<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>Using Artificial Intelligence to Uncover How Safety Perception Influences Travel Behavior Shifts: Comparative &amp; Longitudinal Analysis for the Future of Autonomous Vehicle, Transit and Ride-hailing Services</title>
      <link>https://rip.trb.org/View/2655700</link>
      <description><![CDATA[Transit agencies and cities are increasingly overwhelmed by large volumes of unstructured data; yet they lack methodical, validated tools to turn safety narratives into operational indicators. This project addresses that gap by measuring and comparing public safety perception for autonomous-vehicle services (robotaxis), public transit, and ride-hailing services. It will assess how these perceptions relate to traveler profiles and mode choice in San Francisco and San Jose over a six-month period. San Francisco as a mature setting where robotaxis may compete with ride-hailing and transit, and San Jose as a newer coming deployment that provides a baseline for comparison and forward-looking extrapolation.
The research team will use artificial intelligence with human-audited classification to analyze public discourse drawn from news-comment threads and social-media posts, for example, discussions of disengagements, curb conflicts, yielding behavior, and interpersonal harm such as unwanted contact, theft, or assault. Validation will include human audit with inter-rater reliability (aiming for Cohen’s kappa of at least 0.60), time- and city-based cross-validation, and an error taxonomy with documented adjustments. The project will deliver (1) a transparent safety-perception taxonomy, (2) traveler-persona profiles linked to safety perceptions, (3) a lightweight dashboard for agencies and cities to explore time, place, and topic trends, and (4) operational and policy frameworks for improvements across all modes, organized into vehicle-level safety measures, station and hub operating practices, reporting and response mechanisms, and rider communication standards. The approach and workflow are replicable and can be extended to additional cities. The innovation lies in a reusable tool bridging research and practice providing concrete, methodical steps to turn qualitative narratives into consistent indicators they can trust. Agencies can adopt it to sort and prioritize incoming signals, rerun it with new data, and compare results across time and places to support day-to-day decisions and longer-term planning.]]></description>
      <pubDate>Mon, 19 Jan 2026 16:09:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/2655700</guid>
    </item>
    <item>
      <title>Are Automonous Vehicles Safer Drivers than Humans? Comparing performance in San Francisco</title>
      <link>https://rip.trb.org/View/2625584</link>
      <description><![CDATA[This research project seeks to determine if automated vehicles (AVs) are safer drivers than humans by comparing their pedestrian interaction behaviors and yielding performance in real-world conditions in San Francisco. The study will be framed by the city's "Focus on Five" strategy, which targets the five moving violations most commonly associated with traffic fatalities. Researchers will conduct evaluations of two focus violations, with the first being a comparison of the compliance of AVs and human drivers in yielding to pedestrians in a crosswalk. To gather data, the team will install high-resolution video cameras at two or more crosswalks with no traffic control for a period of one to three weeks to passively record vehicle-pedestrian interactions. Machine learning-based computer vision methods will then be used to automatically classify vehicles as either automated or human-driven. Following this classification, researchers will review the footage to code each interaction, noting if the vehicle yielded to the pedestrian. Finally, the performance of the two groups will be compared using two-sample t-tests to determine if any observed differences are statistically significant. A parallel analysis will be conducted for a second violation, to be determined.]]></description>
      <pubDate>Tue, 18 Nov 2025 15:14:24 GMT</pubDate>
      <guid>https://rip.trb.org/View/2625584</guid>
    </item>
    <item>
      <title>Synthesis of Information Related to Transit Practices. Topic SD-07. Red Tinted Bus Lanes Experience</title>
      <link>https://rip.trb.org/View/2190448</link>
      <description><![CDATA[Bus lanes have been around for decades and were initially identified with white pavement markings. Tinted pavement bus lanes first surface in international cities. In the US, city bus lanes conformed to signage and markings described in the Manual for Uniform Traffic Control Devices (MUCTD). This began to change in 2017 with pilot tinting allowed by the Federal Highway Administration (FHWA) and was formally approved by the FHWA in 2020. Since then, many cities have implemented red tinted bus lanes as part of both bus rapid transit (BRT) projects and non-BRT bus lane projects. The expansion of the concept suggests wide success, but little is known about their successes/failures and policy, technical and operational issues. How do tinted bus lanes compare to physically separated exclusive BRT lanes? What have been key factors to the success of the painted bus lanes and what are the key challenges? Observations in San Francisco indicate that right turning motorists better understand the red tinting and that enforcement is critical to their success. Other regions are exploring this approach as a means to help motorists better navigate an increasingly multimodal arterial cross-section. Foundational questions remain - are the tinted lanes safer, do they improve operations and how important is enforcement?
OBJECTIVE: The objective of this synthesis is to document the current state of practice in the performance and implementation of red tinted bus lanes. ]]></description>
      <pubDate>Mon, 05 Jun 2023 16:44:18 GMT</pubDate>
      <guid>https://rip.trb.org/View/2190448</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>Multi-Agent Simulation</title>
      <link>https://rip.trb.org/View/1938502</link>
      <description><![CDATA[The objective of this project is to develop a simulation model capable of representing tradeoffs between fixed route transit, coordinated on-demand transit, independent ride-hail operators, and other travel modes. Regional travel models as currently constructed do not attempt to handle the intricate relationship between supply for and demand of on-demand transit and independent ride-hail services. The simulation is being implemented in the BEAM transportation demand simulator to evaluate the strategies envisioned by the Center with the necessary choice of coordinated and competing modes. 
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 15:10:03 GMT</pubDate>
      <guid>https://rip.trb.org/View/1938502</guid>
    </item>
    <item>
      <title>Multi-Modal Optimization </title>
      <link>https://rip.trb.org/View/1938501</link>
      <description><![CDATA[The objective of this project is to develop the multi-modal optimization model, which will operate at a planning level and generate an optimal design for a multi-modal on-demand transit system given the input demand and constraints. Optimization models provide a means of providing the best possible outcome as measured by an objective, subject to a set of constraints. 
The starting point for this model was developed for a NSF-funded project - Socially Aware Mobility (SAM) project – that seeks to design coordinated microtransit systems in large, congested cities. These systems combine on-demand transit that serve low-density regions with high-occupancy vehicles (buses or trains) traveling along high-density corridors.  
These systems combine on-demand transit (cars or vans) that serves low-density regions with high-occupancy vehicles (buses or trains) traveling along high-density corridors. The scheduling and dispatching of vehicles is coordinated holistically and optimized to achieve socially desirable outcomes such as mitigating congestion, decreasing cost, improving accessibility, and providing the service efficiently.  
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 15:07:24 GMT</pubDate>
      <guid>https://rip.trb.org/View/1938501</guid>
    </item>
    <item>
      <title>Towards Inferring Welfare Changes from Changes in Curbside Parking Occupancy Rates: A Theoretical Analysis Motivated by SFpark and LA Express Park</title>
      <link>https://rip.trb.org/View/1441934</link>
      <description><![CDATA[The structural model has three components. The first relates welfare to the mean number of curbside parking spaces searched, for multiple cruising-for-parking strategies. Using traffic microsimulation on an idealized network, the second relates the mean number of curbside parking spaces searched to the occupancy rate, again for multiple cruising strategies. The third aims to statistically infer cruising strategy by comparing how local meter rate changes affect global occupancy rates in the data versus from simulations for different cruising strategies.]]></description>
      <pubDate>Wed, 04 Jan 2017 10:57:11 GMT</pubDate>
      <guid>https://rip.trb.org/View/1441934</guid>
    </item>
    <item>
      <title>Development and Demonstration for Integrated Dynamic Transit Operations System (IDTO)</title>
      <link>https://rip.trb.org/View/1441780</link>
      <description><![CDATA[The task will develop a fully functional Integrated Dynamic Transit Operation (IDTO) prototype system that builds upon Dynamic Traveler information, several dynamic operations, including dynamic demand responsive transit operations, Dynamic Dispatch (T-DISP) and Connection Protection (T-CONNECT). T-DISP will allow public transit to be responsive to public needs by enabling the transit agency and the public to communicate with each other. T-CONNECT will ensure that the public will be able to transfer from one transit agency to another (i.e. between buses) even if a system is running ahead or behind schedule. This prototype IDTO will be tested and demonstrated in a full scale test site in East Contra Costa County of the San Francisco East Bay operated by Tri-Delta Transit.]]></description>
      <pubDate>Wed, 04 Jan 2017 10:52:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/1441780</guid>
    </item>
    <item>
      <title>Transferability &amp; Forecasting of the Pedestrian Index Environment (PIE) for Modeling Applications</title>
      <link>https://rip.trb.org/View/1420159</link>
      <description><![CDATA[There have been important advances in non-motorized planning tools in recent years, including the development of the MoPeD pedestrian demand model (Clifton et al., 2013, 2015). This tool and others are increasingly requested by governments and agencies seeking to increase walking activity and create more walkable places. To date, the MoPeD tool has been piloted with success in the Portland region using data unique to Metro, the metropolitan planning organization. However, there is increasing interest from planning agencies within and outside of Portland and Oregon (e.g.: City of Tigard, OR; Metropolitan Council of the Twin Cities, MN; San Francisco Public Health Department, CA) about adapting the pedestrian modeling tools for use in their own jurisdictions. Local governments desire to apply these tools for a variety of planning and forecasting purposes, not only for regional demand modeling. Unfortunately, other regions often do not have uniform access to the same kinds of pedestrian environment data as Metro, particularly at such a fine-grained scale. Important challenges remain in model development that must be overcome if these tools are to achieve widespread application. Among the most critical needs are the standardization and forecasting of model inputs, particularly measures of the built environment. In this next phase of the pedestrian modeling work (see Clifton et al., 2013, 2015), the project team will propose focusing on making our measures, models, and methods more transferable to other locations. Specifically, the project team will re-evaluate, compare and test our pedestrian index of the environment (PIE) measure using data resources more commonly available to planning agencies across the country. Next, the project team will re-estimate our pedestrian trip generation and destination choice models using this new PIE variable. The updated MoPeD will then be ready for further validation in Portland and testing in other regions (Twin Cities) and contexts (suburban Tigard). This process will also consider how PIE may be forecast to reflect future planning scenarios. These tasks will balance data availability, scale, computational capacity, and behavioral realism. This proposed project continues the team’s efforts to advance pedestrian demand modeling tools available for planning analysis and forecasting. In the past 5 years, the project team have completed 2 projects funded by National Institute for Transportation and Communities/Oregon Transportation Research and Education Consortium (NITC/OTREC) (in partnership with Metro) to improve the representation of pedestrians in travel demand models. As a result of these projects, the project team have created a framework model of pedestrian demand (MoPeD) that integrates into trip-based regional models (Clifton et al., in press), estimated models for pedestrian trip generation (Clifton et al., 2013) and destination choice (Clifton et al., 2015), and developed a pedestrian index of the environment (PIE) measure (Singleton et al., 2014). This proposed work program represents the next logical step in the MoPeD’s enhancement and is critical to enabling its utility beyond the Portland region. The project team remains the same, continuing an 11-year collaboration on pedestrian modeling between Dr. Kelly Clifton (PI) and Dr. Robert Schneider]]></description>
      <pubDate>Tue, 16 Aug 2016 16:34:15 GMT</pubDate>
      <guid>https://rip.trb.org/View/1420159</guid>
    </item>
    <item>
      <title>Condition Monitoring of Urban Infrastructure: Effects of Ground Movement on Adjacent Structures</title>
      <link>https://rip.trb.org/View/1236221</link>
      <description><![CDATA[Underground space is an essential element critical to the solution of many problems associated with the emerging large urban clusters around the US and worldwide. Many of these urban clusters have developed initially as smaller, relatively independent entities which have grown into heavily interdependent clusters of entities. This interdependence has wide ranging implications related to transportation. Planners increasingly are finding that underground space is one of the few options available to solve the myriad of problems posed by these urban clusters. For example, in the San Francisco Bay Area several underground construction projects are in various phases of design and construction to eliminate important transportation bottle necks (e.g. MUNI central subway, Silicon Valley Rapid Transit, Trans Bay Terminal). Similar projects are underway in Seattle and New York. Damage to buildings adjacent to excavations is a major design consideration when constructing underground facilities in congested urban areas. As new infrastructure is constructed or existing infrastructure rehabilitated, the excavations required for tunnels or basements affect nearby existing buildings, especially those founded on shallow foundations. Often excavation support system design must prevent any damage to adjacent structures or balance the cost of a stiffer support system with the cost of repairing damage to the affected structures. Similarly, tunnel operations often times include provisions, such as compensation grouting, to keep minimize the ground deformations associated with tunneling. In either case, it is necessary to predict the ground movements that will induce damage to a structure. Practically speaking, a designer is attempting to limit/prevent damage to either the architectural details of a building, which occurs prior to structural damage, or to load bearing walls. To evaluate damage potential in buildings affected by ground movements resulting from deep excavations, one must first predict the magnitude and distribution of ground movements caused by the excavation. This may be done using empirical or finite element methods, depending on the importance of the building, budget considerations, and design phase of the investigation. After locating the affected building in relation to the expected ground movements, one then evaluates the impact of these movements on the building. The main two sources of uncertainties in this analysis are the structural evaluation of the affected building and the movement prediction. The key issue in the structural evaluation is to define the level of ground movements that will prevent or minimize damage to the adjacent structures. This depends on the type of building that is being impacted by the operations, resulting in a wide range of possible allowable movements. In many projects, the allowable movements are set arbitrarily, and without consideration of the details of either the structures to be protected or the ground conditions. In past work funded by Infrastructure Technology Institute (ITI), the projects have focused on the predictions of the ground movements. This work with real time monitoring systems at a number of excavation sites in Chicago and Seattle allowed us to develop an adaptive management approach that can be used to predict ground deformations under a variety of ground and support conditions. A key aspect of the methodology is the incorporation of the real time monitoring as a means to help guide construction activities and to allow a quantitative approach to find key soil parameters based on field performance data that result in an accurate prediction of the ground movements caused by excavation. The objectives of this proposal are to collect and evaluate detailed ground and building movement data not normally collected during excavation monitoring to allow development of rational criteria for establishing allowable ground movements associated with excavations. In particular, it is proposed to monitor the ground movements caused by the excavation for the William Jones High School in Chicago and to evaluate the effects of these deformations on two adjacent structures founded on shallow foundations. To this latter end, it is proposed to monitor the movements of the two buildings most affected by the cut. This project provides the opportunity to evaluate in detail the effects of excavation-induced ground movements on the existing buildings. This data will be supplemented with building movements caused by excavation obtained by the PI at several other excavations in the Chicago area. It is likely that the damage levels will be very slight at these buildings, as they were at the other case studies, so that conclusions can be drawn regarding the relation between the deformations at the foundation level at an impacted structure and the initiation of damage. These magnitudes can be used as a basis for setting rationale criteria regarding allowable deformations. 2.0 Excavation for the William Jones High School The proposed structure is located at the southeast corner of State and Polk Streets south of the Loop in Chicago. The proposed excavation is approximately 100 ft by 400 ft in plan, will be 18 ft deep. The excavation will be made using bottom up techniques with a temporary lateral support system consisting of a sheet pile wall supported laterally by two levels of cross-lot bracing. The soil conditions generally consist of about 14 ft of urban fill overlying a sequence of glacially-derived clays. This stratigraphy is typical of those found in the downtown area of Chicago with the important exception at this location of the presence of a very soft clay stratum that underlies the excavation. Because of this soft clay, there is a potential of ground movements that may cause damage to adjacent buildings in spite of the relatively shallow cut. There is a narrow alley that separates the excavation and three buildings, two of which are founded on shallow foundations, at this side of the cut. Access through the alley must be maintained throughout construction. These buildings are 6 and 7 stories with one basement level. Beneath State Street to the west of the site, there are an existing subway, as well as electric, gas, sewer and water lines that will be impacted by the excavation. Along the south end of the site, there is an abandoned 8-ft-diameter city water tunnel located about 60 ft below ground surface. Because of the presence of the public utilities and existing buildings, the Board of Underground of the City of Chicago has dictated that surface settlement points be established and monitored around the site to monitor the ground response close to these utilities, and that inclinometers be placed around the property line to measure lateral movements within the subsurface to evaluate the effects of the excavation on the buildings and utilities. Hayward Baker, Inc., the excavation support subcontractors and designers of this system for the project, is our partner for this project. The matching funds for this project are derived from the excavation support system for the project, the excavation costs and the conventional instrumentation installed at the site, and the effort to collect the conventional performance data. The letter of support is appended to this proposal.]]></description>
      <pubDate>Thu, 03 Jan 2013 15:43:08 GMT</pubDate>
      <guid>https://rip.trb.org/View/1236221</guid>
    </item>
  </channel>
</rss>