<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Research in Progress (RIP)</title>
    <link>https://rip.trb.org/</link>
    <atom:link href="https://rip.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
    <description></description>
    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
    </image>
    <item>
      <title>Advancing a Statewide Model for Multimodal Transportation Planning and Asset Management Integration in Rural and Small Urban Contexts</title>
      <link>https://rip.trb.org/View/2606412</link>
      <description><![CDATA[This research addresses the critical need for integrating transportation asset management (TAM) with transportation planning practices in rural and small urban contexts. Building on federal guidance from the Moving Ahead for Progress in the 21st Century Act (MAP-21) and subsequent legislation, the project will develop a statewide framework that strengthens the relationship between asset management and multimodal transportation planning across state, regional, and local agencies. The research focuses on three foundational components: meaningful stakeholder collaboration, high-quality integrated asset data, and aligned performance measurement processes. Using West Virginia as a pilot context, the study will evaluate current integration practices, assess multimodal asset data gaps, develop a prototype infrastructure database, and create a practitioner-focused toolkit for co-prioritization and performance-based decision-making. The methodology encompasses assessment of current practices, evaluation of data opportunities, database development, framework creation, and pilot implementation with selected agencies to test real-world applications and gather user feedback for refinement.]]></description>
      <pubDate>Thu, 02 Oct 2025 15:27:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/2606412</guid>
    </item>
    <item>
      <title>Opportunities and Challenges of Mobility-as-a-Service (MaaS) for Rural-Metro Communities: Case Study of the Rio Grande Valley, TX </title>
      <link>https://rip.trb.org/View/2459121</link>
      <description><![CDATA[Mobility-as-a-Service (MaaS) emerges as a potential solution to several contemporary transportation challenges. This technology aims to offer mobility options on a single application for which users can purchase the service rather than the means of transportation, integrating several mobility options, payment, and real-time information into a single application that is easily accessible. The Rio Grande Valley is a small urban and rural area challenged by automobile dependent urban form, traffic congestion from an exploding population, and limited mobility options for low-income and vulnerable people.. Few studies have explored the impact MaaS could have in a U.S. context, and even fewer have studied in small urban and rural contexts in the United States. This report demonstrates that while respondents are supportive of transit, their distances are conducive to multimodal use, and that they have easy access to smartphones and internet, that the car is almost exclusively used for travel trips. Finally, a MaaS offering in the Rio Grande Valley would face several, likely, insurmountable challenges, but that efforts should be undertaken to improve transportation options and experiences in the Rio Grande Valley.]]></description>
      <pubDate>Sat, 23 Nov 2024 11:06:04 GMT</pubDate>
      <guid>https://rip.trb.org/View/2459121</guid>
    </item>
    <item>
      <title>Optimizing Complete Streets through Best Practices and Simulation Analysis </title>
      <link>https://rip.trb.org/View/2397864</link>
      <description><![CDATA[This report, presents a comprehensive analysis on the optimization of Complete Streets through best practices. The concept of Complete Streets, which includes the design and operation of streets to safely accommodate all users, has fundamentally reshaped urban and suburban landscapes. The quarterly report probes the evolution and legislative integration of Complete Streets in the United States, noting significant progressions in policy, design, and community engagement. It highlights the shift from vehicle-centric to multimodal, people-centric urban planning, supported by rising urbanization, environmental concerns, and changing public attitudes towards active mobility. The report also examines best practices with emphasis on pioneering cities that have successfully implemented Complete Streets principles. These include traffic calming measures, protected bike lanes, enhanced pedestrian crossings, and other elements that contribute to safer urban environments. The report also discusses the economic, environmental, and technological impacts of Complete Streets, such as increased property values, improved public health, and the use of simulation tools to analyze and predict traffic patterns and user behaviors. This document can assist planners and policymakers in designing more effective and competent transportation systems that cater to the needs of the commuters.]]></description>
      <pubDate>Tue, 25 Jun 2024 11:21:09 GMT</pubDate>
      <guid>https://rip.trb.org/View/2397864</guid>
    </item>
    <item>
      <title>Digital Twins as a Catalyst for Sustainable and Smart Cities</title>
      <link>https://rip.trb.org/View/2350747</link>
      <description><![CDATA[This project aims to develop an urban digital twin for the city of Austin that assists city planners and managers to build a sustainable and smart city. The proposed urban digital twin will incorporate a data management and visualization platform, a real-time city monitoring system, an integration of predicting models, and a dynamic urban simulation environment to achieve effective city management, better resource allocation, more efficient transportation operation, and more proactive responses to risks. The data management and visualization platform will store and publish static and real-time urban data. The platform will enable API access and data download to facilitate third-party use. The real-time city monitoring system will access and process multiple data sources, including public real-time dataset, camera, and road sensors, for traffic monitoring and accident detecting. The digital twin will incorporate a traffic predicting model and a risk predicting model using graph-based deep learning methods. The project team will also build a dynamic urban simulation environment for the city of Austin, including a 3D city model, a road network model, and a traffic simulator. These digital twin modules will operate cooperatively by interacting with each other to synchronize real-world and virtual information. The expected outputs of this project include online platforms, software, technical reports, and research papers.]]></description>
      <pubDate>Tue, 12 Mar 2024 10:57:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2350747</guid>
    </item>
    <item>
      <title>
National Investigation of the Environmental, Safety and Livability Impacts of Travel Lane Width: Evidence from 10 American Cities</title>
      <link>https://rip.trb.org/View/2331768</link>
      <description><![CDATA[This project is one of the most comprehensive efforts to date to address a long overdue built environmental and transportation challenge to health: unnecessarily wide travel lanes that are designed to accommodate fast and convenient driving. There has been a constant competition for space in roadways’ right-of-way. In most American cities, the automobile is the winner of this competition, making it a challenge to find space for bike lanes and sidewalks. One of the easiest and most cost-efficient way to make space for cyclists and pedestrian is to narrow travel lanes and parking lanes to an optimal width. The main drawback is safety concerns. Are wider lanes safer? A recent study in seven US Cities by the PI found that narrower lanes do not have a higher number of crashes than their wider counterparts, after controlling for 21 functional and design street characteristics. This study builds on the earlier effort by (1) expanding sample to more than 1,500 street sections with three additional cities and measuring a comprehensive set of 21 micro-scale street design features for these streets; (2) quantifying the impact of narrow travel lane on traffic fatalities, pedestrian safety, and bicycle safety indicators; and (3) measuring the impact of narrow lane width on pedestrian volume and activities. Finally, from the national sample of ten cities, the PIs will select one lane width reduction project for further longitudinal analysis of traffic speed, roadway capacity (traffic volume), roadway safety (crash severity and frequency) and GHG emission impacts before and after the lane width reduction.]]></description>
      <pubDate>Thu, 01 Feb 2024 10:04:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/2331768</guid>
    </item>
    <item>
      <title>Exploring Shared Micromobility as an Alternative Transportation Option:
Opportunities and Challenges in U.S. Mid-sized Cities and Small Towns</title>
      <link>https://rip.trb.org/View/2265853</link>
      <description><![CDATA[With over half a billion trips taken in the United States (U.S.) since 2010, shared micromobility1 has quickly developed as an alternative to private automobiles, providing safer, cheaper, and more accessible ways for people to get around2. In tandem with the surge in shared micromobility, there is an exponential increase in privately owned micromobility devices, particularly in electric-assist bicycles (e-bikes) and scooters3. Micromobility’s alignment with key objectives and policies of U.S. transportation agencies is evident, as it has the potential to capture a new market of active transportation users and connect people to transit. Several cities and towns across the U.S. are exploring shared micromobility as an alternative transportation option for trips that are too far to walk but too short to drive.
Because micromobility is still a relatively new and emerging mobility option, most transportation agencies lack data-driven tools to measure the costs and benefits of shared micromobility systems. Agencies also lack guidance on integrating shared micromobility in the planning and designing of their transportation systems. Besides, micromobility is generally discussed with examples from major cities, with little to no discussion on the efficacy in mid-sized cities and small towns in rural areas. That is partly because micromobility modes thrive on high economies of density that rural areas lack.
This research aims to study the usage patterns of shared micromobility in mid-sized and small cities. Specifically, we aim to answer the following questions: (1) Who is using shared micromobility, and for what kinds of trips? (2) What factors affect shared micromobility device ridership? (3) Is the shared micromobility system adequately serving mid-sized cities and small towns? (4) What factors affect the safety of micromobility device users?
]]></description>
      <pubDate>Thu, 19 Oct 2023 16:44:01 GMT</pubDate>
      <guid>https://rip.trb.org/View/2265853</guid>
    </item>
    <item>
      <title>Expanding Rural Access to Non-Emergency Medical Transportation</title>
      <link>https://rip.trb.org/View/2071596</link>
      <description><![CDATA[River Cities Public Transit will receive funding to expand a program that provides transportation for oncology patients to a large hospital in central South Dakota to all types of patients within a 60-mile radius. The project will feature an integrated single payment system and allow Avera St. Mary's Hospital to hire a full-time transportation coordinator to advocate the service.]]></description>
      <pubDate>Mon, 28 Nov 2022 14:20:21 GMT</pubDate>
      <guid>https://rip.trb.org/View/2071596</guid>
    </item>
    <item>
      <title>The (In)Equitable Distribution of Quality Bicycling Infrastructure</title>
      <link>https://rip.trb.org/View/1944008</link>
      <description><![CDATA[This project seeks to investigate the development of bicycling infrastructure through a transportation justice lens. More specifically, how equitable has the distribution of this infrastructure been across the socioeconomic/sociodemographic spectrum? The authors will also seek to investigate whether the installation of bicycling facilities leads to socioeconomic/sociodemographic changes in a neighborhood or vice versa. While the authors will not be able to resolve this causality dilemma, the authors will be able to identify the strength and direction of these relationships. The authors will answer these research questions via an exhaustive, longitudinal data collection effort – for at least ten U.S. cities – combined with statistical analysis. The results will assist cities and DOTs in managing and monitoring their bicycling infrastructure, assessing its equality, as well as understanding the potential implications for those that live and work in these neighborhoods. The results of this project will benefit cities looking to better understand, manage, and monitor their bicycling infrastructure while also providing them with a better understanding of the neighborhood/housing impacts associated with infrastructure decisions.
]]></description>
      <pubDate>Sun, 04 Sep 2022 15:04:28 GMT</pubDate>
      <guid>https://rip.trb.org/View/1944008</guid>
    </item>
    <item>
      <title>State DOT Policies Affecting Adaptive Street Use: Learning from
COVID19 Experiences (Project E6)</title>
      <link>https://rip.trb.org/View/2004433</link>
      <description><![CDATA[This project examines local and state level responses to changing demands on public street space
during the COVID-19 pandemic. Cities across the US moved quickly to reallocate street space to
accommodate increased need for space to walk, cycle, or engage in outdoor commerce.
However, such actions were underrepresented in southeastern US cities. The research team seeks to identify state
level actions—policies, resources, expertise—from other regions that facilitated rapid local responses
and evaluate their transferability to southeastern US cities. The team uses existing data sources on
local COVID-19 actions, which the team will supplement with structured interviews with state-level
officials in a sample of US states that enacted strong supports for local street space adaptations.]]></description>
      <pubDate>Wed, 10 Aug 2022 13:55:46 GMT</pubDate>
      <guid>https://rip.trb.org/View/2004433</guid>
    </item>
    <item>
      <title>Impact of Autonomous Vehicle (AV)-Based on Demand Transportation Services on Traffic Crashes</title>
      <link>https://rip.trb.org/View/1948953</link>
      <description><![CDATA[There has been two recent major advancements in the area of transportation industry which facilitated the mobility across the nation. The first technological advancement has brought Autonomous Vehicles (AVs) into reality, and the other major advancement is the emergence of on-demand ride services which has overcome many of the conventional travel barriers and improved personal mobility options. Although some studies explored the benefits and positive outcomes of both AVs and on-demand services; however, there are some other studies which found different outcomes and do not recommend the technology and service for safety reasons. Therefore, there is a need to study the impact of AV-based on-demand services on crashes as this will be future of the transportation systems in various cities and states. This study aims to evaluate the impact of AV-based on demand transportation services on traffic crashes with different severity levels. This project will analyze the (1) impact of the AV-based on-demand transportation services on frequency (number of) of crashes, (2) impact of the AV-based on-demand transportation services on total number of injuries, and (3) impact of the AV-based on-demand transportation services the number of serious injuries to analyze the crash patterns before and after the deployment of these services. To successfully achieve the objectives of this project, this study will use the data from City of Arlington, Texas Department of Transportation (TxDOT), and Arlington RAPID project. Arlington RAPID project is an implementation case study which has integrated the AVs into on-demand transportation services in Arlington, Texas. This study will use Difference in Difference, Time Series analysis, and Multivariate Regression modeling to evaluate the safety aspects of this integration and develop models for planners and policy-makers to estimate the changes in the number and severity of the crashes in their area while integrating AVs into their on-demand public transportation services. The results will be implemented in three other cities with different congestion and populations. The outcomes of this study will help with the planning for future deployment of AVs and integration of them into on-demand transportation services.]]></description>
      <pubDate>Mon, 09 May 2022 11:04:06 GMT</pubDate>
      <guid>https://rip.trb.org/View/1948953</guid>
    </item>
    <item>
      <title>One-to-Many Simulator Interface with Virtual Test Bed for Equitable Tech Transfer</title>
      <link>https://rip.trb.org/View/1942832</link>
      <description><![CDATA[After five years of R&D, researchers have developed a number of independent simulation tools to evaluate different algorithms. A broad API will be developed to handle interfacing any simulation with a multi-agent demand simulator. This will be tested on the existing MATSim-NYC (which will be enhanced to include freight and parcel delivery activities) and a BEAM implementation, BEAM-NYC, for three use cases in electric transit, freight, and traffic, considering equity impacts on different population segments (by income level, ability, and age). The team will jointly conduct case studies in NYC and Seattle, enabling deeper insights of evaluated cases and promote tech transfer and collaboration to broader communities (including agencies, the industry, and the public).]]></description>
      <pubDate>Fri, 22 Apr 2022 11:11:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/1942832</guid>
    </item>
    <item>
      <title>Implementation and Quantitative Evaluation </title>
      <link>https://rip.trb.org/View/1938504</link>
      <description><![CDATA[This project will implement the integrated MMOS in Salt Lake City to evaluate the strategic directions envisioned by the Center. Additionally, researchers will work directly with staff from San Francisco County Transportation Authority (SFCTA) and the Metropolitan Transportation Commission (MTC) to transfer the MMOS to their context. By implementing the MMOS for both a medium and a large city we will be able to evaluate the effects of the strategic directions in different contexts and set ourselves up for tech transfer to other regions.  Further, by making the MMOS work in two settings, the center designs transferability into the system from the start, thus facilitating future adoption.  
A major objective of this project is to leverage data being collected in each region so that the MMOS can be calibrated to realistic behavior where feasible. In San Francisco, a data set of ride-hail vehicle traces scraped from the Application Programming Interfaces (APIs) of two ride-hail companies is available for this task. This data-centric approach is important, because research to date on the topic has been hampered by a lack of data on ride-hailing and transit interactions.   
The result of this project will be an evaluation of how the on-demand multi-modal transit systems differ in the two contexts, and how they differ from ride-hail use.  This assessment will provide a better understanding to transit operators for the contexts in which such systems might be most effective.
The models are being simultaneously developed in a collaboration with staff from SFCTA and MTC in San Francisco, and with WFRC and UTA in Salt Lake City. These external collaborators join weekly meetings to inform of local situations, supply data, and learn of the project’s progress and purposes. ]]></description>
      <pubDate>Wed, 06 Apr 2022 15:14:19 GMT</pubDate>
      <guid>https://rip.trb.org/View/1938504</guid>
    </item>
    <item>
      <title>Investigating the Impact of COVID-19 Pandemic Outbreak on Bike Share Usage and Ridership: A Case Study in Houston</title>
      <link>https://rip.trb.org/View/1881802</link>
      <description><![CDATA[Public bicycle share systems have increased from operating in a few European cities to expanding in the United States at an increasing pace. During the COVID-19 pandemic outbreak, people may opt to bike instead of riding transit to avoid exposure to the coronavirus.
The goal of this project is to investigating the impact of COVID-19 pandemic outbreak on bicycling mode share. The research is developed based on the CAMMSE theme of addressing the FAST Act research priority area of “Improving Mobility of People and Goods.” The research is relevant to three CAMMSE research thrusts, “Innovations to improve multi-modal connections, system integration and security” and “Develop data modeling and analytical tools to optimize passenger and freight movements.” Specific project objectives include:
(a)	Identify potential attributes related to bike sharing demand,
(b)	Examine the trip distribution of bike share users throughout the four seasons of the year, and the different hour blocks of a day,
(c)	Model bike share station activity,
(d)	Examine and locate the dock stations in relation to potential demand, and
(e)	Investigate system users and impacts on the bike share.
]]></description>
      <pubDate>Mon, 04 Oct 2021 12:12:21 GMT</pubDate>
      <guid>https://rip.trb.org/View/1881802</guid>
    </item>
    <item>
      <title>Potential Impact Analysis of Driverless-Cars on Megaregion Traffic Flow Patterns</title>
      <link>https://rip.trb.org/View/1878139</link>
      <description><![CDATA[This study aims to further previous research, GIS-based Megaregion Transportation Planning Model, into the application of self-driving vehicles, developing planning strategy in by sustainable transport system as a series of travel demand modeling. The Year 1 through 3 proposals focused on developing database of freight mobility and identifying its travel patterns. The two-year proposal develops an analytical framework to load not only traditional passenger/freight flows but driverless cars to comprehensively predict the near future travel patterns in Texas mega cities, especially
Dallas-Fort Worth and Houston. Its novel approach will help to develop a foundation for promoting sustainable aspect of emerging transportation as a benchmarking tool.]]></description>
      <pubDate>Wed, 15 Sep 2021 13:13:37 GMT</pubDate>
      <guid>https://rip.trb.org/View/1878139</guid>
    </item>
    <item>
      <title>A Systems-Level Analysis of Left-Turning Vehicle-Pedestrian Crashes</title>
      <link>https://rip.trb.org/View/1846422</link>
      <description><![CDATA[Left-turning vehicle-pedestrian crashes have long been dangerous for pedestrians in situations when drivers should be yielding the right of way. They outnumber right-turning vehicle-pedestrian crashes by a factor of 3 to 1 and are grossly overrepresented in terms of crash severity. If a driver does not properly yield, it is easy for traffic engineers to tally such crashes among the more than 90% of crashes that are attributed to human error. Yet, an accumulation of challenging conditions for a driver suggests that left-turning vehicle-pedestrian crashes are systematic problems and not random crashes caused by human error.

Accordingly, the proposed project seeks to take a system-level approach to studying this crash type via an empirical, macroscopic analysis of eight cities across multiple years. This includes: (1) determining where this crash type is over- or under-represented while controlling for the level of pedestrian activity; and (2) statistically evaluating what combination of signal, design, and/or policy approaches associates with better or worse safety outcomes while also accounting for crash migration. Instead of focusing solely on signalization solutions, as is common in the existing literature, the intent is to shed light on how cities can employ a combination of approaches.]]></description>
      <pubDate>Tue, 13 Apr 2021 16:30:32 GMT</pubDate>
      <guid>https://rip.trb.org/View/1846422</guid>
    </item>
  </channel>
</rss>