitan areas in the United States (Phoenix, Atlanta, Austin, and Tampa) to understand the attitudinal factors underlying men and women’s willingness to share rides on ridehailing services that use automated vehicles (AVs). The study uses a measurement model to classify the attitudinal measures into unobserved latent constructs, and preferences towards owning and driving a vehicle. A Structural Equation Model is then used to measure the effects of gender upon the willingness to share rides in autonomous vehicles, controlling for respondents’ attitudes (latent constructs), current use of mobility-on-demand services, and socioeconomic characteristics. The results of this study are key to ensure that the future of transportation reaches all, regardless of gender. Understanding women’s willingness to engage in autonomous shared rides will enlighten the process of including them in the automated, shared, and electric future. By identifying the different attitudinal traits motivating different groups to engage in shared ridehailing rides, ridehailing service providers can better accommodate their needs, and promote a more egalitarian transportation service. Preliminary results indicate that men’s environmental motivations to use AV shared rides are stronger than women’s, while women’s perception of autonomous vehicles is a stronger predictor of AV ridesharing adoption.]]></description>
      <pubDate>Fri, 24 Mar 2023 10:57:07 GMT</pubDate>
      <guid>https://rip.trb.org/View/2142128</guid>
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    <item>
      <title>Corridor-Wide Surveillance Using Unmanned Aircraft Systems Phase II: Freeway Incident Detection using Unmanned Aircraft Systems Part B
</title>
      <link>https://rip.trb.org/View/2120992</link>
      <description><![CDATA[Unmanned aerial vehicles (UAVs) provide a platform that can carry cameras and sensors for collecting real-time traffic information, especially for corridors under congested conditions, when the traditional loop detectors do not work properly and where there is a lack of other means of traffic monitoring. As an alternative, Road Rangers continuously patrol the roadways monitoring for traffic crashes and stranded motorists and then respond to those incidents. Continuously patrolling along the roadways is costly and man-power consuming. In this study, the researchers will explore the possibilities of replacing the patrolling tasks of Road Rangers with UAVs. The challenging research problems include: (1) development of on-line incident detection methodology with video data from multiple flying UAVs; (2) UAV path planning for corridor incident detection; (3) design and conduct experiments aimed at establishing protocols, standards, and guidance for safely using multiple UAVs for monitoring corridor-wide traffic conditions to complement Part 107 of FAA regulations, as amended. This research requires three phases. Phase I focused on design and test of the operations of multiple UAVs for collecting traffic information and development of incident detection methodology (see NICR Project 4-3: Corridor-Wide Surveillance Using Unmanned Aircraft Systems). Phase II will involve two separate but related research efforts by University of Puerto Rico, Mayaguez (Part A) and The University of South Florida (Part B). The University of South Florida research team will conduct experiments along I-75 and I-275 freeway corridors in Tampa, Florida to verify the protocols, standards and guidance, as well as the methodologies developed in Phase I. In Phase III of this project, the research team will focus on the validation of the algorithms developed in the previous phases and implementation matters of Phase II.

]]></description>
      <pubDate>Tue, 21 Feb 2023 14:30:17 GMT</pubDate>
      <guid>https://rip.trb.org/View/2120992</guid>
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      <title>The Influence of Mode Use on Level of Satisfaction with Daily Travel Routine: A Focus on Automobile Driving in the United States</title>
      <link>https://rip.trb.org/View/1984231</link>
      <description><![CDATA[How does the extent of automobile use affect the level of satisfaction that people derive from their daily travel routine, after controlling for many other attributes including socio-economic and demographic characteristics, attitudinal factors, and lifestyle proclivities and preferences? This is the research question addressed by this research project. In this study, data collected from four automobile-dominated metropolitan regions in the United States (Phoenix, Austin, Atlanta, and Tampa) are used to assess the impact of the amount of driving that individuals undertake on the level of satisfaction that they derive from their daily travel routine. This research effort recognizes the presence of endogeneity when modeling multiple behavioral phenomena of interest and the role that latent attitudinal constructs reflecting lifestyle preferences play in shaping the association between behavioral mobility choices and degree of satisfaction. The model is estimated using the Generalized Heterogeneous Data Model (GHDM) methodology. Results show that latent attitudinal factors representing an environmentally friendly lifestyle, a proclivity towards car ownership and driving, and a desire to live close to transit and in diverse land use patterns affect relative frequency of auto-driving mode use for non-commute trips and level of satisfaction with daily travel routine. Additionally, the amount of driving positively impacts satisfaction with daily travel routine, implying that bringing about mode shifts towards more sustainable alternatives remains a formidable challenge – particularly in automobile-centric contexts.]]></description>
      <pubDate>Wed, 22 Jun 2022 09:41:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/1984231</guid>
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      <title>Attitudes Towards Emerging Mobility Options and Technologies – Phase 3: Survey Data Compilation and Analysis for Tampa, FL</title>
      <link>https://rip.trb.org/View/1983979</link>
      <description><![CDATA[Emerging transportation technologies including electric and autonomous vehicles and emerging mobility services such as ride-hailing and vehicle sharing are bringing about transformative changes in the transportation landscape. With the emergence of new transportation technologies and services, it is critical that transportation forecasting models be enhanced to account for behavioral dynamics that will result from the increasing penetration of disruptive forces in the transportation marketplace. To enhance transportation forecasting models, people’s attitudes towards and perceptions of emerging technologies and services need to be measured and understood. Armed with such an understanding, it will be possible to specify and develop behavioral models that account for attitudes and perceptions, adoption cycles, and adaptation patterns. It is envisioned that such models will help decision-makers better plan transportation infrastructure systems and design marketing and policy strategies that maximize the benefits of these disruptive technologies. This project aims to collect survey data from a sample of 1000 residents in the Tampa Bay metro area to understand how the market perceives, adopts, and adapts to transformative transportation technologies. The third phase of this research project focuses on the compilation and analysis of survey data in order to better understand people’s preferences and choices for future mobility options and technologies in the Tampa Bay metropolitan area. A comprehensive description of all the steps taken to full deployment, data cleaning, and weighting is provided, in addition to a descriptive weighted univariate illustration of the findings from the Tampa Bay survey sample.]]></description>
      <pubDate>Tue, 21 Jun 2022 09:35:18 GMT</pubDate>
      <guid>https://rip.trb.org/View/1983979</guid>
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    <item>
      <title>Attitudes towards Emerging Mobility Options and Technologies – Phase 2: Data Collection in Tampa, FL</title>
      <link>https://rip.trb.org/View/1746072</link>
      <description><![CDATA[Emerging transportation technologies including electric and autonomous vehicles and emerging mobility services such as ride-hailing and vehicle sharing are bringing about transformative changes in the transportation landscape. With the emergence of new transportation technologies and services, it is critical that transportation forecasting models be enhanced to account for behavioral dynamics that will result from the increasing penetration of disruptive forces in the transportation marketplace.  To enhance transportation forecasting models, people’s attitudes towards and perceptions of emerging technologies and services need to be measured and understood.  Armed with such an understanding, it will be possible to specify and develop behavioral models that account for attitudes and perceptions, adoption cycles, and adaptation patterns.  It is envisioned that such models will help decision-makers better plan transportation infrastructure systems and design marketing and policy strategies that maximize the benefits of these disruptive technologies. This project aims to collect survey data from a sample of 1000 residents in the Tampa Bay metro area to understand how the market perceives, adopts, and adapts to transformative transportation technologies. During the one-year duration of the project, the research team will review relevant behavioral studies, design the survey instrument and sampling plan, conduct a survey pre-test, perform full-fledged data collection through the administration of a comprehensive attitudinal and behavioral survey, compile and clean data, and produce reports and documentation. Thus, the focus of this phase-II effort is to collect a rich dataset of users’ attributes and current mobility choices, together with attitudes, perceptions and stated preferences towards new mobility options and technologies. It is envisioned that this project will result in the development of a data collection protocol and methodology that can be widely adopted in any jurisdiction interested in replicating the study.]]></description>
      <pubDate>Tue, 20 Oct 2020 18:29:07 GMT</pubDate>
      <guid>https://rip.trb.org/View/1746072</guid>
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